Yep exactly my thoughts, went and looked at the code for the deepseek provider in my coding agent. and basically all of what the author wrote there is implemented... http://github.com/tontinton/maki for the curios
Great question! I like to think about this in two ways:
1. Counter-positioning. Most existing tools have invested heavily in their web platforms and compete on their UI/UX. But actually, what matters to our clients is that bugs are fixed. Our top clients would rather never open our tool at all. If our competitors want to beat us, they essentially have to fight against their established business models that hinge on users looking at their browsers.
2. Evals. In order to have the most accurate RCA analysis you need a very good suite of evals: what was the right root cause in this bug? what is the right fix?. We're investing into this heavily, and as one of the early movers we have a big advantage here.
At the same time, I tend to approach strategy with a lot of caution. A lot of the canonical reasoning behind 'startup positioning' is based on extrapolation from trends, but surprisingly few analogies work in economics.
Our focus right now is:
- talking to our users
- making sure they have the best experience
Currently the subagent chat windows don't allow to inject user messages like the main window, I want to change that soon though.
Regarding tiered models, it currently caps the model use to the current tier you're on, so no it can't upgrade from haiku to opus suddenly. The reasoning for that is that if you selected haiku, you probably don't want to pay for opus by accident.
Yeah we all converge to the same workflow, in my ai coding agent I'm working on now, I've added an "index" tool that uses tree-sitter to compress and show the AI a skeleton of a code file.
I'm curious, what does your workflow look like? I saw a plan prompt there, but no specs. When you want to change something, implement a new feature etc, do you just prompt requirements, have it write the plan and then have it work on it?