Backend Engineering11 min read
Which language should you build Redis in?
Honest comparison of building a Redis clone in Python, Go, Node, Rust, Ruby, and Elixir: concurrency, idioms, throughput, and where each language wins.
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136 posts in total
LLM Engineering9 min read
Query anonymization for RAG bias mitigation
How to strip names, roles, and demographics from queries before retrieval to reduce RAG bias. The redaction pipeline and the 3 leakage traps to avoid.
AI Engineering in Practice9 min read
pip vs uv vs poetry for Python AI services
Which Python dependency manager for production agent services? Install speed, lockfiles, and Docker build times of pip, uv, and poetry compared.
AI Engineering in Practice8 min read
Retry patterns for LLM API errors in production
How to build retry logic that handles rate limits, timeouts, and transient failures without burning money. The backoff rules and the 3 errors you must not retry.
LLM Engineering8 min read
Choosing the LLM judge for evaluation pipelines
How to pick the LLM that grades your LLM. The cost-quality tradeoffs, the calibration check, and why a weaker judge is sometimes the right call.
LLM Engineering9 min read
Ground truth vs relevancy in RAG evaluation
Why ground truth and relevancy measure different things in RAG evals. When to use each, how to build both datasets, and the 2 metrics that matter most.
LLM Engineering8 min read
Pydantic output structuring for RAG agent plans
How to use Pydantic models to force your RAG planner LLM to return structured steps. The schema, the retry loop, and why plain JSON prompts break in production.
LLM Engineering8 min read
Hallucination testing for RAG pipelines
How to test a RAG pipeline for hallucinations systematically. Adversarial prompts, the out-of-scope set, and the metric that catches confabulation.
LLM Engineering8 min read
Testing and evaluating RAG pipelines end to end
How to test a RAG pipeline like real software. Unit, integration, and eval tests that catch regressions before they ship. The 3-layer test strategy.
LLM Engineering8 min read
Fact-checking RAG answers: grounding with verification
How to fact-check RAG answers with a second LLM pass that verifies every claim against the retrieved context. The prompt, the rejection rule, and the loop.
LLM Engineering8 min read
Query rewriting in RAG with LLMs: the rewrite loop
How LLM-powered query rewriting fixes vague user questions before retrieval. The prompt, the multi-query fan-out, and when rewriting hurts more than helps.
LLM Engineering8 min read
LLM-based content filtering for RAG pipelines
How to filter irrelevant retrieved chunks with a cheap LLM call before the final answer. The prompt, the batch pattern, and the 40 percent noise reduction.
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