The AI Cookbook: AI Tools | Enterprise AI | Leadership

Malcolm Werchota
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Malcolm Werchota's AI Cookbook is where artificial intelligence meets authentic business transformation. Known for his direct style and willingness to show AI in action—even during live presentations—Malcolm helps organizations understand that AI isn't about replacing humans but amplifying their capabilities. From voice-note productivity hacks to real-time meeting intelligence, this podcast delivers actionable insights for immediate implementation.

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    E82: Dubai's $1.4T AI Push: Strategic Expansion Insights from GITEX

    Just back from GITEX Global 2025 in Dubai, our Managing Partner Sumeyra Yildirim noticed something fundamental: the conversation has shifted from “what can AI do?” to “how do we scale it?”—and the UAE ecosystem is deliberately optimized for speed. In this episode, Malcolm Werchota breaks down why werchota.ai is seriously exploring expansion to the UAE, sharing insights from Dubai’s largest tech conference and the strategic logic behind this decision. What you’ll discover: The infrastructure reality: $1.4 trillion US investment framework, 500,000 Nvidia chips annually, and the 5-gigawatt Stargate UAE AI campus—50× larger than typical data centers.Why the UAE government is racing toward becoming the world’s first AI-native government by 2027, with AI CEOs in every ministry since 2017.How werchota.ai’s proven DACH market model could accelerate in an ecosystem where regulatory frameworks enable rather than slow deployment.The competitive advantage of dual-market operations: learn fast in one market, apply lessons with proper governance in another.Real examples of deployment timeline differences—three months in Dubai versus eighteen months in Germany for identical AI solutions. Episode Summary: Malcolm Werchota explores werchota.ai’s strategic consideration of UAE expansion, sharing data-driven insights from GITEX Global 2025. The episode examines how the UAE’s AI-optimized ecosystem—backed by $1.4 trillion in infrastructure investment, deliberate government policy, and rapid deployment frameworks—creates a unique environment for AI transformation at scale. Key Topics Covered Market shift: from “what can AI do?” to “how do we scale it?”$1.4T UAE investment framework and US partnerships500,000 Nvidia AI chips annuallyStargate UAE: 5GW AI campus (50× typical data center)Abu Dhabi’s $3.5B AI-native government strategy (by 2027)Mohamed bin Zayed University of AI & K–12 mandatory AI educationGITEX 2025 highlights: autonomous governance, quantum AI, digital twinsDeployment timeline: 3 months (Dubai) vs 18 months (Germany)Dual-market acceleration modelMGX sovereign wealth fund ($100B+ AI investments)G42, Technology Innovation Institute, and UAE global AI partnershipsNotable Statistics MetricFigureUAE–US Investment Framework$1.4T (10 years)ADNOC AI Expansion$440BNvidia Chips Imported500,000/yearStargate AI Campus5GW (50× average DC)MGX Fund Target$100B+MGX Data Center Acquisition$40BUAE Tech Funding (H1 2025)$1BAbu Dhabi Gov’t Digital Strategy$3.5B (2025–2027)Global AI Startup Funding Share53%New Jobs from Copilot UAE152,000AI GDP Target13.6% by 2031Fully AI-native Government Target2027Resources & ReferencesUAE AI Initiatives: GITEX Global 2025UAE National AI Strategy 2031Abu Dhabi Digital Strategy 2025–2027Stargate UAE AI Campus Organizations Mentioned: G42, MGX, Mohamed bin Zayed University of AI, Technology Innovation Institute, ADNOC, Du Global Partners: OpenAI, Microsoft, Nvidia, Oracle, Cisco, SoftBank, BlackRock, Cerebras Systems Contact & LinksMalcolm Werchota 🔗 LinkedIn 🌐 Website 🎥 YouTube 🐦 X (Twitter) 📘 Facebook 📸 Instagram 🎵 TikTok Email Contacts: General: malcolm@werchota.aiGCC Inquiries: Sumeyra Yildirim (Managing Partner, GCC)Show Feedback: social@werchota.ai AI Fit Academy: Learn AI tools hands-on. Ship First, Study Later — working workflows by Week 2 or 100% refund. 👉 Learn more

    23min

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    E81: Build Better AI Agents (Part 2): The Five Building Blocks of Context Engineering

