Jono Herrington

New leaders inherit teams that already have the answers.

AI keeps generating code until someone decides what one pull request is allowed to carry.

A senior director told me projects went well when I was involved and struggled when I was not.

The worst failures are not always missing documentation.

My diagnosis didn't magically improve my leadership.

Managers fail development in two predictable ways.

The team responded to the incident.

Communication matters.

A high-drive engineer asked what it would take to grow.

If one engineer taking PTO can stall shipping, your problem is not staffing.

A team turned on agent mode.

For 23 years I've watched developers copy code they didn't understand.

I was watching the head of architecture demo his team's AI setup when I realized we'd been solving the wrong problem.

Everyone has worked with a Steve.

For the first month I treated Copilot like a junior engineer with ambition and no guardrails.

A senior engineer posted on Reddit recently about how it's almost like he's in grief.

AI is amplifying the technical debt you were already permitting.

We stopped talking about DevOps.

We treat AI like a vending machine.

I built a dashboard to track PR review times.

Accountability means knowing why.

Every productivity system I tried assumed my brain could be disciplined into submission.

Every junior engineer thinks the job is syntax.

The strongest engineers walking through the door are not the ones with the cleanest GitHub.

The loudest voices in engineering keep framing AI as the great equalizer that will let mediocre developers ship junk code.

Six months into AI adoption, every team has dashboard metrics that look good.

AI changes speed.

Your leadership thinks you'll code in 3 seconds, read and understand it all, push to production without breaking stride, and never forget anything.

You're asking engineers if they know how to use AI tools.

I've seen engineers lose the spark in their eyes in their craft having to just plan and review the output.

I used to stay up endless nights losing myself in code.

A junior engineer told me he couldn't explain his own code.

Procurement is not adoption.

When AI scales output without scaling review, the quality gate breaks.

If I had to roll out AI to my engineering team again, I wouldn't start with the tools.

A junior engineer told me he wasn't sure he understood everything the AI was outputting for him.

Technical leaders are being asked to set AI standards, define acceptable output quality, and govern what gets into production.

When I reviewed my team's AI adoption dashboard last quarter, every number was moving in the right direction.

More than 500 engineers described what happened when their companies chose mandates over conversations.

Jono Herrington pushed for higher velocity.

Six weeks after giving our team AI coding tools without guardrails, the codebase looked like a junk drawer with a CI/CD pipeline.

GitHub found developers complete tasks 55% faster with AI tools.

Engineers who spend their days directing AI agents and reviewing generated output are experiencing the same skill decay that managers hit years ago.

Most teams attack PR bottlenecks with better tooling, shorter PRs, and review rotation schedules.

AI doesn't have blind spots.

AI adoption at speed is erasing the orientation senior engineers spent years building.

AI tooling compresses the low stakes work out of an engineer's day.

When an engineer says 'ChatGPT recommended something else' to close a technical debate, that's not a technology problem.

I spent time in a thread with 500+ engineers saying AI destroyed their love of coding.

A dev posted on Reddit about their manager's manager demanding more productivity while adding more meetings.