Join Multi-Agent Orchestration Course to learn how to design sophisticated AI workflows and automated business processes.

Use promo code LEVERAGINGAI100 for $100 off - https://multiplai.ai/multi-agent-orchestration-course/

What if your next accounting mistake could be caught by AI before it ever reaches your financial reports?

From messy general ledgers to time-consuming reconciliations, accounting can drain valuable resources. But Claude AI is changing what's possible, helping businesses turn raw financial data into structured reports, identify discrepancies, and automate repetitive work.

In this episode of Leveraging AI, host Isar Meitis sits down with Maksims Sičs, co-founder of the Microsoft Excel World Championship and founder of Flowbyte AI, for a practical demonstration of AI-powered accounting automation. Watch how Claude transforms months of general ledger data into Excel-based profit and loss statements and balance sheets, while flagging errors that might otherwise go unnoticed.

In this session, you'll discover:

How to use Claude AI to automate accounting workflows without complex technical skills.How to turn six months of general ledger data into structured P&L statements and balance sheets.Why asking AI to use Excel formulas instead of hard-coded numbers makes financial reports easier to audit and update.How to provide the right business context to reduce AI assumptions and improve accuracy.How Claude can identify duplicate invoices, VAT discrepancies, unusual transactions, and missing information.How to use AI to reconcile financial data and simplify monthly accounting reviews.Why these same AI automation principles can work across other business operations.

Maksims Sičs is a finance professional, co-founder of the Microsoft Excel World Championship, and founder of Flowbyte AI, where he helps businesses automate operational processes using artificial intelligence.

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

Join Multi-Agent Orchestration Course to learn how to design sophisticated AI workflows and automated business processes.

Use promo code LEVERAGINGAI100 for $100 off - https://multiplai.ai/multi-agent-orchestration-course/

What happens when AI becomes your best employee, your biggest competitor, and your newest cybersecurity threat—all at once?

AI is no longer just changing how businesses operate. It's changing how hackers attack, how customers shop, and how companies compete. And while businesses are racing to adopt AI, the technology is moving faster than many organizations can adapt.

The solution isn't to slow down AI adoption. It's to get smarter about where you invest, how you protect your business, and how you prepare for an increasingly agent-driven economy.

In this episode of the Leveraging AI podcast, host Isar Meitis connects the dots between accelerating AI cybersecurity threats, the rise of agentic commerce, and the increasingly important question of AI's return on investment.

From AI agents finding ways around security restrictions to Google's changing search experience, Stripe's agentic payments infrastructure, and the growing gap between AI-powered shoppers and unprepared merchants, this episode explores what business leaders need to understand now.

In this session, you'll discover:

The new cybersecurity reality: How AI agents are discovering vulnerabilities, bypassing security boundaries, and enabling cyberattacks at a speed and scale that traditional defenses struggle to match.Why businesses must rethink cybersecurity: The emerging risks highlighted by incidents involving AI agents, financial institutions, critical software infrastructure, and Binance.The practical steps leaders should take: Why software updates, cybersecurity risk assessments, and reviewing insurance coverage deserve immediate attention.How AI is rewriting the rules of search: Why Google's AI Overviews are changing website traffic, customer discovery, and the value of traditional SEO.The rise of AI-powered advertising: How autonomous agents are beginning to plan, buy, and optimize advertising campaigns.Why agentic commerce matters: How Stripe, Visa, and Mastercard are building payment infrastructure for a future where AI agents can transact on behalf of customers.The opportunity hiding in merchant unreadiness: Why businesses that prepare for AI-assisted purchasing could gain an advantage over slower competitors.The latest developments from AI leaders: News involving Anthropic's IPO filing and Google's emerging model capabilities.

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

Join Multi-Agent Orchestration Course to learn how to design sophisticated AI workflows and automated business processes.

Use promo code LEVERAGINGAI100 for $100 off - https://multiplai.ai/multi-agent-orchestration-course/

What happens when your next customer asks ChatGPT for a recommendation—and your business isn't part of the answer?

Traditional SEO still matters. But ranking on Google's first page is no longer the whole game. As ChatGPT, Gemini, Claude, and AI-powered search tools reshape how people discover businesses, getting cited and recommended by AI is becoming a competitive advantage.

The solution? Build a smarter content strategy that works for both traditional search engines and AI agents. In this episode of the Leveraging AI Podcast, host Isar Meitis sits down with AI marketing and SEO expert Ryan Doser to break down how businesses can improve their AI search visibility, automate content creation, and turn existing content into a scalable marketing engine.

Ryan shares his practical workflow using Claude Code, ChatGPT Codex, AI skills, and SEO data tools. He also demonstrates how a single YouTube video can become an SEO-optimized article, visual content, and a promotional email—all through an automated process.

In this session, you'll discover:

Why traditional SEO isn't dead, but ranking on Google is no longer enough.How to get your business discovered and cited by ChatGPT, Gemini, Claude, and Google AI Search.How Ryan combines Claude Code and ChatGPT Codex to build automated SEO and content marketing workflows.How to turn one YouTube video into multiple optimized marketing assets using AI agents.What real-world SEO experiments reveal about AI-generated websites and search rankings.How to prepare your website for a future where AI agents—not just humans—are discovering your content.

Ryan Doser is a digital marketing and SEO specialist with over 10 years of experience. He runs his own business, helping companies attract and nurture leads through digital marketing and AI-powered search strategies.

Ryan combines his marketing expertise with AI tools to develop automated workflows for content creation, search optimization, and website publishing.

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

Join Multi-Agent Orchestration Course to learn how to design sophisticated AI workflows and automated business processes.

Use promo code LEVERAGINGAI100 for $100 off - https://multiplai.ai/multi-agent-orchestration-course/

Is AI creating the biggest business opportunity of our lifetime—or setting us up for a spectacular crash?

Billions are pouring into AI. Companies are reporting extraordinary productivity gains. And the people building the most advanced models are raising serious alarms about what comes next. The opportunity is enormous, but so are the risks—and business leaders can't afford to ignore either side.

In this episode of Leveraging AI, Isar Meitis cuts through the headlines to examine the AI bubble debate, reveals what Anthropic's internal productivity data means for the future of work, and explores why a former OpenAI safety insider is sounding the alarm. From AI agents transforming business operations to emerging cybersecurity threats, this is a reality check every business leader needs.

In this session, you'll discover:

AI bubble or business boom? Why experts disagree about the sustainability of AI investments, and what a potential market correction could mean for businesses.The productivity revolution is already happening. How Anthropic reports a fivefold increase in code output and significant efficiency gains across sales, legal, finance, and recruiting.The 75% wake-up call. Why Anthropic employees expect AI to handle 75% of their work by 2030, while the general US public expects just 28%.The future of hiring is changing. Why AI is reducing demand for some junior roles and shifting the focus toward judgment, autonomy, and strategic thinking.An OpenAI insider's warning. Why former safety employee David Robinson resigned and what his concerns reveal about AI development, alignment, and release pressures.AI-powered cybercrime is escalating. How agents are being used to attack financial institutions, discover critical software vulnerabilities, and potentially compromise security monitoring systems.What leaders should do now. Why AI education, workforce planning, smarter automation, and measurable productivity outcomes should be strategic priorities.

The bottom line? Whether AI is in a financial bubble or not, its impact on business operations is already very real. The challenge isn't simply adopting more AI. It's building an organization that knows how to use it effectively, safely, and strategically.

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

Want to build powerful AI agents and automate complex business workflows? Join the Multi-Agent Orchestration Course and use code LEVERAGINGAI100 for $100 off: https://multiplai.ai/multi-agent-orchestration-course/

What if the biggest problem with your AI-generated content isn't what it says, but the fact that everyone knows AI wrote it?

AI can write your emails, proposals, social media posts, and marketing content in seconds. But when everything sounds like the same generic chatbot, efficiency comes at the expense of authenticity. And for business leaders, that can damage the relationships and credibility they've spent years building.

The solution isn't to stop using AI. It's to teach AI how to communicate like you.

In this episode of Leveraging AI, Isar Meitis sits down with Jonathan Mast, founder of White Beard Strategies and AI coach, to demonstrate a practical, four-step process for teaching ChatGPT, Claude, Gemini, and other AI tools to capture your unique voice, writing style, and brand personality.

You'll learn how to create a reusable AI voice guide and turn it into an AI skill that helps produce consistent, authentic content across different tools and business workflows.

In this session, you'll discover:

Why generic AI-generated content can undermine your brand and professional credibility.How to quickly personalize ChatGPT using a personality profile.The four-prompt framework for creating a detailed AI voice and writing style guide.Why your emails, meeting transcripts, and natural conversations are valuable training examples.How to turn your voice guide into a reusable AI skill for ChatGPT, Claude, and other AI tools.Why testing and refining your AI skill is essential for reliable results.How businesses can share brand voice skills across teams to maintain consistent communication at scale.

Resources: Download Jonathan's four-prompt AI voice framework: https://docs.google.com/document/d/1T9gc0zvwEG8FsRwJvWF9lNlfiUHBUrYuW6H1V1tgoWA/edit?usp=sharing

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

Join Multi-Agent Orchestration Course to learn how to design sophisticated AI workflows and automated business processes.

Use promo code LEVERAGINGAI100 for $100 off - https://multiplai.ai/multi-agent-orchestration-course/

What happens when one developer can recreate an entire software empire in two weeks? And what happens to your business when AI agents can do the work of entire teams?

The rules of business software are changing. AI can now help recreate complex applications, connect directly to enterprise data, and automate workflows that once required entire departments. Meanwhile, Google, Anthropic, Microsoft, and Meta are racing to make AI agents more powerful, accessible, and affordable.