    After learning why AI agents fail in Part 1 (attention budget, context rot, orchestration limits), Malcolm Werchota now reveals how to build scalable, long-running AI systems using Anthropic’s framework for Context Engineering. This episode goes beyond prompts — it’s about architecture. Malcolm introduces the five building blocks of Context Engineering: 1️⃣ System Prompts – Define your agent’s identity, purpose, core capabilities, and quality standards. 2️⃣ Minimal Tool Sets – Stop giving 20 tools; focus on what’s essential. 3️⃣ Just-in-Time Retrieval – Only load information when it’s needed, not everything at once. 4️⃣ Long-Horizon Strategies – Extend runtime with compaction, note-taking, and delegation. 5️⃣ Examples & Patterns – Train with diverse examples, anti-patterns, and confidence scoring. Using practical cases from Werchota.ai — like invoice automation and large-scale feedback analysis — Malcolm demonstrates how these techniques turn fragile “demo agents” into reliable production-grade systems. Key topics: agent architecture, context optimization, compaction, token management, orchestration patterns, Anthropic Claude Code implementation, and how to scale AI workflows in production environments. Perfect for professionals working with Claude, GPT-5, or Gemini — and anyone ready to move from prompt engineering to system thinking. 🗒️ SHOW NOTES Episode 81, Part 2: Build Better AI Agents Through Context Engineering Malcolm Werchota breaks down the five practical building blocks of Context Engineering, showing how to design scalable AI systems that actually think ahead — not just follow commands. WHAT YOU’LL LEARNThe five key building blocks of Context EngineeringHow to write effective system prompts that guide decision-makingWhy fewer tools = better agentsHow to implement Just-in-Time data retrievalExtending AI lifespan through compaction and delegationUsing examples and anti-patterns to improve agent reasoningConfidence scoring and note-taking for long-running tasks KEY TAKEAWAYSSystem Prompts: Define identity, purpose, and quality — short and structured (600–800 tokens).Minimal Tool Sets: Reduce decision complexity; fewer, focused tools improve speed and reliability.Just-in-Time Retrieval: Load only what’s needed in context; one file or task at a time.Long-Horizon Strategies: Use compaction, external note-taking, and delegation to prevent context overload.Examples & Patterns: Teach your agents from both successes and failures — diversity beats volume.REAL-WORLD USE CASESInvoice automation using Claude Code orchestrationCustomer feedback summarization (10,000 → 5,000 words)Parallel sub-agent processing (reading 10 invoices simultaneously)Long-running report generation using compaction & note-taking TOOLS & PLATFORMSClaude Code (Anthropic)Claude Sonnet 4.5 (1M-token context window)Gemini 2.5 (1M-token context window)ChatGPT-5 (200k-token context window)Werchota.ai Cloud Dashboard (Episode Notes) RESOURCESAnthropic Research: Effective Context Engineering for AI AgentsPrevious Episode: Build Better AI Agents – Part 1 (Context Engineering Basics)Claude Code DocumentationWerchota.ai Blog: “Context Engineering in Real Workflows” MALCOLM’S KEY INSIGHTS“Don’t give your agent 20 tools — it will spend half its energy deciding which one to use.”“The future of AI isn’t about bigger models. It’s about better architecture and context engineering.”“System prompts are not messages — they’re thinking frameworks.”“Context engineering turns fragile demos into production systems.” 🔗 WHERE TO FIND MALCOLM WERCHOTA LinkedIn → linkedin.com/in/malcolmwerchota Website → werchota.ai YouTube → youtube.com/@werchota X → x.com/malcolmwerchota Facebook → AI Cookbook by Malcolm Werchota Instagram → @malcolmwerchotaai TikTok → @malcolmwerchota 📧 Get in touch: Questions, feedback, or transformation stories → malcolm@werchota.ai Episode ideas → social@werchota.ai 🎓 Upgrade your AI skills: Join the AI Fit Academy — Malcolm’s hands-on program that helps professionals and teams ship real AI workflows by Week 2 — or your money back. Learn more → werchota.ai/ai-fit-academy

    32min

  3. HÁ 2 DIAS

    E80: Build Better AI Agents: Context Engineering Over Prompts (Pt. 1)

