Two years ago, the highest-leverage skill on an AI project was finding the exact phrasing that made a model behave. That era is largely over. Modern models are forgiving enough about wording that clever prompt tricks buy you very little anymore. What actually determines whether an agent works reliably is what information it sees at the moment it needs to make a decision.

What "context engineering" actually means

It's the discipline of deciding, for every step an agent takes, exactly what data, history, tool results, and constraints get placed in front of the model — and just as importantly, what gets left out. Too little context and the agent guesses. Too much and the signal drowns in noise, and cost and latency climb for nothing.

Where teams get this wrong

  • Dumping the whole database into the prompt. More context is not more accuracy. It's usually the opposite once you cross a relevance threshold.
  • Static context that never updates. An agent working a multi-step task needs its context refreshed after every tool call, reflecting the new state of the world — not the state it started with.
  • No memory boundary. Long-running agents need a clear policy for what persists across steps and what gets summarized or dropped, or the context window fills with stale information.

How we approach it in production systems

We treat context as a designed artifact, not an afterthought. For every agent we build, we define: the minimum data required to make this specific decision, where it comes from, how fresh it needs to be, and how it gets trimmed as the task progresses. That design work happens before we write a single instruction to the model.

The model was never the bottleneck. The information pipeline feeding it was.

The practical upside

Teams that shift their effort from prompt wording to context design see fewer hallucinations, not because the model got smarter, but because it stopped being asked to fill gaps with guesses. That's the whole trick — give the model exactly what it needs to know, and it rarely needs to invent the rest.