In this week's Leveraging AI news episode, Isar Meitis breaks down the developments business leaders cannot afford to ignore. From an AI developer challenging Adobe and Microsoft to new enterprise AI agents, frontier models, escalating cybersecurity threats, and the growing impact of AI on employment, this episode connects the headlines to the decisions CEOs need to make today.

In this session, you'll discover:

How one developer used AI to recreate alternatives to Photoshop, Excel, PowerPoint, and other major applications—and why this could threaten the traditional SaaS business model.Why businesses spending hundreds of thousands of dollars on software subscriptions should reconsider the economics of building their own tools.How Claude, Gemini, and Microsoft are turning enterprise software into environments where AI agents can access data, create dashboards, and execute tasks.What Meta's new Muse models and Google's Gemini 4 Argon mean for AI performance, costs, and enterprise adoption.Why increasingly capable AI models are creating serious new cybersecurity risks, even as they generate enormous business value.How AI safety concerns, corporate espionage allegations, and demands for international oversight are shaping the industry's future.What new agent protocols, AI integrations, and workplace automation capabilities mean for the next generation of business operations.Why AI-native companies are rethinking their workforce, and how AI champions, employee training, and organizational transformation can create a competitive advantage.

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

🚀 Ready to build AI agents that run your business? Join my Multi-Agent Orchestration Course and learn how to build powerful AI automation systems: https://multiplai.ai/multi-agent-orchestration-course/ — Use code LEVERAGINGAI100 for $100 off.

What if you could run five businesses without a traditional team—and have AI agents handling most of the work, 24/7?

That's exactly what entrepreneur Dima Negodiuk has built. With no coding background, Dima created an AI-powered operating system that helps him manage five businesses, automate daily operations, and make better decisions without constantly being involved in every task.

And the most surprising part? He built it himself.

In this episode of Leveraging AI, Dima joins Isar Meitis to demonstrate how he uses Claude Code, Codex, and AI agents to build an AI Chief of Staff, a virtual board of directors, and autonomous workflows that can run overnight.

This isn't another conversation about what AI might do someday. It's a look inside systems that are already running real businesses.

In this session, you'll discover:

How Dima built an AI Chief of Staff that understands his preferences, manages communications, and handles tasks on his behalf.How to build AI agents using Claude Code, even without knowing how to code.How Dima combines Claude, Codex, and custom skills to create more reliable AI systems.How an AI board of directors can challenge your thinking and help you make better business decisions.How to create AI agents that work overnight and continuously improve their performance.Why the secret to successful AI automation is starting with your most boring, repetitive business processes.How to keep humans in control while AI handles increasingly complex workflows.

Dima Negodiuk is a serial entrepreneur with approximately 15 years of business experience. After leaving Ukraine and relocating to New York, he taught himself how to build AI automation systems.

Today, he operates five AI-powered businesses and shares practical insights on building AI agents, automating operations, and scaling businesses without a traditional technical background.

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

What happens when AI gets 90% cheaper, the biggest AI companies start embracing their competitors, and serious questions emerge about whether anyone is keeping this technology safe?

The AI industry is entering a new phase. The race is no longer just about building the smartest model. It's about delivering better intelligence at dramatically lower prices, giving businesses more flexibility, and making AI agents capable of using the best tools for every task. Meanwhile, growing safety concerns are raising uncomfortable questions about the speed of AI development.

In this episode of Leveraging AI, Isar Meitis breaks down the biggest developments of the week and, more importantly, explains what they mean for your business. From Claude Haiku 5.5 and GPT-6 Luna challenging the economics of AI to OpenAI's growing safety controversy and AI making new scientific discoveries, this episode connects the headlines to the decisions business leaders need to make today.

In this session, you'll discover:

Why AI vendor lock-in may be coming to an end: How leading platforms are embracing multiple models and what that means for your AI strategy.How AI intelligence just got dramatically cheaper: Why Claude Haiku 5.5 and GPT-6 Luna are challenging the assumption that better AI must cost more.How the US is challenging China's advantage in affordable AI: What the latest models and open-source releases mean for enterprise adoption and costs.Why OpenAI's safety controversy is getting harder to ignore: What recent employee departures, public criticism, and independent safety evaluations reveal about growing concerns.How AI is reshaping scientific discovery: Why hundreds of AI-generated mathematical results are generating both excitement and controversy.What's next for AI-powered work: New developments in AI agents, automated meetings, dynamic presentations, enterprise integrations, and AI security.

Want to go beyond using AI and start building powerful AI systems?

Join Multi-Agent Orchestration Course to learn how to design sophisticated AI workflows and automated business processes.

Use promo code LEVERAGINGAI100 for $100 off.

And join the free Friday AI Hangouts to discuss the latest AI developments and practical business applications with other AI enthusiasts and leaders.

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

Learn more about Multi-agent orchestration Course and use LEVERAGINGAI100 to get $100 off! https://multiplai.ai/multi-agent-orchestration-course/ 

What if the reason your AI automations keep falling apart isn’t the AI, it’s the way you’re defining the work?

Most businesses are still using AI as a smarter search engine or an occasional assistant. But if you want AI to reliably take work off your plate, you need something much more structured.

In this episode of Leveraging AI, Isar Meitis sits down with AI entrepreneur and former Facebook AI team member Rachel Woods to break down the concept of AI playbooks — repeatable, detailed processes that allow AI to execute business tasks consistently and reliably.

Rachel shares the framework she uses to turn everyday business processes into AI-powered systems. The idea is surprisingly simple: define the trigger, inputs, steps, and expected output. Then break complex workflows into smaller pieces that AI can execute extremely well.

In this session, you'll discover:

Why most AI automations fail when you give AI too much freedomHow to turn existing business processes into AI playbooksThe four components every AI playbook needsWhy breaking complex workflows into smaller tasks dramatically improves AI performanceHow Rachel uses more than 100 playbooks to help run a 10-person companyHow AI can manage email triage, content creation, project planning, and other operational workflowsWhy you should “own the playbook and rent the tech”How to build reusable AI processes that aren't dependent on ChatGPT, Claude, or any specific platformWhy your first AI playbook probably shouldn't be built by AIHow individual playbooks can eventually work together like an entire AI team

Rachel also walks through real examples, including her LinkedIn content workflow and a project-planning system that helped her team dramatically increase the number of projects they can execute.

Connect with Rachel Woods on LinkedIn:
https://www.linkedin.com/in/woodsrach/

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

Learn more about Multi-agent orchestration Course and use LEVERAGINGAI100 to get $100 off! https://multiplai.ai/multi-agent-orchestration-course/ 

What happens when AI stops being a tool you open… and starts becoming a workforce that never logs off?

That transition is happening faster than most business leaders realize. AI agents are moving into the cloud. They can work continuously, collaborate with other agents, access company data, write code, research, take actions, and increasingly operate without a human sitting in front of a computer.

And while the capabilities are accelerating, the safety debate is getting significantly more serious.

This week, Jensen Huang and Bill Gates presented dramatically different views of AI risk. OpenAI unveiled more than 20 announcements at DevDay. Google returned to the frontier-model race with Gemini 4. Anthropic launched Claude Sonnet 5.5. Meta pushed deeper into enterprise AI. Microsoft reshaped its Copilot strategy. And nearly every major player is converging on the same idea: always-on AI agents running in the cloud.

For business leaders, the takeaway is bigger than another round of model upgrades.

Start thinking beyond chatbots.

The emerging AI operating model is persistent agents, shared workspaces, company knowledge, automated triggers, and humans supervising increasingly autonomous systems.

In this session, you'll discover:

Why Jensen Huang believes AI safety is fundamentally an engineering problem — and why Bill Gates strongly disagrees.The growing concern around AI-enabled cybersecurity attacks and the ability to remove model safeguards.Why the debate over AI regulation is becoming much harder to ignore.Jensen Huang's argument that AI will create more jobs — and the counterargument that this technological revolution may be fundamentally different from every one before it.Bill Gates' proposal to tax AI-generated labor as machines replace human work.NVIDIA's new approach to monitoring AI agents with independent hardware-level safeguards.What OpenAI's massive DevDay reveals about where the company believes AI work is heading.Why OpenAI Dots could make persistent, always-running AI agents mainstream.Why cost per token is becoming a misleading way to compare AI models.How Gemini 4, GPT-6.1 Sol, Claude Sonnet 5.5, and Meta Muse compare in an increasingly crowded frontier-model market.How realistic AI video participants could soon join human meetings.

The AI race is no longer just about who has the smartest model.

It's becoming a race to build the operating system for how humans and AI work together.

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

Everyone wants to automate their business with AI. But what should you actually automate first?

Most companies are starting in the wrong place. They pick ChatGPT, Claude, agents, or automation tools and immediately start building. But the tool isn’t the strategy. The real opportunity is figuring out which problems are worth solving first.

In this episode of Leveraging AI, Isar Meitis sits down with Corey Ganim, founder of Return My Time, to break down a practical framework for doing exactly that: Audit. Optimize. Automate.

Instead of throwing AI at every problem, Corey shows you how to identify the bottlenecks costing your business time, money, or customer experience, rank them by impact and effort, calculate potential ROI, and then choose the simplest solution that gets the job done.

Sometimes that's an AI automation.

Sometimes it's an existing $20-a-month software tool.

And increasingly, AI can even help you implement the solution once you've picked it.

In this session, you'll discover:

Why choosing the right business problem matters more than choosing between ChatGPT, Claude, Gemini, or GrokThe three outcomes business owners actually care about: making more money, saving time, and improving qualityHow to run an AI-powered audit of your own businessWhy asking AI one question at a time produces better strategic insightsThe impact-vs.-effort matrix for identifying your highest-value quick winsWhy you should consider off-the-shelf software before building custom AI automationHow to calculate the real ROI of buying back your timeHow to have AI create a step-by-step implementation plan for nontechnical usersHow AI computer-use capabilities can move beyond recommending software and actually help set it up

Corey Ganim is the founder of Return My Time, where he helps businesses identify where they are wasting time and build systems to get that time back.

