When a company rewards developers for the number of pull requests they open, artificial intelligence (AI) agents can produce those pull requests almost for free. This post explains why counting output was always a weak way to measure software work, why agents make it actively harmful, and which measures still tell you something true.
Imagine a team where artificial intelligence (AI) agents write most of the code, and then imagine it ten or a hundred times bigger. Writing code stops being the slow part. This post walks through the stages that become slow instead, from reviewing pull requests to talking to other systems, and proposes the best fix for each one.
Ontologies are popular again, mostly because of artificial intelligence (AI) agents. A developer who knows Domain-Driven Design will find much of the idea familiar. This post covers what the two share, where they differ, and why the interesting work now is letting AI programs use your existing business model safely.
In 2026, Anthropic's artificial intelligence (AI) agents began to merge more than 30,000 code changes a day into one repository, and git could no longer keep up. So Anthropic built its own source control system, Scion. Here is the problem it solves, how it works, and what it means for teams that will keep using git.