Your Agent Keeps Asking the Same Question It Already Answered Last Session
You finish a long session with Claude Code. You made three real decisions: which auth flow to keep, why the cache key must include the tenant id, an…
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Once I wrote in the MCP tool description when to use the tool, AI agents called it
Summary I built an MCP tool that assigns multiple independent tasks to subagents and has the subagents execute them in parallel. Below, I call this…
Context engineering: what fits and what gets dropped
Originally published on Loop & Retry — field notes on building LLM agents that survive production. "Context engineering" showed up this year as…
Context Window Management for Long-Running AI Agents: 4 Patterns That Work
Originally published on robatdasorvi.com The agent had been running for four hours and it was arguing with itself about a file it had already fixed.…
Multi-agent work in three spoonfuls: what worked for me and what did not
This started as a practical annoyance: long tasks interrupted by quota limits, conversations that became too heavy, and reviews that required copyin…
I stopped writing prompts. I write the repo.
Originally published on indiecore.net . For about a year I got better at asking. Longer prompts, worked examples, careful phrasing, a private collec…
The Glass Box: Inside OpenAI's Computer History & Agentic AI
🎙️ Short on time? Explore the 10-Min Interactive Visual Deck first ➔ Every major breakthrough in software automation begins by removing a layer of h…
OpenCode Needs Memory, Not Another Background Pipeline
I kept explaining the same project facts to new OpenCode sessions. Not the durable rules that already belonged in AGENTS.md . Those were present. Th…
One bad step, N bad steps: how agent failures cascade
Originally published on Loop & Retry — field notes on building LLM agents that survive production. Here's the failure mode that surprises people…
Context window sizing for fine-tuning: how long should your training examples be?
Originally published on Loop & Retry — field notes on building LLM agents that survive production. Most fine-tuning guides answer "how many exam…
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…
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 r…
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 actua…
The Website Is Not the Product
TL;DR Anthropic's crawler now retrieves 60,000 pages per visitor sent back — up from 6,000:1 six months ago. The website as distribution channel is…
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 c…
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…
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 r…