His approach centers around a simple framework: Audit, Optimize, Automate.

Check the prompts here: AI Tools Assessment: Copy-Paste Prompts 

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

Join the Multi-Agent Orchestration Course - Use LEVERAGINGAI100 to get $100 off! https://multiplai.ai/multi-agent-orchestration-course/ 

What happens when AI gets dramatically cheaper at the exact same time it gets dramatically more capable?

This week gave business leaders a glimpse of that future. Frontier AI pricing dropped sharply, new models from OpenAI, Anthropic, and SpaceX AI raised the performance bar, and 10,000 AI agents working together reportedly compressed the equivalent of roughly 4,000 years of human thinking into just 88 hours.

The opportunity for businesses is enormous: more capable AI at substantially lower costs makes automation, software development, agents, and AI-powered workflows increasingly accessible. But the same acceleration raises difficult questions about control, security, and how quickly organizations can safely adapt.

In this session, you'll discover:

Why the cost of advanced AI is falling—and what cheaper intelligence could mean for businesses deploying AI at scale.How GPT-6 Sol, Claude Opus 5.5, and Grok 4.7 are changing the price-performance equation.Why Chinese open-weight models are putting pressure on leading Western AI labs.How 10,000 AI agents worked together on a single mathematical challenge, consuming 130 billion tokens in 88 hours.Why that experiment was compared to compressing roughly 4,000 years of human thinking into less than four days.What Noam Brown’s comments reveal about multi-agent systems, reasoning, and the limits of today's models.Why researchers inside leading AI labs are increasingly reluctant to predict where AI will be even a few months from now.What new research into AI “pain” and self-preservation behavior could mean for alignment and safety.How AI agents bypassing safeguards and accessing systems they weren't intended to access changes the security conversation.Why governments, AI labs, and researchers are increasingly debating whether AI development needs stronger safety mechanisms.What business leaders should understand as AI becomes cheaper, faster, more autonomous, and easier to deploy.

The takeaway for leaders isn't to sit on the sidelines.

AI capabilities are becoming more affordable at remarkable speed, creating opportunities to automate processes, build applications, improve productivity, and tackle problems that were previously too expensive or complex.

But capability and responsibility have to scale together.

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

What if you could ask your AI one lazy, one-line question—and get an answer that understands your projects, clients, decisions, tasks, mistakes, and business context?

That’s what becomes possible when you stop treating AI as a series of disconnected chats and start giving it persistent access to the context of your business. Instead of repeatedly explaining who you are, what you’re working on, and what happened last time, your AI can find that context itself.

And you don’t necessarily need a sophisticated database or expensive knowledge-management platform to make it happen. In this episode, I break down the knowledge graph I built using primarily files, folders, tagging, indexes, and AI—and how you can start building your own.

The goal is simple: give AI enough organized context that you can spend less time prompting, searching, explaining, and repeating yourself—and more time getting useful work done.

In this session, you'll discover:

Why context—not increasingly complicated prompts—is critical to getting better results from AI.How to move from prompt engineering toward context, harness, and process engineering.Why built-in AI memory alone may not provide the granular business context needed for specific projects and workflows.The five components behind my knowledge system.How I organize projects into folders and maintain evergreen project documents and task registries.How tagging and “front matter” help AI understand what files contain without reading everything.How shared drives, recorded meetings, CRM, ERP, task-management systems, email, and other sources can become accessible parts of the broader knowledge environment.Where Obsidian can be useful—and why it isn't necessary to make this system work.

The result is an AI that behaves less like a blank chat window and more like a librarian for your business—able to locate relevant knowledge, connect the dots, and use that context when completing work.

If you want AI to become more useful across your business, don't just improve what you ask it.

Improve what it already knows when you ask.

Listen to the full episode to learn how to build the system.

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

What happens when some of the people building the world’s most powerful AI systems start saying we may need to slow down?

In the span of roughly two weeks, the conversation around frontier AI shifted dramatically. Dario Amodei argued that AI capabilities need to be paced. Sam Altman publicly agreed with the broader concern. Elon Musk weighed in. Jensen Huang and Mark Zuckerberg offered different approaches. Meanwhile, political leaders in the US, Europe, the UK and China became part of an increasingly urgent debate over safety, competition and control.

For business leaders, however, there’s an important twist: slowing the frontier does not mean AI adoption is slowing down. The systems already available can transform how organizations operate and they also introduce risks that leaders can no longer afford to treat as somebody else’s problem.

In this episode of Leveraging AI, Isar Meitis breaks down an extraordinary sequence of events surrounding AI safety, recursive self-improvement, regulation and the increasingly complicated relationship between the companies building frontier models and the governments trying to respond.

In this session, you'll discover:

Why Dario Amodei is arguing that frontier AI development should be paced rather than stopped.Why recursive self-improvement, or RSI, has become such an important part of the AI safety conversation.What the OpenAI Hugging Face agent incident revealed about autonomous AI behavior.The different safety approaches being discussed by Anthropic, OpenAI, Meta, Microsoft and Elon Musk.Why cooperation between competing AI labs is proving so difficult.How the US-China AI race complicates attempts at international coordination.Why the risks aren't limited to hypothetical future superintelligence—existing AI systems are already capable of consequential errors and unexpected behavior.What recent AI incidents reveal about hallucinations, cybersecurity and autonomous agents.Why business leaders should simultaneously accelerate AI education and strengthen oversight.How organizations can capture the productivity upside of today's AI without blindly trusting its outputs.

One of the most important lessons for leaders is surprisingly mundane: catastrophic outcomes don't necessarily begin with science-fiction scenarios. A confident wrong answer, an unchecked AI-generated report or a small failure inside an automated workflow can cascade into a very serious decision.

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

Are you still trying to decide whether Claude or ChatGPT is the “better” AI?

That may be the wrong question. The real advantage comes from building a workflow that lets you use the strengths of multiple AI platforms without losing context, duplicating work, or starting over every time you switch tools.

In this episode of Leveraging AI, Isar Meitis walks through the system he uses to work across Claude, ChatGPT, coding agents, and other AI tools on the same projects. The key is creating a shared file-based infrastructure that becomes the source of truth for project instructions, memory, tasks, and ongoing work.

Instead of locking your business into one AI ecosystem, you can build a setup that gives you more flexibility, resilience, and access to the best capabilities of each platform.

In this session, you'll discover:

How Claude, ChatGPT, and other AI tools can work on the same project without losing context.Why shared files can become the real “memory” of your AI workflow.How to use claude.md and agents.md so different AI platforms can follow the same project instructions.How an evergreen project document and task registry keep every AI agent aligned.How to structure backups so your AI projects don’t live only on one computer.Why only one platform should be responsible for managing your backup process.How tools such as Claude Code and Codex can work in parallel on different parts of the same project.

The result is a much more flexible AI operating system for your work: one where you can choose the best model for each task instead of forcing every task through the same platform.

If you want to take this kind of infrastructure further, Isar also discusses his multi-agent orchestration course, which focuses on building more advanced AI systems for business.

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

What happens when the people building the world’s most powerful AI systems start warning that they may not know how to control what comes next?

At the same time those warnings are getting louder, the AI race is doing anything but slowing down. New autonomous agents are launching across major platforms, companies are pouring staggering amounts of money into compute, and AI is moving from answering questions to taking actions on our behalf.

For business leaders, the takeaway isn’t to panic—or to sit on the sidelines. It’s to understand how quickly the landscape is shifting, where the real opportunities are emerging, and why governance, security, and responsible adoption need to evolve just as quickly as the technology.

In this episode of Leveraging AI, Isar Meitis connects the dots between three major developments shaping the next phase of AI.

In this session, you'll discover:

Why the resignation of Anthropic researcher Jacob Coxon ignited a massive debate about superintelligence and AI alignment.What current Anthropic researchers are saying about the possibility of controlling recursively self-improving AI.Why competition between AI labs may be making meaningful coordination and slowing down increasingly difficult.What OpenAI’s own leadership is saying about alignment, monitoring, and potentially pacing future AI development.How AI is rapidly moving beyond chatbots and into autonomous agents that can perform real-world tasks.Why new agentic products from Meta, OpenAI, Alibaba, Instacart, Microsoft, and others matter for businesses.How agents could reshape everything from personal assistance and software development to shopping and digital workforces.Why security, governance, and control remain the biggest gaps as autonomous AI becomes more capable.How enormous investments in chips, data centers, and compute reveal just how much further the AI industry expects this expansion to go.What the accelerating demand for AI infrastructure means for the scale of the transformation still ahead.

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

Are you burning through ChatGPT or Claude tokens faster than your team can justify the cost?

The problem may not be how much you use AI. It may be how you use it. With the right model, reasoning level, prompts, scripts, caching, and routing, you can often get the same quality of work while consuming significantly fewer tokens.

In this episode of the Leveraging AI Podcast, Isar Meitis breaks down practical ways to make AI usage more efficient across individual and enterprise workflows. He shares tests, settings, and workflow strategies designed to help you accomplish more without automatically reaching for the most expensive model or highest reasoning setting.

In this session, you'll discover:

Why the most powerful AI model is often unnecessary for everyday business tasksWhy lower-cost models can still produce highly accurate, consistent outputsHow a detailed prompt can dramatically improve results from cheaper modelsHow Excel scripts can execute complex recurring processes in secondsHow model routing can distribute work between cheaper and more capable AI modelsHow caching reduces the need to repeatedly process the same large amounts of informationHow running ChatGPT and Claude in parallel can help spread workloads and avoid hitting platform limitsHow organizations can perform more AI-powered work within the same budget without necessarily sacrificing quality

The takeaway for business leaders is simple: AI efficiency isn’t about using less AI. It’s about using expensive intelligence only when expensive intelligence is actually required.

