The Merge (by CodeRabbit)

The Merge by CodeRabbit is a podcast that brings you deep conversations with legendary developers who've shaped the tools we use every day. We explore how artificial intelligence is transforming software development while celebrating the creators and tools that built our foundation. Each episode features intimate discussions about building developer tools, maintaining open source projects, and navigating the evolution of technology.

The Merge (by CodeRabbit) is a technology podcast hosted by Unknown Host, with 19 episodes on record and a Required Pod Score of 80.

Unknown Host hosts The Merge (by CodeRabbit), a technology show with 19 episodes published.

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  Episode #19

  Your Tests Pass. Can Your AI Agent Finish the Job? | Francesco Bonacci, Cua

  Sep 25, 202642 min

  AI agents can click, type, and operate software—but how do you know they actually finished the job? Cua co-founder and CEO Francesco Bonacci joins The Merge to discuss computer-use agents, agent evaluation, and the human judgment behind reliable automation. Hendrik Krack and Francesco explore what it takes to give AI agents computers they can work in—and how to check the results. From testing computer controls to evaluating real tasks in KiCad, the conversation examines the gap between an action succeeding and an assignment being complete. Francesco also shares his experiments with bot-driven development through Slack, including a bot CTO and chief of staff, and explains why he stays close to his coding agents to steer their work. In this episode: • Computer-use agents and the infrastructure behind them • Why working tools don’t guarantee successful tasks • Agent evaluation, Cua-Bench, and circuit-design tasks in KiCad • Catching regressions while shipping quickly • Isolated environments and protecting sensitive data • Delegating to bots while retaining human judgment • Why visibility matters: how repeated attempts led to five identical customer emails What task would you trust an AI agent to handle today—and what would you still check yourself? Tell us in the comments. Explore Cua: https://cua.ai/ Cua on GitHub: https://github.com/trycua/cua Learn about computer use: https://cua.ai/docs/concepts/what-is-computer-use Explore CodeRabbit: https://www.coderabbit.ai/ The Merge is CodeRabbit’s podcast about the people building the future of software. Subscribe for more conversations with founders, engineers, and open-source builders. #AIAgents #ComputerUse #TheMerge

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  Episode #18

  The Last Software Engineer: What AI Can’t Replace | Kent C. Dodds

  Aug 31, 20261h 16m

  AI coding is changing software engineering—but when agents can implement the code, what remains uniquely valuable? Kent C. Dodds joins Hendrik Krack on The Merge to discuss open source, coding agents, product engineering, React, Remix, and why the “last software engineer” will be the person who understands what to build. Kent has spent his career teaching web development and working in open source. In this conversation, he explains how AI is making implementation cheaper, why developers need stronger product judgment, and how his agent-to-PR workflow uses CI and CodeRabbit for independent review while he evaluates system design, migrations, and downstream effects. In this episode: • Kent’s path through PayPal, open source, React, Remix, and Epic Web • Why coding agents change the developer’s role • The “last software engineer” thought experiment • Product engineering versus ticket taking • Choosing the right problem before writing code • What junior developers should learn in the AI era • Reviewing systems, not only diffs • Kent’s AI coding workflow with pull requests, CI, and CodeRabbit • Durable skills: judgment, communication, ownership, and feedback loops Learn more about Kent C. Dodds: https://kentcdodds.com/ Epic Product Engineer: https://www.epicproduct.engineer/ Epic AI: https://www.epicai.pro/ Epic Web: https://www.epicweb.dev/ Try CodeRabbit: https://www.coderabbit.ai/ What do you think the last valuable software engineer will still do? Share your answer in the comments, and subscribe for more conversations with the builders shaping open source and AI-powered software development. #AICoding #SoftwareEngineering #OpenSource

