10 stories
Factory electrification reshaped production only after owners redesigned the floor. AI software teams need the same shift in workflow, review, and verification.
Software factories need speed & quality. Ship fewer bugs by testing in layers; fast tests first, then deeper validation
AI model routing and evaluation now decide your production results. Learn how companies are adapting to make the most of the highly competitive LLM landscape.
AI tools produce 41% more bugs and 98% more pull requests. MTTR can't keep up. Here's how MTTF shifts your team from incident response to prevention.
Tokens per second measures how fast a model emits, not how fast it finishes. Our 13-model probe shows the gap that flips both the speed + cost leaderboards.
git worktree isolates your files. Moo isolates the database, ports, and services, saved per commit. Together, they give your agents fully isolated machines. Learn how to use Moo, the benefits, and why your agents need it.
Ito moved production QA agents from GPT-5.3-codex to open-weights. Here's what we saved, why inference providers matter as much as models, and what to check.
Agents can stare at code all day long, but they will not find all the issues because they are probabilistic unit tests. You need to actually run your application to get runtime evidence and proof that things behave as your organization expects them to for full integration and end-to-end tests.
When developers are 3–5x more productive with AI, your org is effectively that much bigger. Your operations need to follow suit.
Discover how AI-driven testing replaces brittle QA automation, cuts bottlenecks, and helps modern teams ship faster with more confidence.
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