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Six AI-assisted engineering projects showed that faster code shifts the real bottleneck to specs, context, review, and ownership.
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We ran an AI-assisted engineering contest across six fintech projects. The strongest pattern was not just faster coding, although teams reported 2x–20x acceleration in different parts of the work. The bigger shift was that once implementation became faster, the bottleneck moved into specs, context, review, architecture, handoffs, and ownership. AI helped teams reach working artifacts much earlier, but the hardest decisions still required human judgment.