What we are learning
‍Building SenseLab

Jev has no idea how its last decision went. Every call starts from the state you send and the policy you wrote.

A deploy finishes. An agent reads the logs for nine minutes and tells you one of two things. Either "cold image, ignore it," or "this looks like a product regression, here's a draft PR." How much do you trust that?

Today most people run coding agents on a laptop, or on one long-lived dev box the agent has been slowly redecorating for three weeks. Those are pets.

We can get agents to use tools, follow instructions, coordinate through chains and graphs. What we can't easily do is get them to collectively improve at a task over time.

Continual learning requires training signal. Training signal requires knowing what your agents read, what they decided, what happened as a result, and which pieces of knowledge were actually causal in the outcome. That's a cognitive layer.

The switching cost isn't the model anymore. It's everything the model remembered. That's a moat the vendor gets to build out of your data, and the better their memory works, the deeper it gets.