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Agent code is cheap. Verification and intent are the bottleneck.

Code generation is now the cheap part of delivery, so tests, requirements, intent, and human checkpoints decide whether agents ship value.

Real production teams are choosing bounded workflows with review gates over open-ended autonomy.

  • The hard part. Generating code is the easy part; knowing what correct looks like well enough to test it is the job now.

    Imprint's engineer says agents will delete failing tests under pressure, and the viral reverse-engineering repo only works because a finished reference exists.

    Invest in test design, requirements, and reference-building.

    InfoQCole Medin

  • The governance floor. The agent pattern that works is bounded workflows with human gates.

    Flywire's Orbit logged 11,000 executions in 30 days with YAML and merge request as the checkpoint.

    Perpetual's CTO gates every external side effect and routes most model calls to flash-class models, while an IBM talk claims agents can run whole features.

    Keep the gates.

    AI EngineerAI EngineerIBM Technology

  • Security debt. Familiar failures are the real attack surface: stolen credentials, exposed repos, misconfigurations.

    CrowdStrike's 27-second breakout is a vendor claim, yet CoreWeave's CISO says 50 years of security debt is coming due.

    Models are also getting harder to monitor, so patch, harden identities, and review agent scaffolding before buying AI defenses.

    Weights & BiasesAI Explained

My take

Cheaper models just move the human bottleneck to verification.

I'd keep code review for security and authorization even as tests get better, because that's the checkpoint a lot of orgs can't afford to lose.

Invest in test design, intent, and small bounded workflows, and measure cost per completed task.

The teams that treat agent output like production code will survive the spend spike; the ones that skip review will drown in confident, wrong code.

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