Podcast
LaunchStack AI
Hosted by LaunchStack AI · EN
Every week we unpack the automations, apps, and creative systems that help real businesses get their time back and stack revenue. Think Make, Airtable, Framer, and OpenAI turned into marketing engines, productivity loops and money machines.
Curated by @KenbuildsAI, this podcast drops raw, practical episodes for founders, creators, and operators ready to stop watching trends and start wiring them into their business.
launchstackai.substack.com
launchstackai.substack.com
5episodes
Episodes
Newest firstAll episodes
STACK SIGNAL 006. The Compact AI Revolution
Jan 1200:15:55Tap to summarizePODCAST SUMMARY:Bigger isn’t winning anymore. Smarter is.In this episode, we break down January 2026’s compact AI revolution — where a 7-billion parameter model is outperforming systems seven times its size, funding is flooding into platforms that democratize AI (not companies hoarding it), and the shift from “AI as tool” to “AI as colleague” is officially underway.We cover:* Falcon-H1R and why compact models are changing the economics of automation* Lovable’s $6.6B valuation from letting non-coders build apps with prompts* NVIDIA’s Physical AI play with Alpamayo and what it means for real-world deployment* The StackFlow breakdown: how to apply this to your GrowthFlow, OpsFlow, and InsightFlow* Plus: Albania’s AI cabinet minister, a vending machine that tried to call the FBI, and lawyers predicting judge rulings with 86% accuracyThe operators who build specialized stacks in 2026 won’t just save money — they’ll outperform teams ten times their size.Build the stack. Ship the system. That’s the game now.Subscribe for free to receive new posts from LaunchStack AI & Ken Anthony. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit launchstackai.substack.com
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STACK SIGNAL 004. GPT-5.2 and the 'Ship Faster or Die' Trap
Dec 2700:17:03Tap to summarizeGPT‑5.2 just dropped, and it feels less like a chill upgrade and more like a “ship faster or die” move in the middle of an AI arms race. In this episode, we break down why OpenAI rushed this release, how it changes the economics of building on their stack, and what operators should actually do about it.We’ll cover:* Why release cadence is now a competitive weapon, not just a product roadmap.* How GPT‑5.2 shifts the risk profile for businesses running everything on OpenAI.* Adoption and usage trends across GPT, Claude, and Gemini & what they signal for 2026.* A practical playbook for moving toward multi‑model stacks without blowing up your workflows.Prefer to read this one? The full Stack Signal write‑up, including the “Weird Stack Overflow” section and feature comparison table:Resources mentioned:* Full issue and show notes: https://launchstackai.substack.com/p/OPENAI-GPT-52-STACK-SIGNAL* LLM Stack Operator Kit on Gumroad (multi‑model routing + eval templates) dropping Jan 01.* LaunchStack AI newsletter: If this episode helps, tap follow, share it with an operator who’s rebuilding their AI stack, and reply on Substack with your current model mix. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit launchstackai.substack.com
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STACK SIGNAL 003. Google's Multi-Layer AI Expansion Is Hard to Ignore
Dec 800:12:11Tap to summarizeSTACK OVERVIEWThis month confirmed something that’s been building quietly all year: Google isn’t trying to win one category of AI: they’re building the entire stack.From model upgrades to agent frameworks, from TPUv5p compute to Imagen 3 and Veo 3.3 creative tools, this shift runs through every layer of the ecosystem. We’re watching a company move from “search giant with AI tools” to “AI infrastructure company that happens to own search.”Google is coming after OpenAI’s reasoning edge, Anthropic’s analysis edge, and everyone’s creative tools: at the same damn time. They’re not picking a lane. They’re paving the road.If you’re a creator, SMB, or enterprise team, these moves directly impact the tools you’ll be using in 2025. The question isn’t whether AI will reshape your workflow. It’s which stack you’ll be building on when it does.Let’s unpack this.Gemini Steps Fully Into the Agent EraGoogle doubled down on “AI that works with you,” not just answers prompts. The shift is from question-and-answer interfaces to goal-based coordination systems. Think less ChatGPT, more autonomous operator.What dropped this cycle: Gemini 2.0 Ultra and Flash, Workspace Enterprise AI, Live APIs and Video