Over year ago, our engineering team ditched Scrum. Not because we read some contrarian blog post, but because we looked at our calendars and
realized we spent more time talking about work than doing it. Standups that ran long. Grooming sessions nobody prepared for. Retros that
concluded "we should have fewer meetings" and then we'd schedule a meeting to discuss that.
We tried going process-free. That lasted a few weeks before leadership started asking "when does this ship?" and nobody had an answer.
So we landed somewhere in the middle.
It's called Flights - and it's not new; someone tried it back in 2021: https://simonhoiberg.medium.com/...
The idea is dead simple: a project is a flight. It has a takeoff date, a landing date, and a captain who's responsible for getting it there.
Tasks are crates loaded onto the flight. Team members are crew. People doing maintenance between flights are ground mechanics.
That's it. No story points. No velocity charts. No burndown graphs that give everyone a false sense of confidence. A crate is done or it's not.
The flight lands on the date or it doesn't.
The thing that surprised us most was how well it communicated upward, sideways and to the rest of the organisation.
When we told our CEO "sprint velocity dropped 15%," we'd get blank stares.
When we said "this flight is hitting headwinds but still lands Friday," everyone in the room knew exactly what that meant.
No translation layer needed.
We started with sticky notes and a shared Figma file. It worked well enough that we built a proper tool around it - an airport-board-style dashboard
where you see what's in the air, what's on the runway, and what's landed. Captains, crew, status - all visible at a glance.
We know the obvious reaction: "AI is writing all the code now, who needs project management?" Honestly, we've found the opposite. AI makes
individual developers faster, but it doesn't solve the coordination problem. If anything, teams ship more things in parallel now, and the need
for visibility into what's actually happening has gone up, not down. Your AI pair programmer doesn't know that another team's flight just went
into emergency and yours needs to adjust course.
We've been running it in production for over a year across multiple teams. It was also built as a human-AI
collaboration and experiment - Engineers working with Claude from first commit to production, including the database migrations, E2E tests, CI/CD.
We tried going process-free. That lasted a few weeks before leadership started asking "when does this ship?" and nobody had an answer.
So we landed somewhere in the middle. It's called Flights - and it's not new; someone tried it back in 2021: https://simonhoiberg.medium.com/...
The idea is dead simple: a project is a flight. It has a takeoff date, a landing date, and a captain who's responsible for getting it there. Tasks are crates loaded onto the flight. Team members are crew. People doing maintenance between flights are ground mechanics.
That's it. No story points. No velocity charts. No burndown graphs that give everyone a false sense of confidence. A crate is done or it's not. The flight lands on the date or it doesn't.
The thing that surprised us most was how well it communicated upward, sideways and to the rest of the organisation. When we told our CEO "sprint velocity dropped 15%," we'd get blank stares. When we said "this flight is hitting headwinds but still lands Friday," everyone in the room knew exactly what that meant. No translation layer needed.
We started with sticky notes and a shared Figma file. It worked well enough that we built a proper tool around it - an airport-board-style dashboard where you see what's in the air, what's on the runway, and what's landed. Captains, crew, status - all visible at a glance.
We know the obvious reaction: "AI is writing all the code now, who needs project management?" Honestly, we've found the opposite. AI makes individual developers faster, but it doesn't solve the coordination problem. If anything, teams ship more things in parallel now, and the need for visibility into what's actually happening has gone up, not down. Your AI pair programmer doesn't know that another team's flight just went into emergency and yours needs to adjust course.
We've been running it in production for over a year across multiple teams. It was also built as a human-AI collaboration and experiment - Engineers working with Claude from first commit to production, including the database migrations, E2E tests, CI/CD.
Live demo: https://agile.flights Handbook (explains the methodology): https://agile.flights/docs
Happy to answer questions about the methodology and the tool.