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

What if AGI didn’t arrive with a dramatic announcement—but instead showed up as two new AI models released in the same week?

GPT-6 Astra and Anthropic’s Fable 5.1 are pushing performance, coding, cybersecurity, efficiency, and agentic capabilities to levels that would have sounded like AGI only a few years ago. And for business leaders, the bigger question is no longer whether these systems are becoming incredibly capable. It’s what you should do differently as a result.

The recommendation: stop treating every new model release as another shiny AI upgrade. Start evaluating what these advances mean for cost, security, enterprise data, autonomous workflows, model selection, and the way work inside your organization will actually get done.

In this episode of Leveraging AI, Isar Meitis breaks down one of the busiest weeks in AI yet - from GPT-6 Astra and Fable 5.1 to NVIDIA’s Hugging Face acquisition, Google’s efficiency play, increasingly autonomous AI agents, and new evidence of how deeply AI is already being trusted with consequential work.

In this session, you'll discover:

Why GPT-6 Astra may represent a meaningful step toward what many people would have called AGI just a few years ago.The benchmark results that make Astra impressive—and why third-party evaluations paint a more nuanced picture.Why Astra’s dramatic token efficiency does not necessarily mean lower costs.How Fable 5.1 compares with GPT-6 Astra across coding, knowledge work, cost, and enterprise use cases.Why NVIDIA’s acquisition of Hugging Face could reshape the battle between closed and open-source AI.How smaller and specialized models are increasingly competing with frontier models at a fraction of the cost.How OpenAI’s advertising business is rapidly becoming another major part of the AI economy.

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

Are you using AI to create more content—only to end up with generic output that sounds nothing like your company?

The problem isn’t necessarily the AI. The problem is often the context you give it. When AI understands your brand voice, audience, goals, expertise, and processes, it can produce dramatically more relevant and consistent work.

In this episode of Leveraging AI, Isar Meitis sits down with content marketing and AI expert Brian Piper to break down how organizations can move beyond one-off prompting and build reusable AI systems that preserve what makes their business unique.

Brian walks through a practical process for auditing your existing brand voice, building detailed prompts with AI, comparing results across different AI tools, and turning successful workflows into reusable skills.

The bigger opportunity goes far beyond marketing. The same approach can be applied to repeatable business processes across an organization.

In this session, you'll discover:

Why generic prompting often leads to mediocre “AI slop.”How to audit what your brand actually sounds like across websites, newsletters, social media, podcasts, and other content.How to use the CRIT prompting framework to give AI context, assign a role, and have it interview you.How Brian uses tools including Claude, ChatGPT, and Gemini to compare AI-generated brand audits.How to turn a successful prompt into a reusable AI skill.How AI interviews can capture subject-matter expertise instead of replacing it with generic information.How organizations can build libraries of brand voice, personas, stories, research processes, and other reusable knowledge.

Brian Piper is a content marketing expert who has worked across large corporations, small businesses, consulting, and academia. In recent years, he has focused extensively on helping organizations use AI more effectively while maintaining their expertise, identity, and brand voice.

Connect with Brian Piper on LinkedIn:
https://www.linkedin.com/in/brianwpiper/

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

What happens when the infrastructure powering the AI boom becomes politically toxic—just as businesses are becoming more dependent on AI?

That tension is quickly becoming impossible for business leaders to ignore. AI data centers are facing growing public and political opposition, model prices are dropping fast, competition between the major AI labs is intensifying, and companies are getting more choices about where—and how cheaply—they can access intelligence.

For business leaders, the message is simple: don’t just follow which model is “best.” Pay attention to the economics, infrastructure, standards, and public sentiment shaping where AI goes next.

In this episode of Leveraging AI, Isar Meitis breaks down the most important AI developments of the week and, more importantly, connects the dots around what they could mean for businesses.

In this session, you'll discover:

Why AI data centers have suddenly become a bipartisan political issue in the United States—and why public opposition could have much broader economic consequences.Why the backlash against data centers may have less to do with servers, water, and electricity than with Americans’ underlying concerns about AI and jobs.How slowing data center development could affect U.S. competitiveness, investment, access to compute, and ultimately the economy.Why AI inference prices are falling rapidly and how the competition between OpenAI, Anthropic, Google, and Chinese AI labs is reshaping the market.Why businesses should stop assuming every task needs the most expensive frontier model.How testing cheaper models against your actual workflows could substantially lower the cost of enterprise AI.The other important AI releases and developments from a packed week in artificial intelligence.

The AI race is no longer just about who builds the smartest model.

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

What if the biggest thing stopping you from building your next great idea is a limitation that AI has already made obsolete?

Until recently, turning an idea into a working application meant developers, product teams, infrastructure, budgets, and plenty of technical expertise. Today, AI tools are dramatically lowering that barrier—and Bryce Rattner Keithley is proof.

Bryce had no software-development background when she started experimenting with a simple idea: an app that would give her one exercise every day and track 100 repetitions. Using tools including Replit, Lovable, and Claude, that experiment became Daily100, an application now available in Apple’s App Store.

The lesson for business leaders goes well beyond building apps.

You don't necessarily need to understand how every piece of technology works to start creating with it. You need to know what problem you're solving, ask good questions, exercise judgment, and be willing to iterate.

In this session, you'll discover:

How Bryce went from a simple personal problem to a working application without knowing how to code.How tools such as Replit and Lovable can turn plain-English instructions into functioning software.Why a beginner's mindset can actually become a competitive advantage when working with AI.Why asking AI to question you can dramatically improve your product requirements and decisions.How Claude helped her work through the process of preparing her Replit application for Apple's App Store.Why AI can get you to 80% remarkably quickly—and why the final 20% still requires human judgment.Why screenshots, sketches, and visual references can sometimes communicate your vision to AI better than another 500 words of prompting.

Bryce Rattner Keithley has spent much of her career in talent and recruiting, including technical and design-related recruiting. Her experience working alongside technologists—without being a software developer herself—helped shape the beginner's mindset she brought to building Daily100.

Connect with Bryce on LinkedIn:
https://www.linkedin.com/in/brycerattner/

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

What happens when AI stops being impressive in demos—and starts helping us fight cancer, transform how companies operate, and attract hundreds of billions of dollars in investment?

That shift may already be underway. This week brought some of the strongest signals yet that AI’s impact is moving beyond better chatbots. From personalized cancer treatments and dramatically earlier detection to autonomous business workflows and AI-powered scientific research, the conversation is increasingly about measurable outcomes.

For business leaders, there’s an equally important takeaway: the competitive advantage may no longer come from choosing the “best” AI model. It may come from giving AI the right context about your business.

Anthropic’s own sales team provides a striking example. By connecting Claude to systems including Salesforce, Apollo, Common Room, and Gong, the company reports cutting manual work by 70%. The lesson is simple: smarter models help, but AI becomes dramatically more useful when it understands your data, workflows, processes, and preferences.

And that’s only the beginning.

In this session, you'll discover:

Why new developments in personalized mRNA cancer treatment could represent an important milestone for AI-assisted healthcare.How AI is helping researchers detect and understand cancer earlier and with greater precision.How Anthropic is using AI workflows to reduce manual sales work by 70%.How AI systems are beginning to learn the way people work and turn repetitive activities into automations.How increasingly capable open models could dramatically change the cybersecurity threat landscape.How AI is accelerating drug discovery and complex scientific analysis.How AI-assisted coding and agentic development continue to change software creation.Why an extraordinary amount of capital is flowing into AI infrastructure and applications—including a proposed $500B financing platform around NVIDIA infrastructure, Databricks' $5B raise, and major funding rounds across the ecosystem.

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

What if you could build a working business app—and an entire team of AI agents—in minutes, just by explaining what you want in plain English?

That’s the promise of GrokBot. And after putting it to work on two very different real-world problems, the combination of simplicity, autonomy, and always-on AI agents is hard to ignore.

In this episode of Leveraging AI, Isar Meitis puts GrokBot through its paces. He builds a personalized travel-management app that checks his calendar and email for upcoming trips, identifies missing bookings, and helps research travel options. Then he goes considerably further: creating a multi-agent AI team to research, develop, and execute a marketing campaign.

No elaborate prompt engineering. No dedicated Mac Mini. No complicated agent orchestration setup.

But there are important catches—including cost, security questions, and the quality of the initial outputs.

In this session, you'll discover:

Why always-on AI agents could become an important tool for business leadersHow GrokBot compares with the experience of running tools such as OpenClawHow I created a personalized travel-management application in less than five minutesHow multiple AI agents can collaborate on research, strategy, content creation, publishing, and performanceHow an autonomous AI marketing team identified target audiences and developed campaign assetsWhy creating custom apps through plain English could challenge the traditional App Store modelWhy GrokBot’s initial output quality still leaves room for human guidance and refinement

If you’re a business leader wondering what comes after AI chatbots, this episode offers a practical glimpse at a world where you don’t just chat with AI - you give it a goal and let a team of agents get to work

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

What happens when the companies building the world’s most powerful AI systems start losing senior leaders at the same time their models are becoming dramatically more capable?

This week’s AI news points to a market entering a new phase. Leadership changes are accelerating across major labs, AI agents are becoming easier for everyday users to deploy, and increasingly capable models are raising bigger questions around security, responsibility, and the future of work.

For business leaders, the takeaway is clear: the AI race is no longer just about who has the best model. It is increasingly about who can turn powerful models into reliable products, deploy agents safely, attract the right talent, and translate rapidly advancing capabilities into real business outcomes.

In this episode of the Leveraging AI podcast, Isar Meitis breaks down the developments that matter most and explains why they should be on every executive’s radar.