APIs, plus new App Builder templates. You can explore the full scope through Vertex AI Agents and the Gemini API Agents documentation.This is the closest Google has come to OpenAI’s o-series agent frameworks, and it closes a lot of the gap. Where OpenAI has been leading in reasoning-heavy agent behavior, Google is now building the infrastructure to make agents accessible across every layer of the business stack.The play here is clear: agents that don’t just respond, but orchestrate. Email drafted, data fetched, task created, automation triggered, result monitored, summary delivered. One flow. No human intervention unless something breaks. This is what the next generation of business automation looks like.Infrastructure Upgrades Across TPU, GPU, ARM, and Multi-ArchGoogle’s hardware story is strong right now. While most people focus on models and features, the real strategic advantage is being built at the infrastructure level. Better compute means faster inference, lower costs, and more accessible tools for everyone downstream.What’s now live: TPUv5p is generally available, A3 Mega and A3 Ultra are rolling out, NVIDIA Blackwell-ready systems are in place, Axion v2 updates are shipping, and GKE inference enhancements are improving throughput across the board.This is what fuels cheaper, faster model access for everyone, creators included. When TPUv5p becomes generally available, that improvement ripples through every tool that runs on Google’s infrastructure. Your ChatGPT competitor gets faster. Your image generation tool gets cheaper. Your video rendering pipeline handles more requests.Infrastructure upgrades don’t make headlines, but they change economics. And when economics shift, accessibility follows. That’s the real story here.Generative Media Breakthroughs (Imagen 3 + Veo 3.3)Google’s creative tools now compete directly with OpenAI’s Sora. For the first time, we’re seeing real parity in generative media across multiple platforms. That’s significant because competition drives quality up and prices down.What improved: Imagen 3 brings photorealism and fine control to image generation. Veo 3.3 delivers more cinematic output with better prompt adherence. MusicLM 2 upgrades generative audio. Chirp strengthens multilingual accuracy.This is enterprise-level media creation without the enterprise budget. A solo creator using Veo 3.3 and Imagen 3 can produce visuals that would’ve required a production team two years ago. A local business can generate ad creative at scale without hiring an agency. A content team can spin up video concepts in minutes, not days.The ceiling for what’s possible keeps rising. And the floor for who can access it keeps dropping. That gap is where opportunity lives.Google Learn Replaces Google SkillsGoogle consolidated (most of) its training ecosystem into one unified platform at Google Skills. It’s a smart move. Fragmented learning resources create friction, and friction kills adoption.What’s now under one roof: Cloud Skills, DeepMind training, Gemini courses, Workspace AI labs, and developer bootcamps. This matters if you’re building digital literacy programs, running internal training, or trying to upskill a team. One hub. One login. One learning path. It’s the kind of boring operational improvement that makes real implementation easier.Great for internal training, youth programs, and community education. If you’re running workshops or building curriculum around AI tools, this is your new starting point.New Case Studies Highlight Real-World AdoptionEnterprise teams are no longer “experimenting.” They’re integrating.These aren’t pilot programs. They’re production deployments. Shopify is using AI to power commerce at scale. United Airlines is streamlining operations. Canva is embedding generative tools into design workflows. Mercedes-Benz and L’Oréal are rethinking customer experience and manufacturing through AI-first systems.When companies at this level commit resources and infrastructure to AI integration, it signals something important: the technology is stable enough to bet on. That confidence filters down. If Mercedes-Benz is building on Google’s AI stack, smaller brands can trust it too.This is the validation phase. And it’s happening fast.FEATURE COMPARISON: GOOGLE VS OPENAI VS ANTHROPICGOOGLE vs. OPENAI vs. ANTHROPICGoogle → The Full-Stack PlayGoogle is aiming for the entire lifecycle: hardware + cloud + models + agents + media tools + enterprise software. They want to own every layer of the stack, from the chips that run inference to the