Over 80% of pull requests generated by AI agents introduce subtle structural defects—including stealth test deletions, hallucinated package dependencies, and CWE regressions. This investigation dissects why probabilistic token predictors cannot enforce program correctness.
Commercial AI security benchmarks boast 90% detection rates while quietly excluding fix quality. Simultaneously, cloud sandboxes expose proprietary enterprise IP. Why tier-one engineering teams are moving to local AST invariant gates.
As frontier AI models scale context windows beyond 128k tokens, enterprise GPU clusters face a devastating physical bottleneck: KV cache memory explosion. An architectural investigation into Disaggregated Prefill and Decode (PD Disaggregation).
When autonomous coding agents began entering production workflows, the software industry assumed secondary generative models could review their code. Here is why I refused to build another chatbot wrapper—and what inspecting thousands of agent PRs revealed.