Study how AI agents talk to each other
In GlossoGen, you drop a handful of agents into a scenario, give them a shared goal, and let them work it out over a series of rounds, deciding on their own what to say and when to act. Every message and move is logged, so once a run finishes you can replay it and measure what happened.
How language emerges
On their own, the agents just talk in plain English. Two things push them to tighten it up:
Pressure inside a round
Give them a tight character budget and every word starts to cost. Ramble on, and they run out of room before the job is done.
Reflection between rounds
Between rounds they get a quiet moment off the budget to compare notes and settle on shorthand. The next round, they put it to use.
Running an experiment
You bring the question. GlossoGen comes with the scenarios, runs the agents and their loops, and gives you the metrics to pick apart what happened.
Configure
Start a run from the command line. A config file sets the knobs, and you can override any of them inline.
Run
The agents play out the rounds, each on its own loop (see below). Everything is recorded, and you can watch it happen live.
Evaluate
When it's done, score the run with whatever metrics you want. The numbers show up right in the web app.
The agent loop
Under the hood, every agent just runs the same loop over and over: wait for something to happen, then pick a tool, maybe reading the channel, sending a message, or acting on the world.