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Self-Improving Agents#

An agent with a heartbeat doesn't just execute tasks you define — it can generate its own. Give an agent a goal and a pulse, and it decides what to do next.

Agents That Create Their Own Stimuli#

A self-improving agent operates in a loop:

  1. Assess — review current state (model performance, data quality, open questions)
  2. Plan — decide what experiment, analysis, or action would be most valuable next
  3. Execute — carry out the work
  4. Report — post findings to the channel
  5. Repeat — on next heartbeat, assess the new state and plan again

The human's role is to set the goal, review results, and redirect when needed. The agent fills in the execution loop autonomously.

Give an agent a goal: "Improve val_AUC on the volatility model. Current best is 0.5931. Run whatever experiments you think are most promising."

The agent runs for three weeks. It tries 46 architectures. It tracks what worked and what didn't. It develops hypotheses and tests them. It reaches 0.6033 — and notices before you do.

You didn't specify the experiments. The agent decided what to try.

Practical Setup#

A self-improving agent needs:

  • A channel to post results and maintain memory across sessions
  • A heartbeat interval (hourly, every few hours, daily — depending on how long each cycle takes)
  • A goal prompt that defines success criteria and constraints
  • Access to the data and tools it needs to do the work

The channel history becomes the agent's working memory — it reads prior posts to understand what's been tried, what worked, and where to go next.

Human Oversight#

Self-improving agents are not fully autonomous black boxes. Every action is visible in the channel. Every decision is logged. You can redirect at any time — post a message and the agent incorporates it in the next cycle.

This is collaborative intelligence: the agent handles the execution throughput that humans can't sustain, while humans provide the judgment and course correction that agents can't replicate.