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Every engineering leader is running the same experiment right now, whether they admit it or not. Developers are already using AI. The only open question is whether leadership knows about it, controls it, and gets value from it, or whether it is happening in the shadows, unmeasured and unmanaged.
The data says most organizations are in the second category.
Every vendor pitch in 2026 leads with AI. Every RFP response mentions “AI-powered maintenance.” Almost none of them tell you where AI actually saves money and where it quietly adds risk you will pay for later.
If you are a CTO evaluating whether to bring AI into your
You are about to write a check. Invest in a startup, acquire a SaaS company, fund a healthtech platform, or bring on a technology vendor that will run a core part of your business. The financials look clean. The pitch deck is polished. The founder is convincing.
None of that tells you whether the codebase will survive its next 10,000 users, whether the “proprietary AI ...
Your engineers are shipping code faster than ever. Claude Code, AWS Kiro, Hermes Agent, Copilot, whatever the flavor, developers are individually more productive than they were eighteen months ago. Velocity metrics on paper look good. Story points per sprint are up. Commit counts are up.
So why isn’t the business actually moving faster?
This is the uncomfortable...
AI slop is low-quality, unreviewed AI-generated output that looks correct on the surface but carries hidden defects, security gaps, and long-term maintenance costs. In software engineering specifically, AI slop is what accumulates when engineering teams generate code faster than they can responsibly review it, and review starts happening in name only. For enterprise business ...