AI Tinkerers - "One-Shot"

What Happens When You Hit Claude’s Limits? | Sam Hesson (Meta AI)

Description: Sam Hesson — technical founder and newly minted member of Meta's AI incubation team — joins the AI Tinkerers One-Shot podcast for a deep-dive into the custom CI/CD pipeline he built to orchestrate parallel AI agents at scale. Sam became notorious for spending $50,000 on tokens in just two months while pushing the limits of what agentic development systems can do. In this episode, he shares his complete architecture. Sam walks through his "Token Abundance Mindset" and explains why moving beyond single-turn prompting is the key to unlocking a fully automated, multi-agent development workflow. From structuring your codebase for AI readiness to running adversarial LLM judges that self-heal pull requests, this is one of the most technically advanced conversations we've had on the show. Topics covered in this episode: * The Darwinian CI/CD — running multiple parallel agents in competition to produce the best pull request * LLM Judge — rubric-based quality control and adversarial agents for self-healing PRs * AI Dev Readiness — DB seeding, snapshots, and codebase prep for reliable agent testing * The Walk Flow — converting high-level conversations (via Meta Ray-Bans) into structured PRDs and Tech Specs * DevPlan — generating detailed, unambiguous coding prompts that eliminate guesswork for agents Timestamps: 00:00 Introduction: Sam Hesson & Claude Maxing 02:17 The Alpha of 10x Agentic Systems 03:30 The $50k Token Spend & Abundance Mindset 07:25 The Walk Flow: Ray-Bans to PRD/Tech Spec 11:17 AI Adherence to Implementation Patterns 15:21 Playwright & AI Codebase Readiness 17:35 The Darwinian CI/CD: Parallel Agents 21:47 LLM Judge & Rubric-Based Self-Healing 31:03 Bruno API Client: Code-Like Specs 32:47 Self-Healing PRs & Agentic Graph RAG 38:40 DevPlan: Turnkey Structured Prompting 58:43 The Future of SDLC & AI Agent Adoption Resources: * Sam Hesson on LinkedIn: linkedin.com/in/samhessenauer [http://linkedin.com/in/samhessenauer] * Nanome.ai [http://Nanome.ai] (Sam's former company) * AI Tinkerers: aitinkerers.org [http://aitinkerers.org] * One-Shot Podcast: aitinkerers.org/podcast [http://aitinkerers.org/podcast] * AI Tinkerers One-Shot is a podcast for builders and innovators defining the future of AI — going under the hood with the people actually shipping it.

The Architecture of Vibe Coding: Inside Bolt.new's Stack

In this conversation, Eric Simons, founder and CEO of StackBlitz, walks through one of the fastest and most consequential pivots in modern developer tooling. After nearly seven years building deep browser infrastructure and reaching roughly $700k in ARR, the company reoriented around Bolt, effectively defining the vibe-coding category and scaling past $15M ARR in a matter of months. We go under the hood of the WebAssembly-based architecture that lets Bolt run a full Node.js environment directly in the browser, delivering near-instant feedback and fundamentally different unit economics than cloud-hosted VMs. Eric explains the specific model breakthrough that made full-stack, one-shot app generation viable, and why this moment reordered who actually builds software inside companies. 00:00 Introduction 00:36 The 7-Year History and Pivot Point 01:01 The Original WebAssembly Vision 03:20 Near Bankruptcy: $700k ARR 10:49 Sonnet 3.5: The Vibe Coding Unlock 14:23 The $15 Million ARR Board Meeting 17:19 The Web Container/WASM Advantage 22:07 Bolt Demo: Full-Stack App from a Prompt 31:09 The Changing Role of PMs and Designers 36:23 Mitigating AI-Generated Code Security Risks 47:31 The Entrepreneurial Mindset 53:35 What Eric is Tinkering With Now

