The Context Window Is Not a Filing Cabinet Here is what most teams do with the context window: they fill it up. Every prior message, every retrieved document, every system prompt update, every intermediate result piled in until either the model complains about length or performance degrades enough that someone

Your Multi-Agent System Has a Coordination Problem Single-agent systems have one set of problems. Multi-agent systems have all of those plus a new category: the problems that arise at the boundaries between agents. Who tells whom what to do. How agents share state without corrupting each other&

You Can't Improve What You Can't Measure — Agentic Evaluation Done Right Most teams know their agent's average quality in the same way they know their own health without a doctor: by how it feels. The code usually looks right. The summaries are usually reasonable.

If You Can't Reconstruct What the Agent Did, You Don't Have a System The standard for understanding what happened in a software system is the audit log. In regulated industries it's a compliance requirement. In any production system, it's what you reach

How to Stop an Agent That's Gone Wrong The question is not whether your agents will go wrong. They will. Every team that runs agents in production eventually faces a session that's headed somewhere it shouldn't be. The question is what you can do

The Error Your Stack Trace Will Never Catch Software engineers are trained to think about errors in terms of exceptions. The process threw. The API returned a 500. The database connection timed out. These are the errors that interrupt execution and produce a log entry. They are also the easiest

Agentic Systems That Don't Improve Are Just Expensive Software The pitch for agentic AI is that it compounds. You invest in building a system, the system gets better over time, and the return on that investment grows without proportional additional effort. That pitch is true, but only for

Why Your Agent Forgets Everything Every Morning The most common complaint I hear from teams that have deployed agents into real workflows: "it keeps making the same mistakes." They've seen the failure mode. They've told the agent about it. They've watched it

The Orchestration Model You Pick Is the Architecture Decision You Can't Undo Teams tend to pick an orchestration framework the way they pick a JavaScript framework: whatever the first engineer already knew, or whatever had the best tutorial. Three months later, they're fighting the architectural constraints

The Defect Is in the Definition Every software team knows the cost of finding a defect late. The multiplier varies depending on where in the SDLC you catch it, somewhere between 10x and 100x, but the direction is always the same: the later the find, the worse the math. In

The Plan Is a First-Class Artifact Ask most engineers how their agent decides what to do next and they'll say "it reasons through it." That's true as far as it goes, and it's precisely the problem. Reasoning through it is not

Agentic Development Is Eleven Problems, Not One Most agent projects fail at the same place and for the same reason. A team picked up one tool, pointed it at a problem, and discovered six months later that the tool only solved one of the eleven things standing between them and