Watch this episode on YouTube: https://www.youtube.com/watch?v=ze5R5fMKwVY

Watch this episode on YouTube: https://www.youtube.com/watch?v=DS-Dh3AhiIA

Darren created Rancher and k3s, and he is now chief architect at Obot. Matt restates the roles from episode 3 and drops computer scientist. A programmer writes the code someone else specified. A developer owns the lifecycle. A software engineer is supposed to own requirements, design, and reliability. The Bureau of Labor Statistics has programmer employment on a long decline, with hiring mostly replacements. It groups developers and engineers together and calls that work growing.

Darren does not fit the list. He calls himself a bad programmer and an agent of chaos. He cares about the system, how the pieces fit, and the compromise in an architecture. He does not care about the process, and he does not want a perfect design. Robert treats architect as a level inside any of those jobs. Darren pushes back: some engineers optimize a widget and ignore the business problem, which is how engineers end up creating business problems. Matt splits the work another way: people who go deep on one component, people who go wide on the user problem, and people who see a problem and run off to invent something. WordPress and Longhorn come up as cases where the useful question is what you are optimizing for, not whether the code is pretty.

Then AI. Darren does not accept the claim that training on open source destroys it. Rancher sold support and never licensed the software, and he still treats the value as the relationship, not the repo. He wants open source projects to hand the toil to AI, and he thinks code quality goes up once the process is less immature than the last year. Remix 3, which just shipped a stable release and left React, is his example of work a model will not originate: a new idea about simpler JavaScript, not another React app. Robert hates drive-by pull requests and still uses AI for syntax he does not want to keep in his head. Matt compares the model to the crew that lays pipe and cable after the house is designed, and notes that some contributors liked that work.

Senior engineers can guide a model because they already know how the system is put together. People in their twenties are being told to start with the model. Darren’s advice is to copy the seniors who are actually doing the work, and to ignore the posts that claim one prompt built the app. A Rust-to-Bun port, he says, was hours of skilled guidance, not a sentence.

Links

• Episode 3: https://softwaremadhouse.com/episodes/episode-3/
• Obot: https://obot.ai
• Remix: https://remix.run
• k3s: https://k3s.io
• Longhorn: https://longhorn.io

Watch this episode on YouTube: https://www.youtube.com/watch?v=U6xkSQUhQds

Robert and Matt start with the talk that set it off. At Rails World last week, DHH said he has retired from professional programming and now calls himself an “Energized Professional Maker.” We go through his main points. He says the old 10x-programmer debate is obsolete, because the gap between a weak programmer without agents and a strong one with them is closer to 100x to 1,000x. In about 20 months he produced roughly half as much code as in the previous 21 years. 37signals is moving Hey from a web app to a Rust backend service, written without reading the code, with native apps on six platforms. And according to DHH, your app needs a CLI, not excuses. We also cover his recent work on Omarchy and compare all of this with Gallup polling that shows optimism about AI is uneven around the world and lower in the West.

Is running agents like being a manager? We look at Denise Schannon’s take on that comparison and at a four-level model of agentic software development in the enterprise. Then we look at developers taking the opposite path, such as the proposed no-AI policy from some GNOME developers. Rob explains why some developers want AI out of their work and what that could mean for them.

We finish with DHH’s claim that slop is “an executable idea” and return to the question from our previous episode: where do development and engineering fit now?

Links

• DHH’s talk: https://www.youtube.com/watch?v=vDjW_dRyKXY
• Gallup, global optimism about AI: https://news.gallup.com/poll/714593/optimism-globally-widespread-despite-uneven.aspx
• Denise Schannon on managing agents: https://www.linkedin.com/feed/update/urn:li:activity:7508548991379484672/
• Four levels of agentic software development: https://kasparvongruenberg.substack.com/p/four-levels-of-agentic-software-development
• The GNOME LLM policy proposal: https://blogs.gnome.org/alatiera/2026/09/23/the-gnome-llm-policy-that-i-want/
• DHH on slop: https://x.com/dhh/status/2103454839086706746

Watch this episode on YouTube: https://www.youtube.com/watch?v=SuKX0EnULr8

They break down what the sad path actually is, why developers naturally skip it (code is written for the success case, negative tests feel like extra work, and coverage tools don’t tell the whole story), and where the gaps show up in production, from partial failures in multi-service architectures to untested catch blocks, else branches, early returns, retries, and fallbacks. They close on a practical note: with today’s tooling, including AI assistance, writing tests for both the positive and negative cases is easier than it has ever been. There’s no good excuse left.

Watch this episode on YouTube: https://www.youtube.com/watch?v=PpQwkBuPxy8

They also pull Bureau of Labor Statistics outlooks for programmers, software developers, and computer and information research scientists, and talk about what BLS is saying about AI and IT employment through 2034. The practical question underneath the titles: what do you actually own on a team, and what should you put on a resume when the words keep sliding.

Links

• ACM Computing Curricula 2020: https://www.acm.org/media-center/2021/march/computing-curricula-2020
• BLS - Computer programmers: https://www.bls.gov/ooh/computer-and-information-technology/computer-programmers.htm
• BLS - Software developers: https://www.bls.gov/ooh/computer-and-information-technology/software-developers.htm
• BLS - Computer and information research scientists: https://www.bls.gov/ooh/computer-and-information-technology/computer-and-information-research-scientists.htm
• BLS -Artificial intelligence, information technology, and employment, 2024–34: https://www.bls.gov/opub/ted/2026/artificial-intelligence-information-technology-and-employment-2024-34.htm

Watch this episode on YouTube: https://www.youtube.com/watch?v=Gf9na-uU-qU

Links & mentions

• FDE on Wikipedia: https://en.wikipedia.org/wiki/Forward_deployed_engineer
• A Day in the Life of a Palantir Forward Deployed Software Engineer: https://blog.palantir.com/a-day-in-the-life-of-a-palantir-forward-deployed-software-engineer-45ef2de257b1

Watch this episode on YouTube: https://www.youtube.com/watch?v=CxIBrEyJO-k

Links & mentions

• Kubernetes: Open source maintainership in the age of AI — https://www.kubernetes.dev/blog/2026/06/26/open-source-maintainership-in-the-age-of-ai/
• GitHub: Limit open PRs for users without write access — https://github.blog/changelog/2026-06-17-limit-open-pull-requests-for-users-without-write-access/
• Linux kernel coding assistants — https://docs.kernel.org/process/coding-assistants.html
• Vouch (Mitchell Hashimoto / Ghostty) — https://github.com/mitchellh/vouch
• Good Egg — https://github.com/2ndSetAI/good-egg

Watch this episode on YouTube: https://www.youtube.com/watch?v=oRGkEQvsIGo