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  Episode #17

  All the alpha is in the remaining 20%

  Aug 27, 202639 min

  How does a hackathon project become infrastructure for more than 2,000 open-source repositories and reach 1.4 million monthly npm downloads? In this episode of The Merge, Hendrik Krack sits down with Simon Farshid, founder of Assistant UI, to explore what it really takes to build production-ready AI chat for AI agents. Simon explains why the visible chat window is only the surface. Behind it are streaming responses, state management, message editing, attachments, voice, interruptions, agent backends, and the level of polish users now expect from every AI product. The conversation also examines how AI coding agents are changing software engineering. When implementation becomes easier, writing clear specifications, understanding the product, reviewing edge cases, and having good taste become the real competitive advantages. As Simon puts it: “All the alpha is in the remaining 20%.” In this episode: • Why state management is the hardest part of AI chat • How Assistant UI grew from a hackathon project • The future of AI agents and generative interfaces • Why product taste is becoming an essential engineering skill • TypeScript vs. Python for building AI agents • How coding agents are creating more full-stack engineers • Simon’s automated CodeRabbit review and repair loop • How Assistant UI approaches open source and monetization • Why great engineers will lean forward instead of letting AI do everything CHAPTERS 00:00 — The 80% trap and the rise of product taste 01:19 — Meet Simon Farshid 01:56 — What is Assistant UI? 02:44 — From hackathon project to startup 03:32 — 2,000 repositories and 1.4M monthly downloads 05:28 — Why building AI chat is harder than it looks 07:23 — Designing a modular open-source product 08:43 — Why taste is the new engineering bottleneck 10:29 — TypeScript vs. Python for AI agents 13:24 — How coding agents are changing engineering teams 16:25 — Building a business around open source 20:38 — The future of AI chat and generative interfaces 23:17 — “They said chat was dead” 27:38 — Generative dashboards and new UI primitives 29:28 — The future role of software developers 30:36 — Running coding agents in a CodeRabbit review loop 34:10 — Lean forward: where the remaining 20% lives 35:57 — Rapid-fire questions Explore Assistant UI: https://www.assistant-ui.com/ Assistant UI on GitHub: https://github.com/assistant-ui/assistant-ui Try CodeRabbit: https://www.coderabbit.ai/ Subscribe for more conversations with the engineers and founders building the future of software development. #AIAgents #AIChat #AICoding

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  Episode #16

  We still don't understand LLMs today.

  Aug 20, 202630 min

  How do LLMs actually work—and why do they remain black boxes? In this episode of Merge, Shriyash “Yash” Upadhyay, co-founder of Martian, joins CodeRabbit to explore LLM interpretability, AI research, code review benchmarks, and the search for the “steam engine of AI.” We discuss: - Why we still don’t fully understand how LLMs work - How Martian is researching machine intelligence - Why code review is a crucial test of AI code generation - How precision and recall shape AI code-review performance - Why static AI benchmarks eventually become unreliable - How real-world developer behavior can improve evaluations - What more reliable and interpretable AI could unlock - The tools and programming languages Yash uses in his own work - How aspiring researchers can get started in machine learning Today’s language models can generate code, solve complex problems, and power increasingly autonomous systems. But without understanding why they succeed, when they will fail, and how their internal mechanisms produce their outputs, building AI systems we can truly trust remains difficult. Could interpretability provide the scientific foundation for the next generation of AI? Learn more about Martian: https://withmartian.com/ Learn more about CodeRabbit: https://coderabbit.ai/ Subscribe for more conversations about AI, software engineering, code review, and the future of developer tools. #LLM #AIInterpretability #ArtificialIntelligence

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  Episode #13

  Fixing "AI Slop": Managing Agents Like Stressed MIT Interns w/ Jesse Vincent, creator of Superpowers

  Jun 8, 20261h 19mS0

  <p>What happens when you treat an AI agent like a brilliant, chaotic, sleep-deprived MIT intern instead of a perfect computer program? You actually get elite code.</p><p>In this episode of The Merge, we sit down with open-source legend Jesse Vincent, the mastermind behind "superpowers"—the viral AI development framework that exploded to 221k+ GitHub stars in a matter of months. </p><p>Jesse explains why most AI coding tools produce unusable "AI slop" and how he used his 30-year career in management and engineering to fix it[cite: 1]. We break down the exact multi-agent engine powering superpowers: a s...

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