    Your AI agents work—but they’re not smart. They follow instructions, yet fail on edge cases, forget context mid-task, and need constant supervision. Malcolm Werchota reveals why your invoice automation, podcast metadata generation, and business workflows keep breaking down—and why it’s not the AI’s fault. The missing piece is context engineering, a concept most people have never heard of. In this two-part series, Malcolm breaks down Anthropic’s groundbreaking research on how to build AI agents that actually think ahead. Learn why prompt engineering is no longer enough, how attention budget silently kills your automations, what context rot does to long-running tasks, and how the orchestrator pattern allows AI agents to spawn helper agents on demand. You’ll hear how Malcolm’s team cut invoice processing time from 45 minutes to zero human intervention—and why feeding your AI more data can actually make it dumber. This episode isn’t about magic prompts. It’s about designing the entire environment your AI operates in. Key topics: AI agent automation challenges, context window vs. attention budget, why mega-prompts fail, orchestrator pattern design, system prompt architecture, tool-calling strategies, and scalable AI workflows. Perfect for professionals implementing Claude AI, automating business processes, or frustrated with unreliable AI agents. Malcolm’s “Ship First, Study Later” approach means real implementation—not theory. Part 2 dives into advanced system prompts, minimal tool sets, and managing long-running tasks without context explosion. WHAT YOU’LL LEARNWhy functional AI agents still fail at business automationThe difference between prompt vs. context engineeringHow attention budget and context rot sabotage your workflowsThe orchestrator pattern: when agents build their own helpersReal-world cases: invoices, podcasts, and process automationWhy mega-prompts make AI dumber—and what to do insteadAnthropic’s context engineering frameworkHow to design information architecture for Claude and other LLMs TOOLS & PLATFORMSClaude Code (Anthropic)Claude Sonnet 4.5 (1M token window)Gemini 2.5 (1M token window)ChatGPT (100–200k token window)10 Valley OS (TenVOS) – context engineering case studyRESOURCESAnthropic Research: Effective Context Engineering for AI AgentsPrevious Episode: Building Claude Code AgentsPrevious Episode: 10 Valley OS – Context Engineering in ActionMALCOLM’S KEY INSIGHTS“It’s like having an employee who follows orders perfectly—but never takes initiative or thinks ahead.”“Context engineering manages everything the model uses: system instructions, tools, message history—not just the prompt.”“The challenge now isn’t crafting perfect prompts. It’s curating the information within the model’s limited attention budget.”“Don’t feed it a billion files. Use the smallest, clearest, highest-signal inputs possible.” COMING IN PART 2 Advanced system prompt structureMinimal tool sets for reliabilityHandling long-running tasks without context explosionPractical implementation blueprints 🔗 WHERE TO FIND MALCOLM WERCHOTA LinkedIn → linkedin.com/in/malcolmwerchota Website → werchota.ai YouTube → youtube.com/@werchota X → x.com/malcolmwerchota Facebook → AI Cookbook by Malcolm Werchota Instagram → @malcolmwerchotaai TikTok → @malcolmwerchota 📧 Get in touch: Questions, feedback, or transformation stories → malcolm@werchota.ai Episode ideas → social@werchota.ai 🎓 Upgrade your AI skills: Check out the AI Fit Academy, Malcolm’s hands-on program that gets professionals shipping working AI workflows by Week 2—or your money back. Learn more → werchota.ai/ai-fit-academy

    27min

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    E79: AI Cybersecurity: How Hackers Use ChatGPT & Claude for Ransomware

