Context Engineering: What Goes in the Context Window
Prompt engineering asks how to phrase a request. Context engineering asks what the agent needs to know. Here's the budget I run across 30+ production agents
Prompt engineering asks how to phrase a request. Context engineering asks what the agent needs to know. Here's the budget I run across 30+ production agents
A practitioner's buyer's guide to AI agents for small business — the three real tiers (off-the-shelf, DIY, custom), a 5-point rubric for evaluating any tool
Context engineering is the discipline that replaced prompt engineering for serious agent work. Here's how I structure context windows across 30+ production…
Updated for 2026. The decision framework I use to decide when a production AI agent needs a human approval step — and when adding one silently kills adoption.
How to use cache_control to cut Claude API input costs by up to 90% on agents with large stable prompts — the prefix-match invariant, what to cache
The framework I use to decide whether an AI automation is actually worth building — quantified manual cost, build cost, run cost, maintenance tax
The exact playbook I use to automate a real small business with AI agents — from the $5/month Cloudflare stack to the tasks that actually pay off.
Updated for 2026. The cost math I use to pick Claude Haiku vs Sonnet per task — token economics, the routing rule, and where cheap models quietly cost more.
Updated for 2026. The exact playbook I use to debug AI agents running live — trace every step, isolate the failing layer, and reproduce non-determinism fast.
Updated for 2026. The orchestration patterns I use to run multi-agent systems — durable queues, externalized state, and clean handoffs that survive retries.
Updated for 2026. The eval harness I use to ship AI agents — a graded test set, an LLM judge, and a regression gate so a prompt change can't break prod.