A couple of things:
1. data management for music publishers. This came out of nowhere but has got me back into coding, deploying, test. And I've got real lessons using AI-generated code that I wouldn't have got just reading other ppl's blog posts!
We've been mapping all the data formats publishers work with, how to organise them better and build a suite of apps around it.
2. the other projects it the framework. Aside from the product itself, I've ended up with a really nice framework (FE and BE) and playbook for copilot to follow. I've hit multiple problems with AI generated code and had to rework it like I have for junior devs! But now, the framework focuses the work and stops the slop!
I want to build out all the product-dev-helper tools I've wanted in the past. I've already got a lovely schema-UI system, UI components which are data-aware and the basis of some low-ish-code tools. I've also nearly got a "run tests and fix" local LLM which saves tokens.
10+yrs fCTO/fCPO experience in data-heavy at scale applications. I take on 3-4 projects a year helping companies/teams at their inflection points.
Location: UK
Remote: Yes
Willing to relocate: No
Technologies: full stack, especially data-rich / data-heavy applications. E.g. large scale or high complexity of data. Backends include python, node (also java, PHP and others); frontend mostly React but enough experience to adapt. Very deep knowledge of infra and experience in infra-as-code, scaling etc.
Most of my roles are fCTO/fCPO at inflection points: idea to MVP; MVP to stability; stability to scale-up.
I've found:
- amazing business running on ball of mud code maintained in an insane way
- the perfect architecture, CI/CD, TDD where the business/product has little/no value for the customer
Also, I've seen the same stacks succeed and fail. The only common thing I can see is:
- when the tech team fully understand the stack they're using
- when the tech team fully understand the product and business they're building (and can make appropriate trade offs)
There are a bunch of basic tech things. E.g. the underlying infrastructure has to be performance, scale, secure etc. There's also the issue of choosing a tech you can actually recruit for.
It's a facebook messenger bot at the moment but it'll be native app eventually when the details of the chat content are ironed out. I hope to continue the FB bot being free forever, but it depends how it pans out..
Do you know what the roadmap is for this? It looks like they want to build a terminal, but I can't see how it's significantly different from what we've got at the moment.
Social Researching: Like social bookmarking, combined with joining comments so you can share and collaborate on your research.
Think "trails" from V Bush's "As we may think" article, implemented so we can collaborate. As users start bookmarking things in their own trail, the app works out what other trails are similar and suggests you merge your researching efforts.