    80% of ransomware attacks now use artificial intelligence. In this episode, Malcolm Werchota exposes how criminals with zero programming experience are using ChatGPT and Claude to build sophisticated cyberattacks—and why your business might already be compromised. Discover the real case of "Mr. X," who used AI to infiltrate 17 organizations, steal financial data, and craft psychologically-targeted ransom demands worth up to $500,000—all without understanding basic code. Learn how North Korean operatives used AI to pass technical interviews at Fortune 500 companies, get hired by HR, and maintain false identities for years while extracting intellectual property. This isn't theoretical. The Anthropic August 2025 Threat Intelligence Report reveals actual chat logs showing criminals asking AI: "How much ransom can this victim afford?" and "Can you write me a customer support bot for my ransomware buyers?" Malcolm breaks down the democratization of cybercrime through "vibe hacking"—where AI eliminates every barrier to sophisticated attacks. From healthcare systems to religious institutions, from emergency services to small businesses, no organization is safe when a 10-year-old in Iceland or a 90-year-old in Kenya can launch enterprise-grade attacks using conversational AI. Key Insights & Quotes "This isn't just cybercrime. This is AI-powered psychological manipulation conducted by people like you and I, who are basically not cyber criminals." "You don't need a cybercrime MBA. Just ask Claude." "AI-powered operatives don't just blend in. They do a very, very good job. They might be the best performers on your team, and you don't really know it." "We're witnessing the complete democratization of sophisticated cybercrime capabilities. Everybody listening to this podcast can become a sophisticated cybercriminal." "Would you rather be attacked by a human cybercriminal? Or would you rather be attacked by an AI agent? Experts say 100%—they would prefer a human attacker. Why? Because humans need sleep, they make mistakes, and they can be profiled and predicted." "In an AI-powered world, your security is only as strong as your willingness to really embrace AI in your company." Resources & References Mentioned Anthropic August 2025 Threat Intelligence Report: Official documentation of AI misuse casesIBM Security Intelligence Podcast: Analysis of AI vs. AI in cybersecurityDepartment of Justice: Documentation of 300+ US companies hiring North Korean operativesMIT Sloan Research: 80% of ransomware attacks now use AITenValley OS Episode: Referenced for AI agent orchestration capabilities About This Episode This episode is part of Malcolm Werchota's AI Cookbook Show, recorded live from Bregenz. Malcolm brings his signature "Ship First, Study Later" philosophy to cybersecurity, delivering actionable intelligence without academic jargon. Perfect for business owners, IT professionals, security teams, and anyone navigating the intersection of AI and organizational security. Episode Type: Educational / Investigative Difficulty Level: Intermediate (accessible to non-technical audiences) Best For: Business owners, IT departments, security professionals, tech enthusiasts Related Topics: AI security, ransomware protection, threat intelligence, workplace security Where to find Malcolm Werchota: LinkedIn: https://www.linkedin.com/in/malcolmwerchota/ Website: https://www.werchota.ai/ YouTube: https://www.youtube.com/@werchota X: https://x.com/malcolmwerchota Facebook: https://www.facebook.com/people/AI-Cookbook-by-Malcolm-Werchota/61580362300250/?sk=reels_tab Instagram: https://www.instagram.com/malcolmwerchotaai/ TikTok: https://www.tiktok.com/malcolmwerchota Get in touch: Have questions about AI implementation or want to share your transformation story? Reach Malcolm at malcolm@werchota.ai Email the Show: Write to us with episode requests, feedback, or ideas at social@werchota.ai Ready to level up your AI skills? Explore AI Fit Academy – Malcolm's program helping professionals and teams apply AI tools effectively in work and business. Ship First, Study Later – working workflows by Week 2 or 100% refund. Learn more at https://www.werchota.ai/ai-fit-academy Tags: #AICybersecurity #RansomwareAttacks #ChatGPTHacking #BusinessSecurity #AIThreats #CybercrimeAI #NorthKoreaHackers #PhishingAttacks #AIDefense #CybersecurityThreats #MalcolmWerchota #AIWorkflows #EnterpriseSecurity #ThreatIntelligence #AIRisks

    30min

  5. HÁ 4 DIAS

    E78: Chip Wars 2.0: US-China AI Supply Chain Crisis, Gemini & Microsoft Talent | Weekly AI

