The original title is "We let AI write the code. We just don't let it check its own work."

Short summary

AI engineering bridges the gap from 'AI-produced code' to 'production-ready software.' The author shares four core rules: define success upfront and verify independently, ensure humans understand necessary changes, calibrate verification rigor by consequence not speed, and never let AI verify itself—combine human review with a different AI model. The real advantage is speed at turning new AI tools into shipped deliverables.

• •The core challenge is moving from AI-generated code to production-grade code you'll stake your reputation on
• •Effective rules: independent verification, human informedness checks, and layered review (human + different model)
• •Never let the same AI model verify its own work—use independent human judgment plus a different LLM

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