How do you view harness engineering as an organic development that emerges from its use within a specific domain? Basically the meta-loop that allows an agent to tailor its harness to improve outcomes based on performance feedback. I use Pi a lot and I'm very interested in "self-assembling software".

One concrete example might be maintaining a conventions document per-project that covers how to name things semantically from a list of nouns and verbs. The idea is that LLMs are often not very globally aware, but it's important to maintain coherence across a code base in order for it to scale (in size and over time). Sometimes an LLM might call the same concept a Materialization, sometimes a Projection, and its not useful if its using two terms interchangeably without purpose.

Basically, how are you maintaining coherence when there isn't a human steering the code beyond providing requirements and validation directives?

I see you have relevant context in the repo like https://github.com/lopopolo/harness-engineering/tree/trunk/d... but I'm curious what exists beyond context. Do you use any tooling to steer this type of thing more consistently?

One challenge/opportunity I've had is harnessing really wide running cheap agents. Any thoughts on how to move really cheap agents beyond basic summarization so we can go broader than the pricing of frontier llms allows?

Thanks. I am guessing you have to try stuff and build tacit experience. No other way, just get stuck in and try stuff, then try and learn bits from others?

This is interesting. I'd already had a conversation with my harness ( pi ) about incorporating continuous improvement. This is a great deal better than what I came up with.

What motivated you to quote your own quote (??) in your readme claiming to boost productivity by 100x, and where did you derive that number from?

"When a quote sounds profound enough, reality usually nods out of politeness, without echoes is just a sentence wearing pajamas." - slopinthebag