    The US–China chip wars just entered a dangerous new phase. China announced rare earth export controls on materials critical for AI chip manufacturing the same week Trump imposed 100% tariffs on Chinese imports. This isn’t just geopolitical theater—your AI infrastructure costs and availability are about to change dramatically. In this week’s AI roundup, Malcolm Werchota breaks down what’s actually happening in the global AI supply chain and why European businesses can’t afford to sit on the sidelines. We’re covering OpenAI’s DevDay announcements (App SDK, Agent Kit, Chat Kit), Google’s Gemini Enterprise launch as a Copilot alternative, and Europe’s €1.1 billion AI sovereignty plan. But the headline story is geopolitical: rare earth materials, chip manufacturing bottlenecks, and the real possibility of supply chain disruptions that could impact your AI deployment plans. When 90% of rare earth processing happens in China and they just put export controls in place, every business using AI infrastructure needs to pay attention. We also explore a troubling trend of fake AI experts appearing in major media outlets like the BBC and Guardian, Microsoft’s strategic talent acquisitions (including Kubernetes creator Brendan Burns and Python inventor Guido van Rossum), and why the future of AI competition isn’t about model quality anymore—it’s about trust, governance, and human amplification. Who Should Listen:Business leaders, technology professionals, and anyone making decisions about AI infrastructure investments who needs to understand how geopolitical tensions affect AI deployment costs, availability, and strategic planning. Malcolm’s Take: “We’re shifting from a world where AI competition was about model quality to one where it’s about trust, governance, and supply chain resilience.”“When 90% of rare earth processing happens in China and they just put export controls in place, every business using AI infrastructure needs to pay attention.”“Europe’s €1.1 billion AI sovereignty plan isn’t just about independence—it’s about recognizing that relying on US and Chinese infrastructure carries real geopolitical risk.”“The fake AI experts in mainstream media aren’t just a credibility problem—they’re actively misleading businesses about what’s actually possible with AI.” Resources MentionedOpenAI DevDay 2025 announcementsGoogle Gemini Enterprise launch detailsEuropean Commission AI sovereignty planAnalysis of China’s rare earth export controlsMicrosoft Copilot vs. Google Gemini comparisonsAI chip shortage forecasts from Bain & Company Where to find Malcolm WerchotaLinkedIn: linkedin.com/in/malcolmwerchota Website: werchota.ai YouTube: youtube.com/@werchota X: x.com/malcolmwerchota Facebook: AI Cookbook by Malcolm Werchota Instagram: @malcolmwerchotaai TikTok: tiktok.com/malcolmwerchota Get in touchHave questions about AI implementation or want to share your transformation story? Reach Malcolm at malcolm@werchota.ai Email the ShowSend feedback, episode requests, or story ideas to social@werchota.ai AI Fit AcademyLevel up your AI skills with AI Fit Academy – Malcolm’s program helping professionals and teams apply AI tools effectively in work and business. Ship First, Study Later – working workflows by Week 2 or 100% refund. Learn more: werchota.ai/ai-fit-academy

    37min

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    E77: The LocalMind.ai Security Breach – Austrian AI Startup Catastrophe

    In this investigative episode, Malcolm Werchota dissects the LocalMind disaster and exposes the myth that geography equals security. Learn why Microsoft’s cloud is safer than local startups, how to run proper AI vendor security audits, and the five technical questions every organization must ask before adopting AI tools. Key takeaways: • “Local and secure” is marketing, not magic • The 77% AI startup breach rate nobody talks about • Third-party audit obligations under GDPR • Spotting AI-generated code vulnerabilities • The five security questions that save careers If you’re evaluating AI vendors or already using AI tools with sensitive data, this episode might just save your organization from becoming the next LocalMind. 🔍 Episode Summary The LocalMind catastrophe is a wake-up call for any organization trusting AI vendors with confidential data. Marketed as the GDPR-compliant alternative to Microsoft Copilot, the startup’s “local and secure” slogan masked catastrophic vulnerabilities — from unencrypted passwords to exposed network access. The breach went undetected for seven months, cost €47,000 in direct response, and left hundreds of clients unnotified when the company abruptly vanished. Malcolm breaks down what went wrong, explains why cloud giants actually offer stronger security, and shares a practical due-diligence checklist to evaluate AI vendors safely. 🧩 Key Topics Covered LocalMind Breach Timeline: From Marcus’s GDPR-driven decision to Thomas’s discovery of unrestricted access“Vibe Coding” Vulnerabilities: How AI-generated code creates systematic riskThe Data Sovereignty Myth: Why Austrian servers ≠ securityVendor Security Audit Framework: The five critical questions to vet AI suppliersGDPR Compliance Reality Check: Incident obligations, costs, and fine exposurePractical Risk Assessment: Red flags and documentation SMEs can request immediately 💬 Notable Quotes“Geography is not a security control. LocalMind being in Austria made it less secure than Microsoft’s cloud infrastructure.”“If a vendor can’t explain how they store credentials or handle incidents — walk away.”“Seventy-seven percent of AI startups reported breaches. The question isn’t if — it’s how prepared they are.”“‘Local and secure’ was never a security guarantee. It was just good marketing.” 🛠️ Actionable Takeaways Demand Third-Party Security Audits Require proof of SOC2/ISO 27001 audits — no audit, no deal.Ask These 5 Questions:How are credentials stored?What’s your incident response plan?When was your last independent security audit?How do you segment customer networks?Who has admin access, and how is it monitored?Challenge “Local = Safe.” Major cloud providers spend billions on security infrastructure.Check AI Code Review Practices. 68% of vendors use AI-generated code; insist on manual review evidence.Verify Incident Transparency. Ask vendors how they handled their most recent security issue.Understand GDPR Liability. Your AI vendor = your data processor. Their failure = your responsibility.MALCOLM’S CONTACTSLinkedIn: linkedin.com/in/malcolmwerchota Website: werchota.ai YouTube: youtube.com/@werchota X (Twitter): x.com/malcolmwerchota Facebook: facebook.com/AI-Cookbook-by-Malcolm-Werchota Instagram: @malcolmwerchotaai TikTok: tiktok.com/malcolmwerchota 📧 Email: malcolm@werchota.ai 📮 Feedback: social@werchota.ai 🎓 AI Fit Academy: werchota.ai/ai-fit-academy