applications that deliver value to end users.This is the most ambitious AI strategy in the market. It’s also the riskiest. Building everything in-house means longer timelines, more complexity, and higher operational overhead. But if it works, Google becomes the default infrastructure for AI — the same way AWS became the default for cloud computing.The bet is simple: if you control the stack, you control the economics. And if you control the economics, you win the long game.OpenAI → The BrainOpenAI continues to lead in reasoning, coding, and agent intelligence. Their o-series models represent the most advanced autonomous agent behavior available today. Their focus is narrow and deep: build the smartest AI, then let others figure out how to integrate it.OpenAI continues to lead in:* Reasoning* Coding* Assistant intelligence* Agent autonomy (o-series)* Long-context planningSora is powerful, but Google’s media stack is catching up fast. The real question is whether OpenAI can maintain its reasoning edge while competitors close the infrastructure and tooling gaps. Right now, they’re still ahead. But the margin is shrinking.Anthropic → The AnalystClaude continues dominating in analysis, long-form reasoning, and safety-first workflows. If you’re working with legal documents, research papers, or complex written content, Claude is still the best tool available.Claude continues dominating:* Deep analysis* Thoughtful reasoning* Legal and research tasks* Long documents* Safety and reliabilityIts agent tools are improving but less mature than Google’s or OpenAI’s. Anthropic’s focus has always been on building trustworthy, interpretable AI. That positioning is valuable — especially in regulated industries — but it also means slower movement into autonomous agent territory.The trade-off is intentional. Anthropic is betting that trust and reliability will matter more than speed as AI becomes more embedded in critical workflows.Google wants to own the stack.OpenAI wants to own intelligence.Anthropic wants to own trust + analysis.Three strategies. Three outcomes. One accelerating race. And the thing is, they’re all right. There’s room for a full-stack infrastructure play, a pure intelligence play, and a trust-first play. The market is big enough to support all three. Clearly, there are other players in the generative AI space that area making waves (grok, deepseek, mistral, perplexity), we’re spotlighting the big three.What matters for you is understanding which strategy al...
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5 Free Google Tech Courses
Dec 600:12:15Tap to summarizeGoogle is quietly giving away training that used to cost thousands—skill badges, learning paths, and certifications that teach you how AI actually works, how to read your data, and how to market your business without bleeding cash on agencies.In this episode, we break down five free courses every solopreneur, creator, and small business owner should know about:💡💡💡💡💡 Google DeepMind: Train a Small Language Model — Actually build AI, don’t just use it💡💡💡 Generative AI Leader Learning Path — Five courses on deploying AI across your business💡 Fundamentals of Digital Marketing — 40 hours of SEO, ads, email, and analytics💡💡 Google Analytics Certification — Know exactly what’s working💡💡 Google Ads Search Certification — Run paid campaigns with confidenceWe’ll walk you through what each course covers, how difficult they are, why they matter for your business, and how to stack them into a system that makes you more capable.It’s free to share, spread the knowledgeThanks for listening…Subscribe for free to receive new LaunchStack AI podcasts, posts and ways to increase your revenue This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit launchstackai.substack.com
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Has AI disrupted Project Management?
Nov 2300:12:29Tap to summarizeAI broke project management: but not the way you think. Gantt charts are dying. Sprints are shifting. And the PMs who learn to operate AI systems are building distance on the ones who don’t. This episode breaks down how tools like Motion, Asana, and ClickUp are absorbing coordination work, what that means for PM roles, and why hybrid teams are outpacing manual workflows by 30-40%. If you manage projects, this is where your job is headed.Let this episode is your roadmap through the messy middle of the transition. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit launchstackai.substack.com
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