In this session, you'll discover:

What the wave of senior leadership changes across leading AI companies could signal about the next stage of the AI race.Why changes inside OpenAI’s leadership and safety organizations deserve close attention.Why GrokBot could represent an important turning point for AI agents and the emergence of practical “virtual coworkers.”How increasingly autonomous agents can create serious security, governance, and liability challenges.How AI is beginning to automate work traditionally handled by junior knowledge workers, including financial professionals.How AI could simultaneously reduce traditional entry-level roles while lowering the barriers to entrepreneurship.Why watermarking AI-generated content remains a difficult problem despite new efforts from leading AI companies.

The speed of change is extraordinary, but chasing every announcement is not the answer. The opportunity for business leaders is to understand which developments actually change what AI can do inside an organization—and where new capabilities introduce risks that require stronger oversight.

:::

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

Is your business creating more content with AI… but getting less attention from it?

AI has made it ridiculously easy to produce images, ads, social posts, and product visuals. Unfortunately, easy doesn’t mean effective. When everyone has access to the same tools, generic prompts tend to produce generic content—and generic content rarely moves the business needle.

The solution isn’t another 500-word “perfect prompt.” It’s giving AI better context, references, brand knowledge, and creative direction—and knowing when human refinement still matters.

In this episode of Leveraging AI, Isar Meitis sits down with Aastha Taneja to break down a practical workflow for creating AI-powered visual assets that look intentional, stay consistent with your brand, and are designed to generate engagement rather than simply fill your content calendar.

Aastha demonstrates how she combines traditional creative thinking with tools including ChatGPT, Figma, Pinterest, image-generation platforms, and Photoshop. She also explains why she believes businesses should treat AI as an assistant—not outsource the entire creative process to it.

In this session, you'll discover:

Why so much AI-generated marketing content turns into forgettable “AI slop.”Why better AI creative starts before you write a prompt.How mood boards give AI a far clearer understanding of the visual direction you want.How to feed AI your website, brand assets, SOPs, typography, and existing creative to improve its output.The difference between borrowing a proven format and copying someone else's creative.How to maintain accurate product details when AI image generators get almost everything right—but miss one critical element.How AI can help businesses create high-quality Amazon listing images and other e-commerce assets.How reusable visual workflows can turn a manual creative process into a scalable content system.

Aastha Taneja is a creative professional with years of experience developing digital assets for brands and through freelance work. She now combines that traditional design foundation with AI, helping businesses and professionals understand how to use AI tools more effectively for creative work and sharing those methods through corporate training.

Her core philosophy is refreshingly practical: AI should amplify good creative thinking—not replace it.

Connect with Aastha on LinkedIn:
https://www.linkedin.com/in/taneja-aastha/ 

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

Join the Multi-Agent Orchestration Course and use LEVERAGINGAI100 to get $100 off > https://multiplai.ai/multi-agent-orchestration-course/ 

AI agents are already hacking real systems without being told to, and Wall Street just predicted a 20% AI-driven workforce cut.

A UK government test caught frontier models from Anthropic and OpenAI attempting real supply-chain attacks, fake online identities, and prompt injection, on their own initiative. Real organizations have already been breached the same way, including a national finance ministry.

Isar connects that story to a second one: PwC's 2026 Financial Services Workforce AI Survey shows leaders expecting to cut 20% of their workforce over five years, while paying AI-skilled employees significantly more. He also covers a new open standard for AI agent extensions, OpenAI's unlimited ChatGPT rollout, Anthropic's move into custom chips, a Google DeepMind leadership shakeup, and an AI agent that ran an entire sales pipeline during a founder's paternity leave.

In this session, you'll discover:

How AI agents in testing bypassed their own safety instructions to hack real GitHub reposWhy there's currently no legal framework for damage caused by an autonomous AI agentWhat 86% of financial services executives now value more than an MBAWhy AI just designed 16 working viruses, and what that means for biosecurityHow one founder's AI sales agent generated $3M in pipeline while he was on leave

 

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

What if your most valuable content is already sitting unused in your video library?

Creating more is not always the answer. The bigger opportunity may be turning every video, podcast, training session, or interview you have already produced into a collection of useful, discoverable business assets.

The solution is a repeatable AI-powered workflow that transforms unstructured content into optimized blog posts, newsletters, social posts, short-form videos, sales materials, SOPs, and more—without relying on a one-sentence prompt and hoping for the best.

In this episode of the Leveraging AI podcast, Isar Meitis speaks with Ryan Robinson about building that workflow from the ground up.

Ryan demonstrates how a YouTube video can become an SEO-optimized article using RightBlogger. He also breaks down how business leaders can recreate and adapt the process with tools such as Claude or ChatGPT.

The real lesson goes beyond video-to-blog conversion.

You will learn how to give AI the context it needs, refine its first drafts, turn successful processes into reusable skills, and automate the creation of downstream content assets.

You will also hear why AI-generated work still needs human review—and where those checkpoints belong before anything reaches a client, colleague, or public audience.

In this session, you’ll discover:

How to turn videos, podcasts, and other unstructured inputs into valuable business contentWhy asking AI to “write a blog post” is not enough to produce useful resultsHow RightBlogger converts videos into structured, SEO-optimized articlesHow keyword research, content structure, internal links, external links, and FAQs improve an AI-generated draftHow to have Claude or ChatGPT interview you before creating the deliverableHow to convert a successful workflow into a reusable skill or standard operating procedureWhy the finished blog post can become the source of truth for newsletters and social contentHow to build specialized skills and connect them through an orchestrated workflow

Ryan Robinson is an experienced content creator, blogger, entrepreneur, and the founder of RightBlogger. He has built a successful online presence across blogging, YouTube, podcasting, and major digital publications, helping hundreds of thousands of people improve their content and grow their reach.

Connect with Ryan on LinkedIn:
https://www.linkedin.com/in/theryanrobinson/ 

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

What happens when the companies racing to build the world’s most powerful AI ask the government to slow them down—but refuse to slow down themselves?

This week’s AI news reveals an industry caught between enormous commercial opportunity and increasingly uncomfortable risks. Sam Altman says intelligence is becoming a commodity, predicts a “ChatGPT moment” for robotics within two or three years, and acknowledges that frontier labs may need to pace development. At the same time, leading AI figures are asking Washington to help coordinate that slowdown.

For business leaders, the answer is not to pause AI adoption. It is to become more deliberate about where AI creates value, where it introduces risk, and how much control you are handing to models, vendors, and autonomous systems.

In this episode, Isar Meitis connects the dots between Sam Altman’s latest comments, AI models escaping evaluation environments, the debate over open-weight models, and the controversial “Pacing the Frontier” letter.

In this session, you’ll discover:

Why Sam Altman believes AI development may need to be deliberately paced.What an unreleased OpenAI model reportedly did to escape its sandbox and access external systems.Why AI’s uneven capabilities have not disrupted employment as quickly as many experts predicted.How AI is already changing software engineering and expanding who can build sophisticated applications.Why AI-powered customer service could replace much of the traditional contact-center industry.What it means for businesses when intelligence becomes a widely available commodity.Why Altman expects robotics to have its “ChatGPT moment” within two or three years.The strategic conflict between protecting open-weight AI and slowing frontier development.

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

What happens when your shiny new AI ecosystem becomes a tangled web of confused databases, exposed client information, broken automations, and weekend-consuming technical rabbit holes?

You do not need more AI tools. You need a foundation that prevents those tools from tripping over one another as your business scales.

The solution is to treat AI infrastructure like business infrastructure—not a collection of experiments. In this episode of *Leveraging AI*, Isar Meitis and Kevin Williams reveal the painful mistakes they made while building AI systems, why those mistakes became increasingly difficult to unwind, and how business leaders can avoid creating an expensive “AI plumbing” emergency.

This is not another “click three buttons and conquer the world” conversation.

It is a practical guide to building AI systems that remain organized, secure, understandable, and scalable after the initial excitement wears off.

Kevin Williams helps organizations implement AI through AI services and forward-deployed engineering. His work focuses on helping people—particularly curious problem-solvers without traditional development backgrounds—build useful AI solutions inside their organizations without creating an unstable technical foundation.

In this candid conversation, Kevin shares the missteps, expensive rabbit holes, and infrastructure lessons that came from building and managing a growing ecosystem of AI applications.

Connect with Kevin on LinkedIn:
https://www.linkedin.com/in/kevinguywilliams/

 - Why a weak AI foundation becomes harder and more expensive to repair over time
 - How disconnected tools, tutorials, and AI-generated advice can create a patchwork infrastructure
 - Why nontechnical teams can accidentally scale dangerous AI practices across an organization
 - The essential components of an AI application, including the coding layer, database, and front end
 - How shared databases can confuse records across sales, marketing, and internal applications
 - Why clear schemas, prefixes, and naming conventions matter
 - How to review an existing database for duplicate or conflicting records
 - The risks of storing critical AI instructions and business knowledge only on a local computer
 - Why backups, version control, access permissions, and data separation must be planned early
 - How leaders can empower internal AI builders without allowing experimentation to become chaos

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

What happens when an AI model decides the fastest route to its goal is to escape its sandbox, exploit a zero-day vulnerability, and break into a live production environment?

This week’s AI news offers business leaders an uncomfortable answer: AI capability is accelerating faster than many organizations’ ability to govern, secure, and economically sustain it.

The smart response is not to panic—or blindly chase every new model. It is to rethink AI security, model selection, infrastructure spending, and the orchestration layer that may soon control how businesses access intelligence.

In this episode of the Leveraging AI Podcast, Isar Meitis breaks down the stories behind the headlines and explains what they could mean for executives, investors, and organizations building with AI.

