Most AI Revenue Leakage Isn't Fraud. It's Engineering.

<blockquote> <p>Your best feature may be destroying your margins, and your engineering team has no idea.</p> </blockquote> <p><strong>This article isn’t about AI as a productivity

<p>If you're running an AI agency, you're probably building some<br /> variation of RAG or agentic workflows for your clients.</p> <p>You deliver the project, it works great, and

<p><em>This is a submission for the <a href="https://dev.to/challenges/google-gemma-2026-05-06">Gemma 4 Challenge: Write About Gemma 4</a></em></p> <h3> Why I Wrote This </h3>

<p>The organization runs the program. Reserved instances purchased, rightsizing applied, maybe a workload consolidation push across three regions. Spend drops 18%. Leadership

<p>Snap just announced that AI agents generate over 65% of their new code. The same week, they laid off roughly 1,000 employees — 16% of their workforce. CEO Evan Spiegel shared

<p>I kept seeing the same pattern in my own work. The bill was never the first problem. The first problem was that I did not know what I was spending while I was spending it.</p>

<p>I opened an AI invoice recently and felt the stomach drop that every solo developer knows too well.</p> <p>It was not a catastrophic number. It was worse than that. It was a

<p>80% of engineering teams miss their AI infrastructure cost forecasts by more than 25% — not because they're spending wrong, but because they're managing three fundamentally