Why isn't This AI Thing Working

Launch Consulting
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We were all told we needed AI. So, we got AI. And for a lot of companies… nothing really changed. Pilots worked. Tools got adopted. But when AI hit real workflows, things stalled or broke. The reality is, unless your business was built yesterday, it probably wasn’t designed for AI. This podcast is about that moment—when companies realize AI isn’t just something you add. It changes how the work actually gets done. We talk to the people figuring that out in real time—what worked, what didn’t, and what they did next.

Episodes

  1. Oct 30 ·  Video

    Your AI Isn’t Broken, Your Process Is | with Alyssa Clarcq, “Alyssa with AI”

    When AI stalls after the pilot, the instinct is to blame the tool. CPA-turned-AI-builder Alyssa Clarcq has a blunter diagnosis: if your process isn’t documented, AI can’t follow it, just like an intern you never properly trained. Host Jess Lampe of Launch Consulting talks with Alyssa about her path from Big Four external audit to vibe-coding an “AI-native company” with no programming background, guided largely by software developers in her TikTok comments. She explains how her system works: a second brain holding all her context, a central task tracker, specialized “desks” for finance, marketing, and content, and agent loops for prep, review, and QA. She also covers why governance and guardrails matter when AI can hallucinate on a regular basis. They get into the realities: calculating a net savings of about 10 hours a week, building a “babysitter” chat to manage parallel agents, the surprising cognitive load of constant decision-making, and rising token costs that have her weighing local models. Alyssa closes with advice for organizations: treat AI adoption as upskilling rather than replacement, invest in real training, and start with your internal audit team, the people who already understand your processes end to end. Follow Alyssa Clarcq at: https://www.tiktok.com/@alyssa.with.ai https://www.linkedin.com/in/alyssa-clarcq-cpa https://alyssaclarcq.com https://www.skool.com/ai-office-hours-with-alyssa-4640/about

    Your AI Isn’t Broken, Your Process Is | with Alyssa Clarcq, “Alyssa with AI”

  2. Sep 15 ·  Video

    Babysitting vs. Delegating: How to Actually Trust an AI Agent

    Everyone was promised that AI would hand back their time — so why does it feel like you're babysitting four terminals, clicking "yes, allow this" one prompt at a time, and re-reading long specs just to check whether the model did what you asked? In this episode of Why Isn't This AI Thing Working, Jess Lampe talks with Jim and Alysha Rosser, co-founders of Entry Studios and the team behind Grove. Their take on why AI stalls after the pilot: it's a trust problem. Agents skip instructions, invent their own commands, and declare victory before the work is done — quietly shifting the cognitive load onto whoever reviews the output next. Grove is their answer, and it started as a tool they built to solve their own frustration. Jim and Alysha make the case for wrapping AI in old-school determinism: task lists with hard proof requirements, permission "boundaries" that redirect an agent instead of just blocking it, and executive summaries that show the receipts on every session. The result is a two-person team that queues work overnight and walks into roughly ten reviewable PRs each morning — about 900 merged since July. Along the way: cognitive load, "making determinism cool again," designing upfront, and why living in the chat window all day means you're doing it wrong.

    Babysitting vs. Delegating: How to Actually Trust an AI Agent

  3. Sep 1 ·  Video

    LLMs vs. Agents vs. Harnesses: How AI Actually Works

    In this episode of Why Isn't This AI Thing Working?, host Jess Lampe sits down with Alex Kozlowski, Director of Software Engineering at Launch Consulting, to cut through the jargon and explain how AI systems actually work. Alex and Jess demystify the vocabulary everyone uses but few define: what a large language model really is, why LLMs are probabilistic (and why that makes hallucinations inevitable), and what separates an LLM from an "agent" and an emerging "harness" like Claude. Using plain-language analogies, they explain how tool-calling loops create the emergent behavior people find so impressive — and where these systems predictably go wrong. They also tackle adoption reality: why teams with strong DORA metrics get the biggest gains, and why most AI proofs-of-concept never reach production.

    LLMs vs. Agents vs. Harnesses: How AI Actually Works

  4. Aug 18 ·  Video

    Edge AI Explained: Local LLMs, Token Costs and ROI w/ Ozzie Diaz

    In this episode: How edge AI differs from cloud-based AIWhen running LLMs locally makes business senseUnderstanding token-based AI pricing and consumptionComparing privacy, latency and infrastructure tradeoffsEvaluating the ROI of local and cloud AI modelsWhat technology and finance leaders should consider before scaling AI investment

    Edge AI Explained: Local LLMs, Token Costs and ROI w/ Ozzie Diaz

  5. Aug 6 ·  Video

    Responsible AI: Building Customer Trust at Scale w/ Ieshika Chandra

    In this episode: Building customer trust in AI-powered experiencesBalancing personalization with responsible AI practicesUsing guardrails to improve reliability and reduce errorsMeasuring AI performance beyond technical accuracyScaling machine learning and agentic systems responsiblyMaintaining human oversight as AI becomes more autonomous

    Responsible AI: Building Customer Trust at Scale w/ Ieshika Chandra

  6. Jul 21 ·  Video

    Generative AI Myths: What AI Can and Cannot Do w/ Luc Julia

    In this episode: Challenging common myths about generative AIUnderstanding what AI can and cannot doThe difference between artificial intelligence and augmented intelligenceWhy human creativity and critical thinking remain essentialMoving beyond AI hype to identify practical business use casesUsing AI to strengthen human capabilities rather than replace them

    Generative AI Myths: What AI Can and Cannot Do w/ Luc Julia

  7. Jul 14 ·  Video

    How to Build an AI Business Case That Proves ROI

    In this episode: Building an AI business case that resonates with CFOsConnecting AI investment to measurable business outcomesWhy cost reduction alone is not a complete AI strategySelecting AI use cases with clear potential valueUnderstanding how token-based pricing affects financial planningMeasuring AI ROI and deciding which initiatives to scale

    How to Build an AI Business Case That Proves ROI

  8. Jun 22 ·  Video

    AI Adoption Starts With Curiosity, Not Technology

    In this episode: Using curiosity and experimentation to make AI more approachableHow humor and creativity can reduce resistance to AIBuilding AI literacy without requiring technical expertiseCreating low-pressure opportunities for people to explore AIWhat live audience reactions reveal about AI adoptionHelping employees develop confidence using AI toolsLearn more about It Writes Itself at itwritesitself.ai. See Mike's magic at hellomagicmike.com.

    AI Adoption Starts With Curiosity, Not Technology
  • 8 Episodes

About

We were all told we needed AI. So, we got AI. And for a lot of companies… nothing really changed. Pilots worked. Tools got adopted. But when AI hit real workflows, things stalled or broke. The reality is, unless your business was built yesterday, it probably wasn’t designed for AI. This podcast is about that moment—when companies realize AI isn’t just something you add. It changes how the work actually gets done. We talk to the people figuring that out in real time—what worked, what didn’t, and what they did next.

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