Judgment Labs

Agent trace telemetry is one of the most critical parts of the RSI loop. Back when I did an RSI loop on Cline to make it automagically improve the harness over a 17 hour long running agent run I found that parsing good signals and iterating on it with the analyser agent could fix an agent response and rerun to hill climb agentic evals. Until it reaches the models peak possible score without some tricky reward hacking. This is just one part, now imagine if the agent failures at the peak become filtered to become proper post training signals and trajectories of growth, wouldn't that be amazing? Now lets go one step further, if you are an enterprise with tons of confidential data that AI just messes up because its too much context to get it all right at once what do you do? You take a smaller model and get agent telemetry and post train models and get higher perf. The future is a world of smaller post trained models curtailed to specific enterprise use cases working in tandem with behemoth trillion dollar models as agent orchestrators but it all has to start somewhere.