Leveraging AI

By Isar MeitisTechnology

Leveraging AI episodes

September 15327 | Claude vs. ChatGPT Is the Wrong Question - learn how you can use them together with Isar Meitis
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!
21 min
September 12326 | 10% chance AI will destroy humanity, Agentic solutions everywhere, 32% GDP growth with over 10% unemployment in 2030, and more important AI news in the week of September 11, 2026
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!
56 min
September 08325 | Maximize your AI ROI (ROAI 🤔) great output for less money with Isar Meitis
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 tasks
Why lower-cost models can still produce highly accurate, consistent outputs
How a detailed prompt can dramatically improve results from cheaper models
How Excel scripts can execute complex recurring processes in seconds
How model routing can distribute work between cheaper and more capable AI models
How caching reduces the need to repeatedly process the same large amounts of information
How running ChatGPT and Claude in parallel can help spread workloads and avoid hitting platform limits
How 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!
22 min
September 05324 | GPT 6 Astra, and Fable 5.1 - two new models that feel like AGI, in one week, and more AI news for the week ending on September 4, 2026
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!
38 min
September 01323 | Stop Creating AI Slop: Build an AI Content Engine That Sounds Like Your Brand with Brian Piper
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!
33 min
August 29322 | AI Data Centers Are Now a Bipartisan Punching Bag, Claude Tops User Satisfaction, MHS is the New MCP for Hardware, and More Important AI News for the Week Ending August 28, 2026
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!
1 hr 3 min
August 25321 | How to Build an AI App Without Coding: From Idea to App Store with Replit & Claude by Bryce Rattner Keithley
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!
38 min
August 22320 | AI cancer curing breakthrough, context is taking main stage, huge funding rounds, and more important AI news ending week of August 21, 2026
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!
56 min
August 18319 | Grok Bot is the most effective out-of-the-box tool ever with Isar Meitis
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 leaders
How GrokBot compares with the experience of running tools such as OpenClaw
How I created a personalized travel-management application in less than five minutes
How multiple AI agents can collaborate on research, strategy, content creation, publishing, and performance
How an autonomous AI marketing team identified target audiences and developed campaign assets
Why creating custom apps through plain English could challenge the traditional App Store model
Why 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!
23 min
August 15318 | Grok Hits the Frontier, the Leadership Exodus Strengthens, Endless new model releases, and more important AI news for the weekend ending on August 14, 2026
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.
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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!
52 min

About Leveraging AI

From the publisher's feed

Dive into the world of artificial intelligence with 'Leveraging AI,' a podcast tailored for forward-thinking business professionals. Each episode brings insightful discussions on how AI can…