Stop Reviewing Code. Start Proving It Works. My Take on AI in the Quality Process of Software.
Code review was supposed to be about rigor. It became a rubber stamp. AI review will not fix it. What fixes it is building systems that prove correctness. Continuous delivery, not ceremony.
Continuous delivery transforms quality assurance from a human gate to an automated, system-wide capability.
Build quality into the system, not into human review processes.
Quality is not inspected in; it is built into the pipeline through automated gates that verify correctness at every stage of the software development lifecycle.
Traditional human code review often functions as ceremony, providing comfort rather than rigorous defect detection, with most efforts directed at style or minor issues rather than semantic bugs.
Automated verification systems, powered by advanced AI, can consistently perform deep code analysis, identifying defects at a scale and speed unachievable by human review alone.
The shift from human review to automated gates transforms quality assurance into a continuous, data-driven process where every commit is validated, and the system itself becomes the authority on correctness.
Decide whether the AI line item is being audited or invested. The two require different organizations.
Continuous delivery transforms quality assurance from a human gate to an automated, system-wide capability.
Build quality into the system, not into human review processes.
Quality is not inspected in; it is built into the pipeline through automated gates that verify correctness at every stage of the software development lifecycle.
Traditional human code review often functions as ceremony, providing comfort rather than rigorous defect detection, with most efforts directed at style or minor issues rather than semantic bugs.
Automated verification systems, powered by advanced AI, can consistently perform deep code analysis, identifying defects at a scale and speed unachievable by human review alone.
The shift from human review to automated gates transforms quality assurance into a continuous, data-driven process where every commit is validated, and the system itself becomes the authority on correctness.
Decide whether the AI line item is being audited or invested. The two require different organizations.
After 20 years in software development, Norman is both a hands-on leader and defining the new age of AI SDLC for some of the biggest brands in the world — and exploring it with the builders. He writes here about things he is hearing and seeing. All posts are his personal points of view and do not reflect any employer or any customer he has ever had contact with.
The views and opinions expressed in this article are the author’s own and do not represent the positions of any employer, client, or affiliated organization.
