One Corner of Your Company Already Solved AI Teamwork

For as long as there have been companies, work was a team sport. But AI is killing cooperation. Before AI, people handed things off, built on what someone down the hall already worked out, borrowed a good idea and made it better.

Now everyone has an AI helping them do that work, and in the companies that have leaned into AI the hardest, something strange is happening to all that teamwork. Each person and their AI are getting more done on their own, but the work itself is scattering. What you and your AI produce today never reaches me and mine, so tomorrow I redo a version of it, or I build something that collides with it.

One department escaped this, and its people are pulling away from everyone else in how much they get out of AI. Their advantage has nothing to do with better prompts or smarter models. It is a piece of infrastructure they have used for twenty years, built long before AI for a completely different reason, that turns out to be exactly what a company full of AI-assisted workers needs. Read on, because once you see it you will want it for the rest of the company.

The team that still shares

Ask around any company which group gets the most out of AI and you will hear the same answer: the developers. The easy explanation is that AI happens to be good at writing code, which is true and also not the interesting part. Their real advantage has less to do with what AI is good at and everything to do with where their work lives.

Every developer on a team works out of the same shared, organized data store of the project, and has for years. When they point AI at that store, the AI inherits the same view they have. It can see what everyone else is working on, pick up where a colleague left off, and add back to the same pile everyone draws from. The rest of the company has no equivalent, so their AI starts every task blind. It is the same AI in both places, but the ground it stands on could not be more different.

Built to stay organized, then to share

Most companies already have a shared place for work, whether that is Google Drive, OneDrive, SharePoint, Notion, or Confluence. It helps to remember why those tools exist. They were built first to keep your own work organized, and sharing came second, once your files were in one place other people could open them too. They do that job well for humans and almost nothing for an AI, because a pile of documents has no map an AI can follow. Drop some important work that many others could benefit from in there and no one else’s AI ever finds it, because their AI is not looking in your folder and does not know the folder exists.

GitHub, the place software teams keep their work, started from the same instinct — keep one engineer organized — and then grew into the best tool we have for large groups building software together. What matters now is what GitHub does that a shared drive never could, and that gap is the whole reason the developers’ AI works so well and everyone else’s sits in the dark.

Your AI can see the whole picture

Two things make GitHub work for the dev team. The first is discovery. Everything the project needs sits in one cataloged place, so any person, or any AI, can look across the whole thing — all of the context — and find the exact piece they need. Your AI is not guessing or waiting to be handed the right file; it reads the map and goes and gets the information it needs. That shared view becomes a kind of shared memory for the team, one that every person and every AI can draw on instead of each starting from scratch.

The second is order. Because everyone adds to the same data store, there are rules for how changes go in, so a hundred people and their AIs can all contribute without overwriting each other or running into conflicts. Boris Cherny, who leads Claude Code at Anthropic, says code output per engineer there is up 200 percent. The AIs there are no smarter than the one on your desk; they simply share a memory and a way of keeping it clean that your AI doesn’t have.

Marketing and finance are flying blind

Now look at the rest of the company. Marketing, finance, sales, legal, and operations make up most of every business, and each of them is now producing real work with AI — the campaign briefs, the financial models, the contracts, the plans. Almost all of it happens inside someone’s private chat window, invisible to everyone else. The marketer’s AI has no idea what the analyst’s AI worked out this morning, so it cannot use it, cannot build on it, and often reinvents it a little worse.

Picture the other version. If your AI could see the work your team and the teams around you were producing, it would start every task on top of what already exists instead of from nothing. You would get fewer duplicated efforts, fewer plans that contradict each other, and more people building on the best thing anyone has already made. That is exactly what the developers get for free, and exactly what everyone else is missing.

We all work like a dev team now

This is the shift worth naming, and it is not that everyone is about to write software. It is that everyone is now producing the same kind of thing a dev team produces: a steady stream of output made with AI — the drafts and research and decisions and context we each create once and then lose in a private thread. Call it AI exhaust. It is piling up in every department, and almost none of it is being kept where the next person, or the next AI, could use it.

That output needs a home the same way code needed one: a shared place where the context worth keeping is saved, organized, and easy for a colleague’s AI to discover and build on. Managing that context, so every AI in a company works from the same current, shared picture, is the real engine behind the developers’ head start, and it is the problem we are working on at Bot Food. The developers stumbled into their version of this twenty years ago, and the rest of us need one too.