If you use AI for coding every day, you may have noticed something strange: Your AI coding assistant gets dumber the longer you talk to it.
Most developers feel it but can’t name it: you start a chat, it’s brilliant. An hour later — same model, same task — it’s forgetting your instructions and repeating bugs it already fixed. You blame yourself. Don’t.
Matt Pocock calls it the smart zone and the dumb zone. A model is sharp early in a session, then quality slips well before the chat feels “full.” And here’s the surprising part: those huge new context windows everyone is talking about? They don’t give you more smart zone. They just give you a bigger dumb zone.
(Technically: a model’s effective context length is much shorter than its advertised window. As the thread grows, attention spreads thinner across more tokens, mid-context detail gets underweighted — “lost in the middle” — and the model keeps conditioning on its own earlier mistakes still sitting in the history.)
So the fix isn’t a better prompt. It’s a shorter memory. One task. One conversation. Then start fresh.
For larger work, move the memory outside the conversation: define the destination in a a shared specification, break the journey into small independent tasks, and give each task a clean context. The goal isn’t to give the AI everything it could possibly know. It’s to give it exactly what it needs for the task in front of it.
Your assistant was never getting tired. It was getting full.
Highly recommend Matt Pocock’s “Full Walkthrough: Workflow for AI Coding.” I learned a lot from this workshop.
Source:
Matt Pocock’s “Full Walkthrough: Workflow for AI Coding” (AI Engineer). The smart zone / dumb zone section is worth the watch if you use an AI assistant daily: Link
One practical tip from it: keep a token counter visible in your setup, and clear the chat when a task is done rather than stacking the next one on top. A fresh session beats a smart prompt.
Excerpt:
Every breath, the world is made new — and we, unaware of our renewal, endure.
Rumi, Masnavi
