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Small prompt changes can silently break critical behavior in production. This article introduces a practical…
17 min read -
I benchmarked raw chat history, vector-only RAG, and a context graph on the same multi-agent…
19 min read -
LLM rate limits don’t just interrupt agent pipelines—they can silently corrupt structured outputs when fallback…
16 min read -
Increasing context size in RAG systems doesn’t improve accuracy for aggregation tasks—it makes errors harder…
15 min read -
I got tired of copying files into an AI chat just to get feedback. So…
17 min read -
Most RAG systems are optimized for answer quality, not cost—and that blind spot gets expensive…
22 min read -
Prompt Engineering Isn’t Enough — I Built a Control Layer That Works in Production
Large Language ModelMost LLM failures in production aren’t random — they’re predictable. I kept hitting broken JSON,…
23 min read -
LLM Evals Are Based on Vibes — I Built the Missing Layer That Decides What Ships
Large Language ModelMost LLM evaluation systems rely on vague scoring and human judgment disguised as metrics. I…
24 min read -
Three weeks into testing, a learner told me my AI tutor gave her the wrong…
24 min read -
Your RAG system isn’t failing at retrieval — it’s failing at reasoning. This article shows…
25 min read
