Trust fosters responsibility
“Policy Without Tools Is Just Poetry” - AT Protocol
Juliet Shen from ROOST joins the show to talk through the Coop 1.0 release, what open-source trust and safety unlocks for new builders, and where AI actually belongs in moderation
Center for Open Science
At the Center for Open Science, our mission is to increase openness, integrity, and reproducibility of scholarly research. Promoting these practices within the research funding and publishing communities accelerates scientific progress
Trust & Safety Tycoon
Manage your team, set policies, make investments, and tackle the challenging world of Trust & Safety
The Missing Middle of Open Source
Why serious, maintainer-driven projects struggle to sustain themselves—and what it will take to fix it.
AI-assisted Reviewing is Necessary and Should be Open
Peer review is facing a death spiral. AI production tools are speeding it up. AI-assisted reviewing is necessary and should be open.
Dependency Cultures - Richard Feldman | SSW 2026
“They had no concept of a duty of care to their users.” – Unsung
A blog about software craft and quality
Now Hiring: Senior Open Source Maintainer
A rare opportunity to make a real impact in a fast-paced, high-visibility role.
Review the reviews
When I was actively contributing to the Go project, my primary feed was the code review email firehose. Issues, mailing lists, and Slack had low SNR. The finished commit history was better: it was finely polished work with some of the best written commit messages I have ever encountered. But it didn’t hold a candle to code reviews for operational learning. The commit history could tell you what got done and why, in impressive technical detail.
Does Code Cleanliness Affect Coding Agents? A Controlled Minimal-Pair Study
As autonomous coding agents see rapid adoption, their evaluation has primarily focused on task completion rates holding the target codebase fixed. This leaves a critical question unanswered: does the structural and stylistic quality, or ``cleanliness'' of the underlying code affect an agent's ability to navigate and modify it? To isolate the effect of code cleanliness from agent capability, we introduce an evaluation protocol built around minimal pairs: repositories that match on architecture, dependencies, and external behaviour, but differ on static-analysis rule violations and cognitive complexity. The pairs are constructed in both directions, by agent pipelines that either degrade a clean repository or clean a messy one. We author 33 tasks across six such pairs, evaluated through hidden tests at the application's public surface. Across 660 trials with Claude Code, code cleanliness does not change the agent's pass rate. However, it substantially alters the agent's operational footprint: agents working on cleaner code use 7 to 8% fewer tokens and reduce file revisitations by 34%. Our findings suggest that traditional maintainability principles remain highly relevant in the era of AI-driven development, shaping the computational cost and navigational efficiency of coding agents. Code cleanliness joins model choice, harness, and prompting as a factor that materially affects agent behaviours.
A GitHub Issue Title Compromised 4,000 Developer Machines
A prompt injection in a GitHub issue triggered a chain reaction that ended with 4,000 developers getting OpenClaw installed without consent. The attack composes well-understood vulnerabilities into something new: one AI tool bootstrapping another.
Reading Code Is Hard, and tips to improve - Trisha Gee
This week's video for Dave Farley's Continuous Delivery YouTube channel is me ranting about why reading code sucks, and offering some advice on how to improve. "Every programmer occasionally, when nobody’s home, turns off the lights, pours a glass of scotch, puts on some light German electronica, and opens up a file on their computer. ... Read more
The Arguments Against Open Source AI are Very Bad | Tom Bedor's Blog
The release of Kimi K3 has opened a fresh round of angst and confused discourse. There's a loud cohort of journalists, business leaders, and politicians arguing that open source AI is a dangerous threat. OpenAI's Dean Ball:
Identify trusted publishers for your research • Think. Check. Submit.
Tools and practical resources, aiming to educate researchers, promote integrity, and build trust in credible research and publications.
Tests Are The New Moat | Daniel Saewitz
As AI becomes better at cloning people's open source work, what ends up becoming most valuable are software contracts, tests, and API surface area. This clashes the incentives of clearly defining your commercialized open source software with protecting it.
