This case study shows how to implement a HIPAA-compliant CI/CD pipeline using Cosign for artifact signing, OPA Gatekeeper for admission control on EKS, and long-term evidence storage in S3
➤ ku.bz/TYS0yf264
Update on my project to use AI to code up a video editor to replace Premiere: I jettisoned the concept of using PHP/SQL/FFMPEG as the platform for it, and instead switched to Python. So far progress is proceeding at a decent clip and I *think* I see light at the end of the
Top 10 Hermes skills ranked by Github stars thanks to reddit thread.
github.com/obra/superpowe… - An agentic skills framework & software development methodology that works.
github.com/DietrichGebert… - Makes your AI agent think like the laziest senior dev in the room. The best code
Local AI tip: if you've got a big-memory Mac, you can run frontier open models at home now.
antirez, the creator of Redis, built ds4, a lean C engine that runs a few top open models on your own machine.
the setup:
* models → DeepSeek V4 Flash, GLM 5.x and Qwen 3.8 Flash Next
MiaAI_lab blocked me, and I'm not the only one. I'm not here for drama. I spent today checking everything I'd heard against git history, commits and posts, and threw out whatever didn't hold up. This is what did.
Mia holds others to a strict credit standard, but not always Mia's own repos.
Mia asked another dev to add a banner at the top of their README crediting Mia, even though their NOTICE and credits section already did. Mia also sent a fork a PR quoting MIT's notice clause. Fair. Credit matters...right? Here we go:
Now look at Mia's own repos:
• The GLM-5.3 EXL3 recipe started as Chris Scott's code. His commit is the very first one. The credits list names a dozen people. Not him.
• 18 of tonyd2wild's files went in byte-for-byte in a single commit, so his name isn't in the history. The credits say his work "informed" the defaults. Tony has said publicly he caught Mia copying his repos without credit. Mia replied by posting his private DMs.
• The day after Brandon Music published his GLM quant, the recipe switched to pulling a byte-identical copy from Mia's own Hugging Face. The mirror page credited him. The recipe people actually run names him on line 232 of 243.
• The flagship 1x spark Qwen recipe, the one I run every day, pulled weights from Mia's mirror too. The actual creator is first named on line 1,350 of a roughly 1,400-line README.
And it's not that Mia doesn't know how. The dual-Spark Qwen recipe names its base on line 15 and pulls weights straight from the original creator. So it's a choice, made repo by repo.
Community PRs are fine, git keeps those names. This is different: projects that started as someone else's work, files imported so the author disappears from history, and models re-hosted so the downloads land on your name.
That's not the spirit of open source. Credit is how the person who spent a weekend on a patch gets noticed, gets hired, and keeps building. When their name sits on line 1,350 and the downloads go somewhere else, the next person doesn't bother sharing. And when you publish recipes people run 24/7, the replies are where bugs get found. Blocking questions breaks the loop that makes local AI good.
No one's asking for much: name the people at the top, hold yourself to the standard you ask of others, and don't block people for a simple question or a little criticism. I mean... It's X.
If I got something wrong, show me and I'll stand corrected. Receipts below, all public.
Still building in the open, and still rooting for local AI to get this right.
Gitea, an open-source Git host, has a runner bug: workflow files can pass Docker flags that breach container isolation and steal host secrets. Keys in env vars are trivially grabbed. Keep them vault-side; a compromised agent finds nothing. @TheHackersNews@LakeraAI
Building with AI agents has been a norm and that's a future. So everyone now knows that making repo agents friendly is a key. But don't just make it "friendly" for a particular AI agent. As engineers in your team might be using different tools (codex, claude code, cursor, etc)
Finally, ComfyUI github stars surpassed gstack. @garrytan and @ycombinator did what we took us 3 years in half. But curious what user retention for gstack is thou : )
Agent workloads change where infrastructure bottlenecks show up. A model call might be compute-heavy, but an agent spends time across a much broader execution path. eg, reading files, calling APIs, executing code, writing state.
This matters bc model latency can become only one
25,000 GitHub stars used to mean a project had arrived.
Today, you can buy that on Telegram for $200.
I mapped the 7 architectural layers of the 2026 agent stack and the due diligence signals to check before betting your codebase on a trending repo. x.com/i/article/2105…
Hello gm builders
AI agents are getting smarter, but one question still matters:
How do you know which agent deserves access to capital?
That’s where @agenticscredit gets interesting.
Agentics Credit is building credit infrastructure for Agentic Finance, with an Agentic
2026 software engineer starter pack:
-IDE
-GitHub
-ChatGPT / Claude
-Copilot
-Slack
-47 browser tabs
-One production incident
-One meeting that could've been an email
We're not writing less code.
We're just creating bugs faster. 💀
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