If you've spent time building with LLMs, you've hit this wall: you get your agent or workflow...
If you've spent time building with LLMs, you've hit this wall: you get your agent or workflow running, the outputs are decent, and then... they stay decent. Six months later, the same prompts produce roughly the same quality. The model hasn't gotten worse. The workflow hasn't improved.
The reason is almost always the same: you're missing Phase 4.
The pattern most AI workflows skip
Here's the loop most developers run without naming it:
Write a system prompt and user prompt (Brief)
Each week I see a new “autonomous agent” demo in my feed, and each week it seems to be the same...
TL;DR: Half the "AI agents" in production are expensive, fragile reimplementations of workflows. If...
The complete guide to the new loop engineering trend. Write powerful agentic loops while avoiding loopmaxxing.
We have all hit the "monolithic LLM wall." You design an incredibly capable AI agent, arm it with a...
akm improve runs a multi-phase pipeline — reflect, distill, consolidate, memory inference, graph extraction — that continuously…
If you have built an AI agent recently, chances are your codebase started with a simple, elegant...
