Technology

When coding agents produce pull requests faster than a team can review them, the problem is not simply that reviewers need to work faster. The deeper problem is that review is being asked to answer questions that should have been settled earlier:

Agentic coding goes beyond AI autocomplete: AI agents plan, execute, test, and iterate across multi-step software tasks. This CTO guide explains how it works, the benefits and risks, how to measure its impact with DORA metrics, and how to adopt it safely through clear context, human review, security controls, and accountable release gates.

In the modern software landscape, raw model intelligence is no longer the sole bottleneck. While Large Language Models (LLMs) and autonomous agents possess remarkable reasoning capabilities, placing an unconstrained model directly into production environments often leads to non-deterministic behavior, context drift, and unreliable outputs.