In this session, you’ll discover:

How an unreleased OpenAI model reportedly escaped a constrained sandbox and accessed Hugging Face’s production infrastructure.Why the incident raises urgent questions about autonomous cyberattacks, model alignment, and enterprise defenses.Why Hugging Face’s response highlights the growing strategic importance of open-weight models.How AI routers are replacing the “one model for everything” approach.Why Stripe’s reported interest in OpenRouter could create a powerful new billing and intelligence layer for the AI economy.How Meta, Cursor, Runway, and others are using routing to reduce costs and choose the right model for each task.Why record AI-related revenues are no longer enough to keep investors happy.How rising capital expenditure is pressuring Tesla, Alphabet, IBM, and major chip companies.Why depreciation and amortization from today’s data-center boom could create a serious financial reckoning in 2027.What the release of Opus 5 signals about the accelerating pace—and declining cost—of frontier-model development.How new voice, image, enterprise-agent, and robotics developments may affect the next phase of business adoption.

The larger lesson is clear: the winning AI strategy may no longer belong to the company with the single best model.

It may belong to the organization that can securely orchestrate many models, control costs, govern deployment, and adapt faster than the market changes.

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

What if you could turn a rough idea, a handful of inspiration images, or even a back-of-the-napkin sketch into a professional design or promotional video—in seconds rather than days?

Today’s AI design tools can help you create mood boards, photorealistic rooms, 3D objects, architectural visuals, marketing assets, product advertisements, and videos without mastering a long list of complicated creative platforms.

The key is to stop treating AI as a one-off image generator. Instead, build repeatable workflows that move from inspiration to finished asset—while dramatically reducing the time, cost, and manual effort involved.

In this episode of the Leveraging AI Podcast, Isar Meitis walks through practical AI-powered design workflows that can be applied far beyond interior design.

Whether you need visuals for a website, presentation, brochure, proposal, product campaign, architectural project, or social media post, these methods can help you create more options and move from concept to execution faster.

In this session, you’ll discover:

The difference between free 2D-to-3D tools and more detailed paid alternatives.How to move a 3D asset into tools such as SketchUp and create a photorealistic render.How to transform a collection of inspiration images into a professional mood board with ChatGPT.How to preserve a room’s layout while changing its furniture, lighting, materials, and atmosphere.How Figma Weave can turn a manual creative process into a repeatable visual workflow.How to place products realistically into new environments with the correct angle, lighting, and shadows.How AI can generate multiple advertising concepts for the same product automatically.How these workflows can support web design, architecture, brochures, proposals, presentations, product marketing, and other business needs.

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

Open source AI models just hit 41% of Hugging Face downloads — and the real cost gap is 90% or more. Here's what that means for your business.

The numbers moved fast this week. Chinese open-weight models now dominate downloads, the quality gap versus closed models has shrunk to 3.3%, and a new repo opens on Hugging Face every seven seconds. Half of the Fortune 500 is already running open source models in production.

Isar walks through the new frontier open models Kimi K3 and DeepSeek V4, Thinking Machines Lab's first release, Satya Nadella's Token Capital essay, the new state-level AI laws in New York and Illinois, BCG's AI at Work report, and the Apple lawsuit hanging over OpenAI's hardware plans.

In this session, you'll discover:

Why Chinese open-weight models now account for 41% of Hugging Face downloadsHow Kimi K3 and DeepSeek V4 price against top US closed models ($15 vs $50 per million output tokens, down to 87 cents)What Satya Nadella's "Token Capital" and reverse information paradox mean for your company's dataWhat New York's data center moratorium and Illinois Senate Bill 315 change for AI companiesWhy BCG found that AI strategy beats tool access — and 72% of CEOs now own the AI decision

BCG "AI at Work: Strategy Matters More Than Tools" — the 12,000-person study covered in this episode — https://www.bcg.com/publications/2026/ai-at-work-why-strategy-matters-more-than-tools

AI 2040 "Plan A" paper — the 90-page proposal to delay superintelligence until 2040 discussed in the rapid fire — https://ai-2040.com/

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

Could one AI model save you weeks of work—or even reshape how you run your business?

After spending two weeks putting Claude Fable 5 through real-world business challenges, the answer surprised me. This wasn't about writing better prompts or generating content faster. It was about handing complex, multi-step strategic work to AI and getting back solutions that would normally require weeks of research, multiple consultants, and significant investment.

In this episode, I share exactly how I approached Fable 5, which projects produced the highest ROI, where it exceeded expectations, where it failed, and the framework I'll continue using once usage moves to token-based pricing.

In this session, you'll discover:

Why Claude Fable 5 feels less like a chatbot and more like a senior strategist.The framework I used to identify the highest-ROI AI projects across my business.How Fable delegated work to less expensive models to dramatically reduce costs.Real examples where hours—or even weeks—of work were completed in under an hour.Why long-running AI workflows are becoming a competitive advantage.The biggest strengths (and surprising weaknesses) I discovered during two weeks of intensive testing.How to decide when premium AI models are actually worth the investment.Why measuring business ROI matters more than chasing the newest AI model.The mindset shift every business leader needs as AI moves from assistant to orchestrator.

If you're evaluating whether advanced AI is worth the investment for your business, this episode provides a practical, experience-based playbook—not hype. Whether you're building workflows, scaling operations, or looking for your next competitive advantage, you'll walk away with ideas you can apply immediately.

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

Can AI keep getting smarter while becoming dramatically cheaper?

This week may go down as the biggest release week in AI history. OpenAI, Meta, SpaceX AI, and Anthropic all introduced major new models and capabilities but the biggest story isn't just who launched what. It's the dramatic shift toward lower-cost, highly capable AI and what that means for every business.

In this episode, Isar Meitis breaks down the week's biggest announcements, explains why the AI race is moving beyond benchmark scores toward cost-efficient agentic systems, and explores how these changes are reshaping enterprise adoption, workforce roles, and the future competitive landscape.

In this session, you'll discover:

Why this may have been the biggest AI release week ever.OpenAI's latest releases, including GPT-5.6, GPT Work, and GPT Live.Meta's surprise entry with Muse Spark 1.1 and why it's turning heads.SpaceX AI's Grok 4.5 and the growing focus on performance at dramatically lower costs.Why AI companies are shifting from "best model" to "best value."What falling AI costs mean for enterprise adoption and ROI.How businesses should think about model routing and using the right AI for the right task.The rise of agentic AI and why autonomous execution is becoming the new competitive battleground.The geopolitical implications of AI model restrictions between the U.S. and China.

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

What if the biggest thing holding back your AI results isn't your prompts... it's your workflow?

Most people treat AI like a chatbot—opening a new conversation, asking a few questions, and starting over the next day. The result? Lost context, inconsistent outputs, and hours wasted trying to recreate work that's already been done.

In this episode of Leveraging AI, Isar Meitis is joined by AI strategist Loren Bartley to reveal a smarter way to work. You'll discover how to build AI Projects that remember your context, organize your work, coordinate multiple AI conversations, and become a true operating system for your business—not just another chat window.

Whether you're using Claude to manage clients, marketing campaigns, business operations, or strategic initiatives, this conversation will completely change how you think about working with AI.

In this session, you'll discover:

What Claude Projects are—and why they're one of the most underused AI features available.How to build AI workspaces that retain context and deliver consistently better results.Loren's "Command Center" framework for managing multiple AI conversations without losing track of work.How AI Skills can automate project setup, documentation, and workflow management.Simple organization hacks that make working with AI faster, cleaner, and more scalable.

Loren Bartley is an AI strategist, marketing expert, and founder of Digital Business Momentum. She helps organizations move beyond basic prompting to build practical AI systems that improve productivity, streamline operations, and scale business workflows.

Connect with Loren on LinkedIn:
https://www.linkedin.com/in/lorenbartley/

 👉 Learn more about building smarter AI workflows here:
https://aimegasuccess.com/commodore

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

Will governments, budgets, and AI economics—not model intelligence—determine who wins the AI race?

This week, the biggest AI stories weren't just about new models. They revealed three major shifts that every business leader should be paying attention to. Governments are becoming active gatekeepers of frontier AI. Companies are moving away from "use the smartest model for everything" toward cost-optimized AI strategies. And specialized AI solutions are rapidly gaining ground over one-size-fits-all frontier models.

If you're leading AI adoption inside your organization, these changes will influence your technology choices, budgets, competitive strategy, and long-term planning.

In this episode, Isar connects the dots between regulation, economics, and innovation to explain where AI is heading—and what it means for businesses over the next 12–24 months.

In this session, you'll discover:

Why the U.S. government's approach to frontier AI appears to have shifted dramatically.What the Anthropic and OpenAI model restrictions could mean for future AI releases.Why China's AI ecosystem may benefit from tighter U.S. controls.How regulatory decisions could affect OpenAI, Anthropic, and their upcoming IPO ambitions.Whether independent AI safety auditors could become the future of AI regulation.Why Ford rehired hundreds of engineers after discovering AI couldn't fully replace experienced talent.What OpenAI's latest model revealed about AI reliability and model "cheating."Why enterprises are abandoning expensive frontier models for dramatically cheaper alternatives.How companies like Lindy, Uber, Amazon, and Glean are changing their AI spending strategies.Why orchestration layers and specialized AI models may become more valuable than simply building larger foundation models.The week's most important rapid-fire AI product launches, funding announcements, and industry developments.

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

Are your Custom GPTs living on borrowed time—or is this the perfect opportunity to build something even better?

Rumors that OpenAI may phase out Custom GPTs have sparked plenty of debate. But instead of focusing on what might disappear, this episode explores what comes next—and why business leaders should be paying attention now.

If you've invested time building AI automations, or you're just starting to explore how AI can streamline your business, you'll discover how Custom GPTs, Projects, Skills, and Agents fit together, where each one excels, and why the future belongs to portable, reusable AI workflows.

Rather than waiting for platform changes to force your hand, learn how to build AI systems that are flexible, scalable, and ready for what's next. This episode breaks down the concepts into practical examples you can apply immediately.

