Trial caps sized for human attention break the moment a programmatic signup points an agent at the endpoint. A field guide to redesigning quotas, detection, and exhaustion UX for the population actually signing up.
When coding agents write faster than your dev server's watcher debounce, the HMR overlay becomes a self-exciting oscillator that the agent reads back into its own reasoning.
Coding agents ship code that compiles, tests pass, and reviewers approve — but uses idioms your codebase does not speak. Here is why, and what to do about the drift.
Coding agents accelerate diffs and decelerate cognition. The hidden cost is the engineer's mental model — and the practices that keep it alive.
Retiring a deterministic feature in favor of an agent silently hands the predecessor's SLO to a system that cannot meet it — and the gap shows up the morning your inference provider throttles.
Swap a 200ms search call for a 4-second agent loop and the latency budget does not vanish — it migrates from infrastructure to UX, and the team that does not catch the handoff ships a worse product with a better metric.
Coding agents confidently emit code that compiles against the wrong version of your dependencies. The model isn't hallucinating — it's remembering a library that no longer exists.
Multi-agent workflows with human approval queues recreate every classical deadlock condition. The cycle hides across two queues and two calendars until a customer notices.
When an agent posts a polite summary in the incident channel and the commander reads it as ownership, the escalation chain has quietly acquired a transition nobody wrote down. Patterns to close the gap.
Most incident templates have no row for what an AI agent inferred — so the action items chase a deterministic fix for a probabilistic failure, and the same outage class keeps recurring.
When an agent's prompt becomes the only authoritative description of a business process, you have shipped a runbook in the cloud that nobody can audit, version, or hand off.
Per-user context at the top of the system prompt is the silent way to triple your inference bill. Here is why the cliff is invisible until billing close, and how to defend the cache boundary in code, in review, and in CI.