    29min

  7. 8 DE OUT.

    E76: ChatGPT Apps Explained: OpenAI Dev Day 2025 Breakdown

    OpenAI’s Dev Day 2025 introduced ChatGPT apps — a new ecosystem that lets users book travel, create content, and manage tasks directly inside ChatGPT. Malcolm analyzes whether this platform play will succeed, why developers are wary, and what it means for businesses considering ChatGPT automation. Key Topics Covered 1. The ChatGPT Apps Announcement How the new ecosystem works (Booking.com, Expedia, Spotify, Canva, Figma, Coursera, Zillow)800 M weekly active users (up from 700 M)8 billion tokens/minute processed via APIComparison to failed 2023 plugins 2. OpenAI’s Platform Strategy Aiming to be your “digital life orchestration layer”Learning from Meta’s ecosystem model30 % cut → “Apple Store of AI” playMCP protocol adoption from Anthropic 3. AgentKit — Workflow Automation Platform Visual drag-and-drop agent builder (demo in 7 minutes)Guardrails for safe agent deploymentChatKit assistant for building agentsEvals & prompt optimization tools 4. Why Developers Are Skeptical Still no revenue sharing after 21 monthsVendor lock-in to OpenAI models onlyEU access blocked (27 member states)GDPR fines (Italy €15 M)Broken trust in the developer community 5. ChatGPT vs n8n AgentKit = ease of use + integrationn8n = 400 + integrations, self-hosting, model choiceSerious businesses prototype in ChatGPT → build in n8nAvoid full dependency on one platform 6. Business Implications Who should adopt (B2C, general productivity)Who should avoid (lock-in risk = enterprises / EU)Commoditization problem for OpenAIReal-world CRM integration examples 7. The Big Question “Do you want one company controlling your entire digital ecosystem?”75 % of users prefer diversificationTrust > featuresControl of conversation = control of platform 💬 Notable Quotes “ChatGPT wants to become an orchestration layer for your entire digital life.”“Developers are like that girlfriend you cheated on — ChatGPT broke their promise 21 months ago.”“I have 800 million paying customers. Who wants a piece of it? And by the way, I’m taking 30 percent.”“The question is not who controls the conversation — but where does it happen?” 📚 Resources Mentioned OpenAI Dev Day 2025 AnnouncementsChatGPT AgentKit PlatformMCP Protocol by Anthropicn8n Workflow AutomationZapier / Make.com AlternativesChatGPT GPT StoreEU AI Act & GDPR Regulations 🔗 Connect with Malcolm WerchotaLinkedIn: linkedin.com/in/malcolmwerchotaWebsite: werchota.aiYouTube: youtube.com/@werchotaX (Twitter): x.com/malcolmwerchotaFacebook: AI Cookbook PageInstagram: @malcolmwerchotaaiTikTok: @malcolmwerchota📧 Contact: malcolm@werchota.ai 💡 Show Feedback: social@werchota.ai 🧠 Learn More AI Fit Academy – Malcolm’s hands-on program helping professionals apply AI tools in real workflows. 👉 Ship First, Study Later — Working Workflows by Week 2 or 100 % refund. www.werchota.ai/ai-fit-academy 🎬 Production NoteEpisode recorded live from a hotel in Lower Austria after Malcolm’s workshop with a construction company. SubscribeThe AI Cookbook Podcast → Weekly practical insights on AI implementation, workflow automation, and tool breakdowns — without the hype.