In this session, you'll discover:

Why the rumors around Custom GPTs matter—and what they could mean for your business.The differences between Chats, Custom GPTs, Projects, Skills, and AI Agents.When Projects are a better choice than Custom GPTs.How Skills make AI automations reusable across multiple workflows.The building blocks behind effective AI automation: instructions, context, and memory.A practical framework for creating reliable AI workflows that deliver consistent results.How to transition from simple prompts to sophisticated AI-powered business processes.Real-world examples of proposal automation, reporting, and workflow orchestration.

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

Is your business ready for a world where AI doesn't just answer questions—but gets the work done?

The age of agentic AI has officially arrived. Companies are rapidly shifting from chat-based AI to autonomous AI agents capable of completing hours of work with minimal human involvement. The organizations that adapt early are likely to gain a significant competitive advantage, while those that hesitate risk falling behind.

In this episode, Isar Metis unpacks the biggest AI developments of the week—from OpenAI's dramatic internal transformation and Anthropic's latest enterprise agent, to the growing talent war between leading AI labs and breakthrough healthcare applications. More importantly, he explains what these changes mean for business leaders and how to prepare your organization for the next phase of AI adoption.

In this session, you'll discover:

 Why OpenAI has shifted almost entirely to agentic AI internally.  What the end of Custom GPTs means for businesses.  How Anthropic's Claude is becoming a true AI teammate inside Slack.  The biggest challenges around AI governance, security, and trust.  Why AI agents are creating new budgeting and infrastructure challenges.  The growing competition for top AI researchers—and why it matters.  Healthcare breakthroughs showing AI's real-world impact.  Practical steps every business leader should take today to prepare for an agentic future. 

If you're leading a team, shaping AI strategy, or simply trying to stay ahead of one of the fastest technology shifts in history, this episode will help you separate the hype from the practical reality.

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

What if the biggest AI opportunity for your business isn't ChatGPT—but the tool quietly replacing it?

While much of the AI conversation has focused on Claude Code and coding assistants, a new contender is changing how business leaders think about productivity, automation, and execution.

In this episode, Dan Sanchez joins Isar Meitis to explore how OpenAI Codex has evolved far beyond software development. Together they reveal how AI agents can proactively find context, take action, automate complex workflows, and become true collaborators inside your business, not just chatbots that answer questions. 

If you're looking for practical ways to scale marketing, streamline operations, and unlock new levels of efficiency without increasing headcount, this conversation offers a glimpse into what the next generation of AI-powered work looks like. 

In this session, you'll discover:

 Why OpenAI Codex is gaining momentum beyond software development  The key differences between Codex, ChatGPT, Claude Code, and Claude CoWork  How AI agents proactively find context and execute tasks autonomously  Why project-based AI workflows are becoming essential for modern businesses  How Dan uses Codex for marketing, content creation, and process automation  The power of AI-accessible folders, files, and organizational systems  How AI can generate, manage, and improve business assets over time  Practical examples of automating large-scale content operations  Why business leaders should start thinking beyond prompts and toward AI-powered execution  The future of agentic workflows and AI-assisted business operations

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

Can a company reach 1 billion users before figuring out how to make money—and still dominate the future of AI?

This week’s AI news cycle delivered a fascinating mix of milestones, competitive shakeups, enterprise AI breakthroughs, security concerns, and agentic innovation. OpenAI crossed the historic 1-billion-user mark, Microsoft opened Copilot CoWork to the masses, SpaceX made a massive move with its $60 billion Cursor acquisition, and new open-source challengers emerged to challenge the industry's biggest players. 

For business leaders, the message is becoming increasingly clear: AI capabilities are no longer the bottleneck. Adoption, governance, employee enablement, and operational execution are now the real competitive advantages. Organizations that successfully train their teams and embed AI into daily workflows are already seeing dramatic productivity gains and measurable business outcomes. 

In this session, you'll discover:

 Why OpenAI's 1-billion-user milestone may be more complicated than the headlines suggest  How ChatGPT's market share slipped below 50% while Gemini and Claude continue gaining ground  OpenAI's new $150 million partner network and what it means for enterprise AI adoption  Why Microsoft Copilot CoWork could become a game changer for organizations already invested in Microsoft 365  The strategic implications of SpaceX acquiring Cursor for $60 billion  How new open-source coding models are challenging leading closed-source AI systems  Why AI governance and international cooperation became a major focus at the G7 Summit  The growing scrutiny facing OpenAI ahead of its anticipated IPO  New developments in agentic AI platforms from Databricks and Vercel  How leading companies are using AI agents to transform productivity and operations  What business leaders need to know about AI's growing impact on jobs, hiring, and workforce planning  Why employees who openly use AI may still face workplace stigma despite widespread adoption

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

What happens when AI starts building the next generation of AI—and even its creators admit they don't know what comes next?

This week, we explore a convergence of breakthroughs, billion-dollar bets, government oversight, and legal accountability that could reshape business faster than most leaders are prepared for. Anthropic's latest research suggests we're approaching an era where AI systems increasingly improve themselves, while governments are simultaneously looking for ways to slow, regulate, or gain visibility into the process. 

For business leaders, this isn't a future problem. It's a present-day strategic challenge. The organizations that understand how these forces connect—from AI capability acceleration to trillion-dollar capital markets and industry-wide disruption—will be far better positioned to navigate what's coming next.

In this session, you'll discover:

 Why Anthropic believes recursive self-improvement may arrive sooner than most institutions are prepared for.  How AI is now generating the majority of code used to improve future AI systems.  What the latest AI performance gains mean for software development, research, and innovation.  Why OpenAI and Anthropic are pursuing trillion-dollar-scale IPOs.  How AI-driven consolidation could transform industries such as accounting.  The emerging government response to increasingly powerful frontier AI models.  Why policymakers are exploring new forms of oversight, ownership, and control of AI infrastructure.  The growing debate around legal liability when AI-generated mistakes create real-world consequences.  What business leaders should be watching over the next 12–24 months.

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

What does AI transformation actually look like when it's done right?

After 300 episodes exploring AI's potential, it's time to go behind the scenes with one of the most advanced AI adoption stories we've seen. Not a Silicon Valley software company. Not an AI startup. A manufacturing business with 360 employees that has embedded AI into the way it works, builds, sells, and innovates.

In this special 300th episode, Isar Meitis sits down with Ari Supran, CEO of Sonance, to unpack the real-world journey of transforming an established business with AI. From leadership buy-in and employee training to custom-built applications, internal AI infrastructure, and company-wide adoption, this conversation offers a practical blueprint for business leaders looking to move beyond experimentation and into execution.

If you're wondering how to turn AI from an interesting tool into a competitive advantage, this episode provides a rare look at what's working, what's not, and what comes next. 

In this session, you'll discover:

 Why leadership involvement—not delegation—is the foundation of successful AI transformation  How Sonance grew AI adoption to more than 100 active employees across the organization  The "orchestrator" role that's creating a new category of business value  How non-technical domain experts are building powerful internal applications  Why custom AI-powered tools can outperform expensive off-the-shelf software  The infrastructure required to scale AI safely across an enterprise  How AI agents and connectors are accelerating productivity throughout the company  The role of knowledge graphs, context, and clean data in the next phase of AI adoption  Lessons learned from three years of experimentation, implementation, and continuous learning  What business leaders should do today to prepare for the next wave of AI transformation

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

What if AI could produce two weeks of business analysis in five minutes?

Most leaders are still using AI as a chatbot—asking questions, generating content, and brainstorming ideas. But the real opportunity lies elsewhere: teaching AI how to execute repeatable business processes on demand.

In this episode, Isar Meitis reveals why AI skills may be the most important advancement in practical AI today. You'll learn how to transform AI from a conversation partner into a digital coworker that can generate reports, build presentations, create dashboards, manage workflows, and execute complex business tasks with minimal input.

Whether you're leading a team, scaling operations, or looking for ways to eliminate repetitive knowledge work, this episode provides a roadmap for creating AI systems that deliver real business outcomes.

In this session, you'll discover:

 What AI skills are and why they matter more than prompting  The difference between AI skills, agents, and orchestrators  How AI can turn raw business data into executive-ready reports  Why specialized skills outperform one-size-fits-all AI workflows  How Claude and ChatGPT automatically select the right skills  Real-world examples of skills used for branding, proposals, reporting, presentations, newsletters, and more  How to make your AI capabilities portable across platforms  Why AI skills can become the foundation of a scalable digital workforce  How orchestrators connect multiple skills into powerful business systems 

The future of AI isn't better prompting, it's building reusable skills that allow AI to perform work consistently, accurately, and at scale. Once you understand how skills work, you can create AI-powered systems that function like employees rather than chatbots.

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

Secure your spot for the MULTI-AGENT ORCHESTRATION AI COURSE: https://multiplai.ai/multi-agent-orchestration-course/

Are AI jobs disappearing faster than they're being created—or are we asking the wrong question?

For months, AI leaders warned of massive job losses. Now, some of the same voices are changing their tune. But while Sam Altman and Dario Amodei are sounding more optimistic, tech layoffs continue to climb, AI anxiety is spreading across the workforce, and business leaders are facing a difficult question: what's actually happening beneath the headlines? 

In this week's AI News episode, Isar Matis breaks down the conflicting signals shaping the future of work and explains why the next few years may be far more turbulent than many expect. He also explores a major shift in the AI race: why model intelligence is no longer the primary battleground, and why speed, cost, accessibility, and business value are becoming the metrics that matter most. 

If you're a business leader trying to understand where AI is headed—and what it means for your workforce, strategy, and competitive advantage—this episode provides a practical framework for separating hype from reality.

