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Hunger beats tenure: Advice for junior engineers
Felix Rieseberg, an engineering manager at Anthropic, explains why he has stopped giving coding interviews and argues that with AI, engineers without years of tenure or social capital can outpace more experienced peers; he offers practical advice on ownership, taste, empathy and principled thinking for junior engineers.
5 min · 1,233 words
“AI Skills” are worthless in 2026
Charles Miller argues that today's hard-won tricks for working with AI tools are like old C optimisation folklore: quickly made obsolete as the tools improve. Instead of rushing to master prompts and agent workflows now for fear of being left behind, he is content to keep pace with the pack.
2 min · 373 words
OpenAI and Anthropic Wanted to Replace Engineers. Instead, They Shot Their Own Customers.
Techbro Nerd argues that by selling AI coding agents, OpenAI and Anthropic let anyone clone established software, using Adobe versus the vibe-coded ArtCraft as the example, which erodes the enterprise software customers the labs depend on and drives the price of their own product toward zero.
6 min · 1,409 words
Freelance security consultant Lucas Luitjes digs into the public php2shell proof of concept and argues mass exploitation is far harder than vendors claimed: it needs four requests to the same PHP worker and the exact build, which means days of DoS-like brute forcing against real sites behind load balancers and WAFs. Patch fast, but the '15 minutes or die' hype was overblown.
3 min · 608 words
Personal software factories are a waste of time
Peter Piekarczyk argues that software engineers should stop building personal AI 'software factories' for side projects and instead spend their time experimenting with AI on real problems, the way non-developers are already doing in surprising ways.
3 min · 698 words
Does Ruby on Rails still make sense?
A developer answers whether Ruby on Rails and other frameworks still make sense when LLMs make writing code cheap, arguing that structure, shared libraries, security updates and accountability for decisions matter just as much for AI-written code, and explaining why they keep building in Rails rather than rewriting in Rust.
7 min · 1,509 words
It's still OK to enjoy programming
Chris Kiehl pushes back on the doom about AI and programming: work economics may have changed, but programming for fun on weekends, from a buggy Breakout clone to Agda-style type tricks in Java and recursion schemes, needs no economic justification, and the pressure not to enjoy it fades once you disconnect.
2 min · 472 words
Everything Is a Leaky Abstraction (in machine learning)
Elijah Potter, building on Andrej Karpathy's case for understanding backprop by hand, argues that unlike sealed abstractions such as TCP/IP, TLS or PostgreSQL, every part of a machine learning system leaks into the cost function, so practitioners should understand the whole model and training regimen before they start.
2 min · 402 words
More on Anthropic's Scion ripping off Mononoke
In a follow-up post, Rain (sunshowers) reports receiving private confirmation that Anthropic's Scion source-control system intentionally copied Meta's Mononoke, explains that the resemblance extends to the whole data model including Bonsai-style changesets, answers reader objections, and notes Anthropic later added attribution after responding on Hacker News.
5 min · 1,168 words
Anthropic’s Scion is heavily inspired by Mononoke
A former Mononoke engineer compares Anthropic's description of 'derived data' in its new Scion version control system with how Meta's open-source Mononoke source control server used the same idea years earlier, and argues that Anthropic should have credited Mononoke as prior art.
4 min · 855 words
AI Is a Tool. Using It Well Takes Skill.
A response to Rich Hickey's "'AI' is Not a Tool": automation and tool use can coexist, an LLM can be wielded by a human even by Hickey's own definition, and using it well requires skill, feedback, and judgment like any other tool.
2 min · 555 words
Can Ease of Creation Lead to Decrease in Quality & Value?
Gustavo Pezzi of Pikuma reflects on whether AI tools that make software and games trivially easy to produce will flood the market with cheap, generic work, drawing parallels with past shifts in other crafts and asking what will make people care about what you make.
11 min · 2,431 words
Where is all the new, good software?
Nate Meyvis lists candidate answers to the skeptic’s question—if AI coding is so powerful, why isn’t more great new software obvious—covering quieter quality gains, limited adoption, political bottlenecks, ephemeral and private tools, leisure capture, and AI sometimes reducing software use.
2 min · 511 words
I'm sorry, but you still have to think
Piotr Sarnacki examines DHH's AI-agent rewrites of Campfire Once from Rails into Rust, Elixir and Go, showing how unspecified prompts turn design trade-offs like backwards compatibility, latency versus throughput and crash behaviour into coin flips, and why benchmarks and reliability still require human critical thinking.
8 min · 1,742 words
What I've been seeing lately (in software)
A personal survey of software culture amid generative AI: normalizing pro-human discussion, exacting design and organizing, the job question, beautiful work, and a growing European push toward self-hosted and public-sector open source.
4 min · 848 words
Why Are Coding Agents So Dumb?
Michael Lynch argues that while LLMs keep getting better, the coding agents that drive them have barely improved since early 2025: he separates the model from the agent, catalogs the workflow gaps and bugs he still hits in Claude Code, Codex, OpenCode, Cline and Pi, and sketches what a better agent would do.
10 min · 2,316 words
David Heinemeier Hansson follows up his Rails World talk telling programmers to put down the pencils: coding agents are now good enough that writing most code by hand is no longer economically viable, AI is more like gaining capable new coworkers than another tool, and programmers who refuse to collaborate with agents are the ones who should worry.
2 min · 382 words
Jonas Schäfer argues that LLM quality has improved enough that “AI output is bad” no longer works as a blanket objection—quality arguments lost, so the harder fights are about labor, ecology, control, and what we still choose to do ourselves.
9 min · 2,037 words
Stanko, who works on HEY, agrees with DHH's Rails World keynote that programmers, like painters after the camera, must adapt to AI, describing how building HEY CLI and rewriting HEY in Rust with agents changed his workflow, and arguing that using AI well is a skill to practice.
6 min · 1,306 words
Quick thoughts on GitHub’s Sept 23 incident
Lorin Hochstein reads GitHub's terse write-up of its Sept 23 Azure Central US database incident and pulls out the multiple contributing factors hiding in it: planned maintenance, replica failover, and an under-capacity primary.
3 min · 696 words