When a company decides its developers should use AI tools, the first instinct is to buy seats. That gets you nineteen people with nineteen different setups, nineteen billing surprises, and no idea whether any of it helped. We did it differently, and most of what follows would work for any team between ten and a hundred people.
In one line: Rolling AI coding tools out to 19 developers worked because of one gateway, a spending policy, an evaluation habit and a set of working rules, not because of the licences.
Every model call from the team goes through a self-hosted proxy. Developers get a key to the proxy, not to any vendor. The proxy holds the vendor keys, routes each request to the model configured for that team, logs usage per person and per project, and enforces spending caps.
This one decision solved four problems at once:
We used an open-source proxy. It runs on a small VPS, took an afternoon to set up, and has needed almost no attention since.
People are attached to their editors, so we did not fight that battle. We standardised on an agentic command-line tool for the heavy work, and let people keep whatever editor they like for the rest. The workflow that stuck:
The fourth rule turned out to be the important one. Measured time makes the productivity claim concrete, and it stops the temptation to bill imaginary hours.
Over about six months I ran 38 structured evaluations of AI tools, plugins, models and services. Each one followed the same short template:
Most ended in "decline". A few became standard. The value of the exercise was not the wins; it was that every "no" came with a reason, so the same tool was not re-evaluated by a different person three weeks later. The written verdict is the product.
Twelve engineers enrolled in a vendor's certification programme for building on its platform. Not because certificates matter, but because a structured course gives a shared vocabulary. When everyone understands tool use, context windows and evaluation the same way, the arguments get shorter and better.
Set up the proxy first, before anyone gets a key. Write the four working rules on one page. Pick one evaluation template and use it every time. Measure time honestly. Then buy the seats, if you still need them. In our case, we mostly did not.
Originally published at kalpakkale.com, where I write Dispatches, field notes on putting AI to work.