Tag
python
Giving an AI Agent a Memory: Patterns, Storage, and What to Forget
Build a practical memory layer for an AI agent, choose where each kind of memory lives, and design retrieval and forgetting that you can trust.
Data Quality Gates with Great Expectations: Expectations, Checkpoints, and CI
Build a working data quality gate with Great Expectations: define an Expectation Suite, run it as a Checkpoint, store the results, and fail CI on bad data.
Multi-Stage Docker Builds for Node and Python: Smaller Images, Fewer Surprises
Learn multi-stage Docker builds for Node and Python with cache mounts, slim runtime images, non-root users, and digest pinning to cut bloat and build risk.
Cache LLM Responses Without Serving Stale Answers
Design an LLM response cache that actually saves money: exact-match keys, versioned prompts, tenant isolation, and the strict rules for when semantic caching is safe.
Evaluate a RAG Pipeline Before Your Users Do
Build a repeatable evaluation harness for your retrieval-augmented generation pipeline: golden datasets, retrieval metrics, faithfulness checks, and CI gates.
Structured Outputs from LLM APIs: Schemas, Retries, and the Failure Modes Nobody Documents
Get reliably typed data out of LLM APIs: strict schemas, parser-backed validation, retry loops that fix errors, and the failure modes that survive all three.
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