chtefi
Streamhouse: A shared data architecture for the age of AI
Théâtrophone: Proto-Spotify, 140 years ago
Chrome-agent: LLM-native browser automation tool written in Rust
Testing a Kafka Proxy: Taming Millions of Permutations
Loop Engineering: When Generation Gets Cheap, Judgment Gets Expensive
How to Tell If Your Kafka Self-Service Is Working?
MCP is definitely not dead
What do you think, what have you saw in terms of usage/adoption/issues?
Kafka Partitions are the wrong ordering abstraction. Keys are
Useful to debug local Kafka apps against any cluster, intercepts the traffic, decodes the protocol. You see interesting (and weird) things when you look at the protocol. Still early, though already useful for local debugging when you know what you want.
Most agent reliability problems are data engineering problems
Unified macOS service console for launchd and Homebrew
Agents Are Microservices with a Brain
Do LLMs Dream? The Post-Transformers Generation
Is Anthropic Enshittifying their core product?
Stream your terminal. Watch AI agents work. Like Twitch, for shells
$200 subscription VS $3,650 in compute
Kafka Explorer – Configuration, Protocol, Wire Format, Errors, Flink SQL
Paper Cuts #2: RAG is dead, long live memory
Decisions, extracted knowledge, handoff context: reasoning data infrastructure
How to stop your AI agent from gaming its own KPI
- Make the validator read-only for the agent. Mount it as read-only in the container, or hash your eval scripts at startup and verify before each run. If the agent can write to anything in its evaluation path, it can (will) game it.
- Log the full trajectory, not just the output. Every tool call, file diff, reasoning step. Then run a second agent over the trace with no knowledge of the KPI: it only knows what honest execution looks like and will use its internal honest alignment to assess it.
- Write system prompts like job descriptions, not optimization targets. Name a reviewer. Give the agent permission to fail ("if you can't hit the target, explain why").
- Walk your own prompts: what's the metric, what can the agent write, and can it reach the metric by modifying the measurement instead of doing the work? If yes, close that path.