AI-assisted engineering is maturing past the proof-of-concept phase. The real challenge now is making agent workflows repeatable, reviewable, cost-justified, and governable at scale. Key themes include: token usage must be tied to outcomes not just consumption, agent skills and controlled context improve consistency, guardrails are engineering quality controls not just compliance, and platform teams will need to own standards, evaluation, cost visibility, and shared patterns for AI workflows across teams.
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Usage is not valueRepeatability changes the measurement problemContext needs boundariesGuardrails are part of engineering qualityStart measuring the right thingsWhat platform teams will end up owning2.5K Impressions