the @aiDotEngineer World Fair always one of the best events every year to talk to builders at the frontier of Research, Agents, Evals, Systems, etc A few weeks ago I gave a talk on - Continually Improving Agents - building Agents to understand data from other Agents - & a walkthrough of some of our latest work on data agents & post-training experiments some fun takes: - Every Continual Learning company will be an Observability & Eval company (and vice versa) - Environments & Evals are the currency of agent improvement. Agents are literally following the behaviors encoded in Evals. The best way to make good evals is mining Production data at scale - A good recipe to own your intelligence is using a Harness Eng - PostTrain - Harness sandwich with open models - Model-Harness-Task fit! There is no universal model or universal harness. You can always build a better agent system by optimizing the model and harness for a given task if your team is looking to understand your data at scale, build environment/evals, or just improve your agents - reach out, hmu would love to work with you! 🚀