From AI Assistants to AI Coworkers [Testμ 2026]

Nilesh Dalvi of Glean argues that AI coding tools can significantly accelerate code creation but have limited effect on overall delivery velocity because coding represents only about 20 percent of engineering work; making it five times faster reduces a 100-hour cycle to roughly 84 hours. The larger opportunity lies in the surrounding work of deciding what to build, verifying changes, deploying safely, monitoring production, and learning from outcomes, which requires AI to operate as a “coworker” rather than merely an assistant. This shift depends on making organizational context accessible across systems, exposing tools through programmatic interfaces, triggering workflows from events such as escalations or failed evaluations instead of manual prompts, and applying judgment about whether to act, ask for help, stop, escalate, or roll back. Dalvi emphasizes gradual, risk-based autonomy supported by clear permissions, evidence, metrics, guardrails, and rollback mechanisms, while treating human edits, rejected changes, and reversions as valuable feedback that improves the system over time.

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