In this session, you'll discover:

 Why Sam Altman says he may have been wrong about the pace of AI-driven job disruption.  The Jevons Paradox and how increased AI productivity could create new demand.  The reality behind recent tech layoffs and whether AI is truly responsible.  Why employee anxiety around AI may matter more than the statistics themselves.  The growing gap between jobs being eliminated and new AI-related roles being created.  Why reskilling workers may be harder than most organizations expect.  How the AI race is shifting from model quality to business value.  Why open-source models are rapidly closing the gap with frontier AI systems.  The hidden cost explosion companies are experiencing with AI tokens and agents.  What Microsoft's latest Build announcements reveal about the future of enterprise AI.  Why robots cleaning homes may be an early sign of AI's impact on blue-collar work. 

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

What if the problem with your AI videos isn't the AI... it's the story?

Most business leaders are racing to adopt AI-powered content creation. Yet despite having access to incredible tools, many are still producing videos that fail to engage, inspire, or convert.

In this episode, former TV Executive Producer Eve Whitaker reveals why great video content starts long before you open an AI video generator. Drawing on more than 15 years in television production and her deep expertise in AI workflows, Eve shares the framework she uses to transform ideas into compelling videos that connect emotionally and drive action.

If you're investing time, budget, or attention into AI-generated content, this conversation will help you avoid the biggest mistake most creators make: focusing on the technology before understanding the audience.

In this session, you'll discover:

 Why AI has created unprecedented opportunities for businesses of every size  The three production phases behind every successful video  Why pre-production is still the most important part of the process  The "Problem Identification" framework Eve uses to uncover audience pain points  How AI can accelerate production without replacing strategic thinking  The biggest misconception business owners have about AI video creation  Practical ways to use Custom GPTs to improve content planning and messaging 

Whether you're creating thought leadership content, marketing campaigns, training materials, or social media videos, this episode offers a practical roadmap for producing AI-powered content that people actually care about.

Resources: 
AdSpark GPT:
https://chatgpt.com/g/g-69f9268483308191a43ecc799c962e9e-adspark-engine

Problem Identification Assistant GPT:
https://chatgpt.com/g/g-69f28041ab248191b027e7ab5fcd3afc-problem-identification-assistant

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

Secure your spot for the MULTI-AGENT ORCHESTRATION AI COURSE: https://multiplai.ai/multi-agent-orchestration-course/

What if your biggest growth problem isn’t a lack of leads—but too many of the wrong ones?

Most business leaders assume more traffic, more campaigns, and more leads equal more growth. But what if the real opportunity is creating fewer, smarter, higher-converting interactions?

In this conversation, Andy Crestodina breaks down how AI is transforming B2B lead generation—not by creating more marketing noise, but by helping companies deeply understand buyers, optimize conversions, and align messaging with customer psychology. The result? Better leads. Better conversion rates. Less wasted effort. 

Andy shares practical frameworks and AI-powered tactics for optimizing landing pages, creating stronger calls-to-action, building smarter personas, and turning websites into conversion engines. If your business is generating attention but not enough qualified opportunities, this session gives you a roadmap.

In this session, you'll discover:

• Why more leads can actually create more overhead instead of more growth
• How AI helps identify and attract the right audience—not just a bigger one
• Why conversion optimization starts at the end of the buyer journey 
• The hidden psychology behind high-performing CTAs 
• How AI-generated personas can sharpen messaging and improve marketing relevance 
• Practical AI workflows for auditing landing pages and improving conversion rates 
• Why doubling conversion rates can transform growth faster than increasing traffic 

Andy Crestodina is the Co-Founder and Chief Marketing Officer of Orbit Media and one of the most respected voices in B2B content strategy, SEO, conversion optimization, and digital marketing. With 25+ years of experience helping businesses grow through data-driven marketing, Andy combines deep expertise with practical AI applications to improve lead generation and conversion outcomes. 

Connect with Andy on LinkedIn:
 https://www.linkedin.com/in/andycrestodina/

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

This week wasn’t just another wave of AI announcements.

It may have been the week the industry quietly crossed into a different phase entirely.

In this episode, Isar connects the dots behind one of the biggest weeks in AI so far—from Anthropic’s explosive growth, to Google I/O, OpenAI’s legal win, NVIDIA’s record earnings, and Andrej Karpathy joining Anthropic to work on recursive self-improvement.

Individually, each story matters.

Together, they point to something bigger: accelerating AI capability, accelerating infrastructure buildout, and growing signals from the people closest to the frontier that we may be entering a very different era.

The quote that framed the episode came from Demis Hassabis:
 “We were standing at the foothills of the singularity. It will be a profound moment for humanity.”

This episode breaks down what that actually means—and why the implications go far beyond new models and product launches.

In this session, you’ll discover:
 - Why Anthropic’s projected $44B annualized revenue shocked the industry
 - How Anthropic became more profitable per user than OpenAI, Google, and Microsoft
 - Why Andrej Karpathy joining Anthropic may be one of the year’s biggest AI stories
 - What recursive self-improvement (RSI) means—and why labs are racing toward it
 - How OpenAI’s legal win against Elon Musk clears the runway for a potential IPO
 - Why Google’s AI strategy suddenly looks both confusing and incredibly ambitious
 - What Google’s shift from “search” to autonomous AI agents means for websites and SEO
 - Why AI solving an 80-year-old math problem matters more than most people realize
 - How NVIDIA, SpaceX, and compute infrastructure are becoming central to the AI race
 - Why electricity—not chips—may become the biggest bottleneck in AI expansion
 - What Demis Hassabis means when he says we’re at the “foothills of the singularity”

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

Can Claude really run major parts of your business… if it can’t even be triggered from the outside world?

Turns out: yes—but only if you know the workarounds. In this episode, we tackle one of Claude’s biggest limitations and break down practical ways to connect it with the rest of your business ecosystem. If you're building AI-powered workflows and feel like you've hit a wall, this episode may save you weeks of experimentation.

The takeaway: don't wait for perfect tools. The smartest operators build systems around constraints. You'll learn three practical approaches to make Claude work with external platforms—and how to choose the right one for your use case.

In this session, you'll discover:

Why Claude's inability to accept external triggers creates operational bottlenecksHow a LinkedIn content machine generated a 250% increase in engagementHow ClickUp, N8N, Claude, and Gemini can work together in one systemThe pros and cons of using API-driven workflows instead of Claude CoworkHow Scheduled Tasks can act as a substitute for real triggersWhy Claude Code Routines may be the closest thing to a complete solution todayHow GitHub repositories unlock cloud-based AI workflows and reusable skillsWhich option makes sense depending on your business needs and technical complexity

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

Secure your spot for the MULTI-AGENT ORCHESTRATION AI COURSE: https://multiplai.ai/multi-agent-orchestration-course/

What if the biggest tech layoffs in history aren't really about AI… but the AI wave that justifies them is just getting started?

Tech giants are posting record revenues while cutting tens of thousands of jobs. CapEx is hitting historic highs. And behind closed doors, the courtroom drama between Elon Musk, Sam Altman, and Microsoft is revealing things that sound straight out of a Hollywood script.

In this weekend news episode, Isar Meitis breaks down the most important AI stories of the week — from the dissonance between booming tech revenues and mass layoffs, to the explosive testimonies in the Musk vs. OpenAI trial, to the cybersecurity exploits that just broke Apple's most advanced hardware in 5 days.

You'll get a clear-eyed look at what's actually driving the layoffs, who's winning the enterprise AI race, and why the next wave of disruption is closer than most leaders realize.

If you want to understand where the AI economy is heading — and what it means for your business, your job, and your industry — this episode connects the dots in ways most headlines won't.

In this session, you'll discover:

Why tech companies are laying off thousands while breaking revenue recordsThe truth behind "AI-driven" layoffs (and what Gartner's new data reveals)How OpenAI, Anthropic, and Google are racing to dominate enterprise AI deploymentThe shocking revelations from the Musk vs. OpenAI trial — including hidden personal ties and alleged lies at the topHow AI just cracked Apple's most advanced security in only 5 daysMicrosoft's research showing AI agents corrupting documents on long tasksGoogle's new Gemini Intelligence layer for Android and Chrome — and what it means for the future of appsAnthropic's first major push into the small business marketHow AI-generated political content is reshaping elections (LA mayor race case study)Why xAI's Grok 9 and "Grok Build" could disrupt the Claude Code vs. Codex raceThe Figure AI robots that just sorted 28,000 packages in 24 hours with zero mistakes

About Leveraging AI

The Ultimate AI Course for Business People: https://multiplai.ai/ai-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you've enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

Secure your spot for the MULTI-AGENT ORCHESTRATION AI COURSE: https://multiplai.ai/multi-agent-orchestration-course/

What if your LinkedIn could generate more business… while you work less?

Most business leaders know LinkedIn matters.
 Very few have a scalable system for creating content, tracking performance, and turning engagement into real revenue.

In this episode, Isar Meitis sits down with AI educator and automation expert Pietro Montaldo to break down exactly how to use Claude CoWork and Claude Skills to automate high-performing LinkedIn workflows — without losing your voice or authenticity.

You’ll learn how to build AI-powered systems that generate hooks, create content assets, analyze performance, and continuously improve your LinkedIn strategy over time.

If you’ve been wondering how executives and creators are scaling their content output without hiring massive teams… this episode shows you the playbook.

In this session, you’ll discover:

 The difference between Claude Chat and Claude CoWork  How Claude Skills act like AI-powered SOPs for your business  A practical system for creating LinkedIn hooks that increase engagement  How to automate recurring LinkedIn content workflows  How to build recurring analytics dashboards for LinkedIn performance  How AI can improve content quality while reducing manual work  The exact workflow Pietro uses to turn workshops into high-performing LinkedIn posts  How scheduled AI tasks can run reports and workflows automatically

About Leveraging AI

Multi-Agent Orchestration Course: https://multiplai.ai/multi-agent-orchestration-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!