Faros AI’s new report and the article’s proposed “decision review” approach say AI reviews are increasingly merging PRs without human line-by-line review, while the human debate over what was decided and why is still missing. The report found a 76.3% increase in pull requests merged without review since the prior April report, and the article adds that many companies already run AI reviews on 50% to 80% of PRs. Review shifts from checking code lines to recording intent, acceptance criteria, and debated decisions (with humans owning unresolved trade-offs), so teams retain accountability and shared context without reading every line of AI-written code.
People have been using AI to reverse-engineer and rewrite software on smart TVs and other internet-of-things devices, including reviving bricked hardware and removing ads or bloat. The GitHub project “Reverse Engineer Anything” went viral over the weekend and reached more than 342,000 stars. As a result, software features are being cloned faster but often with bugs, raising the risk of low-quality, poorly vetted software spreading through communities and onto physical devices.
A code review system’s average review cost rose from about $1.19 (April) to about $2.46 (end of August), then dropped after mid-September token-usage and caching optimizations. The average review cost fell to $0.77 (down 68%) after changes that also reduced median review time to 1m 32s from 4m 09s. The work shifted spending away from repeated context by improving prompt caching and reducing the number of LLM calls, plus adjusting models and reviewer “effort” levels.
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