Originally published on AI Tech Connect.
What breaks, and why it keeps breaking The failure has a recognisable shape. An agent that has run in production for months starts returning 400s the week a new model version is switched on. Or, far worse, it keeps working — and quietly gets less coherent on the long, tool-heavy tasks that were the reason you built it. Nothing in the agent's own logic changed. What changed is that the model now enforces a rule about how its own reasoning is carried between turns, and the integration has been breaking that rule for months without ever being told. The rule exists because reasoning became state. When a model thinks before it answers, that thinking is not decoration; it is working memory for the rest of the task. Providers could have returned it as readable text and let you decide what to do…
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