1:1s and Self-Reflection for Compound Agentic Engineering

Traditional management patterns transfer well to build a compounding agentic org

I asked Sloane, my Head of Engineering, to change the way Morgan, my COO, was interacting with me. Sloane said I’d be better off talking to Morgan directly because she would more efficiently know how to rewrite her own memory and context files.

I stopped for a moment and realized: Sloane just told me to have a 1:1 with Morgan!

So I did. We clarified the feedback, she updated her skill prompts and context, and now the interactions are much more productive. The pattern was familiar. I’ve been giving feedback in 1:1s my entire career. The only thing that changed was that my direct report updated her own configuration file instead of trying to remember the conversation.

That’s compound agentic engineering. Every session builds on the last instead of starting from scratch. Without it, every session starts from zero. The agent doesn’t know what it worked on yesterday. It doesn’t know what feedback you gave it. It doesn’t know what it tried that didn’t work. It’s a new hire every morning. You’d fire that person.

A 1% improvement per session compounds to a fundamentally different agent in 60 sessions. Small improvements that stack. And the investment is small: a few minutes of feedback whenever it’s warranted. The compound return is enormous.

It turns out that not only can you give agents feedback, you can ask them to reflect on their own performance. Instead of doing it once a year as part of a 360 review, they can do it every night based on their most recent transcripts.

Here’s the technical insight: asking an agent to self-reflect at the end of a long session is like asking someone to do twenty things and then immediately after a crazy day asking them to reflect on how they could have done it better. They’re deep in the stupid zone. Context is exhausted.

The better pattern: spin up a fresh context window, review each of the day’s conversations, and extract insights with one specific prompt: “How could we have reached this outcome more quickly with less input?” The agent reviews its own performance in a clean headspace, then updates its own context and prompts based on the learnings. It knows better than anyone how to improve its own configuration.

Daily automated self-review for every agent. Not annual. Not quarterly. Nightly. Based on real transcripts, not remembered impressions. Your agents get a small upgrade every single day.

What management patterns are you finding transfer well to your agentic workflows?