Notes from a CTO who has to put agents into production. Every post says what I ran, what it cost, and whether I'd use it.
OpenSSH releases now come faster because AI finds the bugs. I counted the gaps, diffed the 10.6p2 fix and wrote the checks a small team can run today.
Claude Code privacy in practice: the account email sat in the model's context. I pointed opencode and Codex at a request logger and read what they send.
DeepSeek V4 Flash in 56.56 GiB on a CPU, no GPU, says llama-modchip. I redid the size sum, checked the comparison file, and say what it's good for.
My AI team structure for a startup: four seats, who owns the eval, and the numbers from my own pipeline, including what broke.
Local LLM hardware requirements for Ripple-65B, a 65B dense Apache 2.0 model: file sizes, KV cache and a speed ceiling per machine. I did the maths.
The DeepSeek coding agent is MIT open source. I installed it in 8 seconds, ran 1,197 tests, and found one prompt rule worth stealing.
Graph engineering models an agent system as nodes and edges, not a prompt chain. Here is the idea, five patterns, and how my open-source Yaaf uses it.
I measured the MCP context cost of 22 server setups. One eBay server takes 40.6% of a 200k window if your client loads every tool. Here is what to keep.
I ran PaperPilot, a local PDF MCP server with 76 tools, on fake invoices. Its redact tool leaves the card number in the file. Here is the test.