    26min

  8. 7 DE OUT.

    E75: Deloitte AI Scandal: Why Consulting Firms Are Failing at AI

    The consulting industry just had its "Titanic moment." Deloitte refunded the Australian government $440,000 after delivering a report filled with AI hallucinations—fake citations, non-existent research, and fabricated quotes. But this isn't just one firm's mistake. It's a symptom of a dying business model. In this episode, Malcolm Werchota breaks down why traditional consulting firms like McKinsey, BCG, Deloitte, and PwC are sitting on an ejector seat in the age of AI. The old pyramid model—one partner billing out 15 junior analysts—collapses when AI tools can do the research, analysis, and slide decks better and faster than any team of fresh graduates. Malcolm reveals the exact AI tools and workflows his firm uses to deliver better results for clients, including the critical 40% rule: spend 40% of your AI time verifying outputs to avoid hallucinations. You'll discover why recording every single meeting, democratizing information access, and building AI agent armies isn't optional anymore—it's survival. What You'll Learn Why the traditional consulting pyramid model is broken in 2025The exact AI tools Malcolm's team uses daily (Claude, Perplexity, ChatGPT, and more)How to verify AI outputs and avoid the hallucination disaster that destroyed Deloitte's reputationWhy spending 21 hours per week on TikTok makes Malcolm a better AI consultantThe "obelisk model" replacing pyramids: AI agents at the bottom, orchestrators in the middleHow to transition from billable hours to outcome-based pricingReal examples of AI-powered client workshops delivering working solutionsTraditional consulting is experiencing its biggest crisis since 2008. Malcolm Werchota analyzes Deloitte's $440,000 AI hallucination scandal and explains why it signals the death of the pyramid model—and what comes next. Notable Quotes “The margin is not at the top, the margin is at the bottom—and that’s where AI just obliterated the business model.”“Deloitte treated AI like a junior analyst they could exploit for margin instead of teaching people how to use AI correctly. That’s organizational malpractice.”“In the age of AI, learners will be the biggest winners.”“Which management consultant can say they spent 21 hours last week researching AI?”“You cannot bring somebody in today who’s not an AI enthusiast from top to bottom.” Resources MentionedClaude Sonnet 4.5ChatGPT (GPT-4o and GPT-5)PerplexityGemini, GrokAzure OpenAI (used by Deloitte)chat.werchota.comMicrosoft CopilotTikTok (AI content discovery)Graph RAG technologyClaude Code News ReferencesFinancial Times on Deloitte scandalUK regulators’ June 2024 warning to Big FourPwC AI pricing pressure statementAccenture layoffs (13,000 employees) For Consultants and Business LeadersThis episode is essential if you’re: Working in or hiring management consulting firmsConcerned about AI’s impact on consulting careersLooking to implement AI in professional servicesTrying to understand why traditional consulting is failing clientsBuilding an AI-first service business Malcolm’s ChallengeIf you’re still listening, tag Malcolm on social media or leave a comment. Follow the podcast on Spotify to show engagement with these deeper AI transformation episodes. LINKS & CONTACT INFORMATION Where to find Malcolm Werchota: LinkedIn: linkedin.com/in/malcolmwerchotaWebsite: werchota.aiYouTube: youtube.com/@werchotaX (Twitter): x.com/malcolmwerchotaFacebook: AI Cookbook by Malcolm WerchotaInstagram: malcolmwerchotaaiTikTok: malcolmwerchotaGet in touch: malcolm@werchota.ai Email the Show: social@werchota.ai AI Fit Academy: Malcolm’s program for professionals to apply AI tools in real work settings. Learn more: werchota.ai/ai-fit-academy

    44min
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Malcolm Werchota's AI Cookbook is where artificial intelligence meets authentic business transformation. Known for his direct style and willingness to show AI in action—even during live presentations—Malcolm helps organizations understand that AI isn't about replacing humans but amplifying their capabilities. From voice-note productivity hacks to real-time meeting intelligence, this podcast delivers actionable insights for immediate implementation.

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