HN user
It's about the hardest agentic problem that has measurable results and will be adopted (because it's an engineering culture) that I can think of. RunWare have some good insights on this - much of the problem is context layer improvisation and repetition, and the only way out is an awful lot of diagnostic development.
And anything less than 90% accuracy on causal analysis is more work than doing everything by hand.
A machine for living. I like sailing, it's just very expensive and time consuming..
I am a middle aged man who lives on a sailing boat. A decade in early stage / founding without an exit that's closer to a car crash. Still trying, I don't have the temperament for consulting or corporate.
I would really like to see more people down my prompt engineering rabbit hole of trying to use ontology / compilation tricks to produce prompts from models rather than curating text. I have this working pretty well for complex tool interaction, without a JSON schema or template in sight.
Believe it or not, agents can run things like this:
e3{p13=e4(p14), p38=$} returns [e3] · Incremental collaboration signal (what changed and when). Poll to stay current; acknowledge so the server can advance your cursor · optional params: p38
Yes but when I go there as a Europoor I still feel like Borat.
An awful lot of problems can in fact be solved by 'more code' in fact. People seem to straw man this in terms of product feature surface.
A lot of places skip creation and maintenance of decent observability - that's code.
We can now easily use advanced, code heavy testing techniques like property testing - code.
We can create environmental simulations to speed up and improve integration testing - code.
We can lift up internal abstraction levels, replace boiler plate with frameworks, DSLs - code.
I'm still mad about not being able to buy a phone with an external RF connector.