I built a 3D brain that watches AI agents think in real-time (free & gives your agents memory, shared memory audit trail and decision analysis)

Posted yesterday in this sub and just want to thank everyone for the kind words, really awesome to hear. So thought I would drop my new feature here today (spent all last night doing last min changes with your opinions lol)

. Basically I spent a few weeks scraping Reddit for the most popular complaints people have about AI agents using GPT Researcher on GitHub. The results were roughly 38% saying their agents forget everything between sessions (hardly shocking), 24% saying debugging multi-agent systems is a nightmare, 17% having no clue how much their agents actually cost to run, 12% wanting session replay, and 9% wanting loop detection.

So I went and built something that tries to address all of them at once. The bit you're looking at is a 3D graph where each agent becomes this starburst shape. Every line coming off it is an event, and the length depends on when it happened. Short lines are old events that happened ages ago, long lines are recent ones. My idea was that you can literally watch the thing grow as your agent does more work. A busy agent is a big starburst, a quiet one is small.

Colour coding was really important to me. Green means a memory was stored, blue means one was recalled, amber diamonds are decisions your agent made, red cones are loop alerts where the agent got stuck repeating itself, and the cyan lines going between agents are when one agent read another agent's shared memory. So you can glance at it and immediately know what's going on without reading a single log.

The visualisation is the flashy bit but the actual dashboard underneath does the boring stuff too. It gives your agents persistent memory through semantic and prefix search, shared memory where agents can read each other's knowledge and actually use it, and my personal favourite which is the audit trail and loop detection. If your agent is looping you can see exactly why, what key it's stuck on, how much it's costing you, and literally press one button to block its writes instantly.

Something interesting I found is that loop detection was only the 5th most requested feature in the data, but it's the one that actually saves real money. One user told me it saved them $200 in runaway GPT-4 calls in a single afternoon. The features people ask for and the features that actually matter aren't always the same thing.

The demo running here has 5 agents making real GPT-4o and Claude API calls generating actual research, strategy analysis, and compliance checks. Over 500 memories stored. The loops you see are real too, agents genuinely getting stuck trying to verify data behind paywalls or recalculating financial models that won't converge.

It's definitely not perfect and I'm slowly adding more stuff based on what people actually want. I would genuinely love to hear from you lot about what you use day to day and the moments that make you think this is really annoying me now, because that's exactly what I want to build next.

It runs locally and on the cloud, setup is pretty simple, and adding agents is like 3 lines of code.

Any questions just let me know, happy to answer anything.