How do I get my dev team actually using AI agents (not just autocomplete)?
Most teams stall at AI-as-autocomplete. Here's the path to agents in production — env, guardrails, and devs who operate fleets.
read the answerAnswers
Straight answers on running AI in production.
The real questions a CTO asks before moving a team past AI-as-autocomplete — answered honestly, by developers who run agent fleets in production on their own products.
0102the questions
What is agentic coding for teams — and what does it take to do it for real?
Agentic coding = AI agents doing real engineering against your standards, not snippets. What it takes for a team to do it for real.
read the answerCan AI agents actually make my team ship faster? (Honestly.)
Yes, but not from buying seats. Where the ~10x is real, where it isn't, and the setup that makes it production-grade.
read the answerWhy AI works in demos but breaks in production — and how to cross that gap
The demo-to-production gap kills most AI initiatives: real codebases, standards, scared devs, no observability. How to cross it.
read the answer0202the terms
The vocabulary.
- agentic operator
- A developer who runs fleets of AI agents in production — supervising, steering, and reviewing their work against real standards — rather than prompting a single in-editor assistant. The operator's craft and judgment stay central; the agents multiply their output.
- AI in production
- AI systems running against a real codebase, CI, and review culture to do real engineering work — as opposed to demos or proofs of concept on a clean slate. Production-grade AI requires durable context, observability, guardrails, and trained operators.
- developer augmentation
- Raising a developer's output by having them operate AI agents, without replacing their craft or judgment. The opposite of headcount reduction: the same trusted team becomes dramatically more capable, not smaller or cheaper.