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Why a Free 30M-Token AI Allowance Can Create More Work Than It Saves

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A large free token allowance from an AI coding tool can feel like unlimited capacity, but the real bottleneck is human review, not model output. Developers risk accumulating unreviewed AI-generated changes faster than any team can responsibly inspect them, turning a free trial into a hidden backlog. A pre-mortem exercise — imagining project failure before work begins — helps teams identify these workflow risks early. The approach involves mapping plausible failure modes, defining pass and stop conditions, and running small test prompts on a disposable sandbox server. Scoring each risk on a simple scale ensures that uncontrolled failure modes trigger a pause before they reach production code.

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Why a Free 30M-Token AI Allowance Can Create More Work Than It Saves · ShortSingh