I talk to engineers at other companies every day and hear the same thing: one person is 10x'ing their output with Claude but the rest of the org hasn't caught up.
Watching teams adopt AI, I keep seeing the same 4 steps.
I mapped them out here: Steps of AI Adoption https://t.co/kQnRAUMKpP
https://x.com/bcherny/status/2077929386146169269
There’s no one right path through the steps. Every team and company is different. But at each step, tokens aren’t enough to move you forward: to get to the next step, you need to find and break down the next set of bottlenecks, and build up the next set of guardrails.
https://x.com/bcherny/status/2077929390806073807
In practice that means giving Claude ways to verify its own work end to end. It means enabling auto mode for permissions, defaulting on automated code review and security review, and using interfaces that let you manage multiple agents at once (Agent view in CLI, Desktop app, iOS and Android apps, Tag).
To get to higher levels it means /loop, /batch, dynamic workflows, and worktree isolation for subagents. It's not about a single feature, but rather using the right features with the right guardrails that enable Claude to automate entire classes of work in a way that your team can trust the output.
https://x.com/bcherny/status/2077929397495959693
Once your teams are bought in, how do you track it? Usage is worth watching (e.g. a dashboard), but it measures activity, not return. A better question: would you have spent engineering effort on this anyway? If yes, how much and what would it have cost in manual eng-hours? That's your return.
https://x.com/bcherny/status/2077929404219474148
The bigger payoff comes when fixing and maintaining happens in the background and your teams can focus on building. That's when you start doing things that weren't even in range before.
Anthropic is on step 3 and pushing toward 4. Personally, I just hit level 4.
Curious where you are -- what step is your team on?