The End of "One-Shot AI": Why Context Engineering Is Replacing Prompt Engineering
Most "prompt engineering" advice circulating today is already obsolete for anyone building production-grade AI. Granular phrasing matters for simple, …
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The Multi-Agent Memory Problem: Why Retrieval-Time Inference Breaks Down at Scale
Published by the Alchemyst AI engineering team. We built Alchemyst AI, the context layer described in this post. This is not a neutral third-party rev…
Load late, load little: just-in-time context for conversation history
Most agents drag their entire past into every turn. A better default: keep a thin index of what was said hot, and fetch only the few turns you actuall…
The README Was a Protocol. The Entrypoint Was Still Optional.
Glossary: terms used in this article 🔸 MICA (Memory Invocation & Context Archive) : A governance schema for AI context management. Defines how con…
Context Engineering: Building More Reliable LLM Systems in Production
Context Engineering: Building More Reliable LLM Systems in Production In LLM-based systems, performance is often driven less by model size and more by…
I built the same MVP twice. The autonomous agent wrote 4.6x more tests — none caught two stubbed core methods.
Side-post in the keppt build-in-public series — an interlude before the Phase 1 implementation write-up lands. While building Phase 1 of keppt , I ran…