Software Engineering

AI agents can execute from a precise spec. The real bottleneck shifted from writing code to writing what you want — clearly. Here's what changed, why it matters for engineers, PMs, and managers, and how to actually do it.

The org chart most teams run was designed when humans wrote all the code. Anthropic's 2026 data says that assumption is gone. Here is what the structure should look like now — and what roles actually matter.

Faros AI tracked 22,000 developers and found individual AI gains evaporate at the org level. PR merge times are down 20%. Incidents are up 23.5%. Here is the mechanism — and what actually fixes it.

PR turnaround time is the most undervalued engineering metric. Here's how to cut it from days to hours without sacrificing quality.

Bad commit messages don't waste seconds. They waste hours, weeks later, when you're debugging an incident at 2am.

Most teams use feature flags wrong. They become permanent if/else branches that calcify into chaos. Here's the discipline that fixes it.

Your AI feature has a 200-line system prompt living in a string in app.py. That's tech debt. Here's how to treat prompts like first-class artifacts.

Microservices are an organizational solution to a coordination problem you don't have yet. Here's when they actually help — and when they're a foot-gun.

Multi-repo is overhead masquerading as separation of concerns. For teams under 50, monorepo is almost always right.

Every 100 lines of diff doubles the time to merge. Here's why, and what to do about it.

Your AI feature passes 100% of unit tests and ships broken to users every other week. Here's why, and how to actually test LLM-powered systems.

TypeScript errors are either a wall of red noise or a useful guide. The difference is how you model errors. Here's the playbook.

Ten months after MCP went multi-vendor, most teams are still treating it as a nicer function-calling wrapper. That's the wrong mental model — and it's quietly producing architectures that don't scale.

A MAST taxonomy of 1,600+ execution traces maps 14 failure modes across 3 root causes. The model is almost never the problem. The orchestration architecture almost always is.

82% of AI teams say prompt engineering alone isn't enough. The ones succeeding in production are treating context design the same way they treat database indexes — as an architectural decision, not a prompt trick.

Georgia Tech tracked 35 CVEs from AI-generated code in March 2026 alone — more than all of 2025 combined. Here's what the data says, why it's happening, and what a secure AI workflow actually looks like.

AI agents made writing code cheap. The skill that actually matters shifted to reading what they produced and deciding whether to keep it.