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LD got some Oracle vibes here. Pricing per CPU core or connection is never great for the user.
The ecosystem around Agentic Engineering is evolving in parallel with an accelerated race to ship new and more capable models while dealing with GPU capacity constraints. This mix of challenges in processes, tools, and infrastructure build…
I wrote down a few thoughts on teaching agentic engineering, how to meet users where they are on their learning journey, and how to scale teaching beyond individual coaching.
Happy to hear what approaches worked for you and where you see f…
GitHub is changing its data usage policy to opt-out required...
"From April 24 onward, interaction data—specifically inputs, outputs, code snippets, and associated context—from Copilot Free, Pro, and Pro+ users will be used to train and im…
pi-autoresearch makes it very easy to spin up optimization loops. The #llm will come up with hypotheses to try, apply changes, and run a verification routine to check for improvement against a defined metric. All changes are tracked in git…
cupcake is a policy enforcement layer for AI coding agents, allowing for local policy evaluation. It integrates with the tools via hooks and supports different activity events.
I took it for a spin to check if I can block prompts that woul…
I'm curious what's wrong with GH UX or tools. We get ~1 PR per week or two to zalando/tech-radar where folks open PRs against the fork instead of staying in their own land. Happened pre-LLM as well. Some are closed immediately, others not.…
Hunter, Skeptic, Arbiter trio as an example of debate-style prompting for scanning the codebase for vulnerability candidates: https://ocytko.net/posts/hunter-skeptic-arbiter-prompting/
It's fun reading the debate content, though the hard w…
#MCP sampling enables the server to make use of the #LLM that has recommended calling it. The protocol description has a safety warning, recommending human in the loop. Fun things can happen when this is ignored...
Here is a simple example…
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