Inside Browser Automation: Andrew Baker on Agents, Playwright, and Claude Draws

In this episode of AI Tinkerers One-Shot, Joe sits down with Andrew Baker—serial builder, former Twilio engineer, and hands-on experimenter in agentic systems—to explore the rapidly evolving frontier of browser automation and AI-driven agents. Andrew shares how his journey began with simple scripting experiments and gradually evolved into sophisticated browser agents capable of handling complex, real-world workflows. One standout example: an airline seat selector that used browser agents to secure optimal seats for frequent flyers—highlighting both the power and the limitations of today’s tooling. Along the way, Andrew breaks down the practical challenges builders face when working with browser agents at scale: • Vision model accuracy and UI interpretation • DOM complexity and brittle page structures • Authentication hurdles and session persistence • The real economics of running large-scale automations The conversation then shifts to “Claude Draws,” Andrew’s playful yet technically impressive side project that brings the classic 90s app Kid Pix into the age of AI. He explains how he wired up a remote PC, streamed sound output, and carefully crafted prompts that allow Anthropic’s browser agent to control a nostalgic art application—brushes, stamps, chaos, and all. The result is both a technical deep dive and a reminder that creativity is often where agentic tooling shines most. Joe and Andrew also zoom out to examine the broader ecosystem shaping the future of browser-native agents. They discuss why UI accessibility matters for agents, how frameworks like Stagehand and Playwright are transforming automation workflows, and why personal evaluation benchmarks are becoming essential for builders pushing these systems beyond demos and into real usage. 💡 Resources & Links Andrew Baker: https://www.linkedin.com/in/andrewtorkbaker [https://www.linkedin.com/in/andrewtorkbaker] AI Tinkerers: https://aitinkerers.org [https://aitinkerers.org] Andrew’s newsletter: https://implausible.ai [https://implausible.ai] What you’ll learn • How browser automation evolved from basic scripts to autonomous agents • Why DOM parsing, vision models, and page structure still trip up agents • How Claude for Chrome was used to control a web-based Kid Pix experience • The architecture behind remote execution, sound streaming, and automation hacks • How Stagehand and Playwright support modern browser automation • The technical, economic, and ethical considerations shaping the future of browser agents Chapters 00:00:15 — Introduction and AI Tinkerers Community 02:49 — Twilio Origins and Browser Automation Journey 04:50 — Building the Airline Seat Selector 07:51 — Browser Agent Challenges and Vision Models 10:44 — Stagehand Framework and Browser Automation Stack 13:28 — Claude for Chrome and Authentication 16:58 — Kid Pix Origins and Demo Setup 21:33 — Technical Architecture and Playwright Tricks 29:24 — Evaluation Platform and Personal Benchmarks 37:42 — Future of Browser Agents and Web Economics Subscribe for more conversations with the builders shaping the future of AI, automation, and agentic systems.

Scaling AI in the Real World: Lukas Biewald on Tools, Teams & Tinkering

What happens when a lifelong tinkerer turns curiosity into two major AI companies? In this episode of AI Tinkerers One Shot, Joe talks with Lukas Biewald—founder of Weights & Biases and CrowdFlower—about how early projects like robot cars and Raspberry Pi experiments shaped his engineering mindset and entrepreneurial path. Chapters: 00:00 — Intro & Guest Background 02:07 — Early Tinkering and CrowdFlower 03:06 — Building Robot Cars and Meeting Pete Warden 08:41 — From Tinkering to Weights & Biases 12:27 — Parenting, Vibe Coding, and Kids as Makers 21:56 — 3D Printing and Creative Play 24:25 — AI Tools, Team Structure, and Company Growth 26:43 — Agentic Coding: Opportunities and Challenges 35:40 — AI in Production: Observability and Real-World Use Cases 49:28 — The Future of AI, Fine-Tuning, and RL https://youtu.be/S84CjOrlMcY [https://youtu.be/S84CjOrlMcY]

Beyond Instructions: How Beads Lets AI Agents Build Like Engineers

In this episode of AI Tinkerers One-Shot, Joe sits down with Steve Yegge—engineer and creator of the Beads framework—to explore how open source tools are transforming the way we build with AI. Steve shares the story behind Beads, a new framework that gives coding agents memory and task management, enabling them to work longer, smarter, and more autonomously. From his days at Amazon and Google to leading engineering at Sourcegraph, Steve reveals how Beads is already reshaping developer workflows and why it’s gaining hundreds of contributors in just weeks. What you’ll learn: - How Beads gives coding agents “session memory” and lets them manage complex, multi-step projects. - Why Steve believes the future of engineering is about guiding and supervising AI—rather than just writing code. - The evolution from chaotic markdown files to structured, issue-based workflows. - Techniques for multimodal prompting, automated screenshot validation, and “landing the plane” for session cleanup. - The challenges and breakthroughs in deploying AI tools at scale within organizations. - How Beads and similar frameworks are making it easier for both junior and senior developers to thrive in the age of AI. Whether you’re a developer, tinkerer, or just curious about the next wave of AI-assisted coding, this deep dive with Steve Yegge will show you what’s possible now—and what’s coming next. 💡 Resources: Beads – https://github.com/steveyegge/beads [https://github.com/steveyegge/beads] Steve Yegge – https://www.linkedin.com/in/steveyegge/ [https://www.linkedin.com/in/steveyegge/] & https://x.com/Steve_Yegge [https://x.com/Steve_Yegge] AI Tinkerers – https://aitinkerers.org [https://aitinkerers.org] Subscribe for more conversations with the builders shaping the future of AI and robotics! 00:00 - Introduction to Steve Yegge and Beads Framework 02:10 - Steve's Background and Source Graph AMP 08:00 - Building a React Game Client with AI Agents 15:36 - Multimodal Prompting and Screenshot Validation 23:16 - Code Review Techniques and Agent Confidence 32:01 - The Evolution of Beads: From Markdown Chaos to Issue Tracking 43:11 - Landing the Plane: Automated Session Cleanup 52:09 - Deploying AI Tools in Organizations 58:59 - Code Review Bottlenecks and Graphite Solution 01:02:57 - Closing Thoughts on AI-Assisted Development