Maintaining quality when an organization just lacks the muscle to make changes and nobody has the mandate to try to make sure uptime is in good shape is a challenge. A lot of things break, precisely because there's just as much change as Will sees, but it's very unevenly distriuted.
- Create a Git Hub project board for issues
- Connect Grok to the above
- Use Grok voice mode to take ideas, have Grok refine them with me and then save them as issues
- Created slash commands in OpenCode like /ni (new issue), /do (do an issue), /curr (what is the current issue), /done (self explanatory)
- I generally tell the OpenCode instance to /do <number> and then off it goes
This give me several benefits:
- I can use Grok Voice while walking or driving to develop and test ideas
- I can lose my entire local OpenCode setup but still have relevant data in the issues
- multiple machines can read from GitHub
- I could go even further and have separate user accounts for each of my bots.
Having been both a PM, dev, SRE and manager, this really does feel like managing a team of devs.
Musk would be so proud. Do you by any chance drive a cybertruck too?
Seriously, don't do this while you're driving. Or even while your car is driving. Its dangerous to be distracted in that situation.
https://jaisenmathai.com/articles/sojourn-for-ios-was-45-one...
However, as far as what's being pursued, it seems more like wantonly trying to ride a hype cycle without strongly questioning the end-to-end value of new software development approaches or vetting their immediate suitability.
Personally, I think it would be more sensible to take a few individuals or a smaller team(s) and do more isolated/skunkworks experimentation and adopt as justified based on what those people report/experience. The smaller group can adjust faster and iterate/advise the larger dev org about the good approaches/techniques/strategies, and avoid more broad damage/chaos for things that aren't that well thought out.
For more conservative AI use cases like adding to code review, writing low stakes PR summaries, or beefing up security checking, a more global, but still not off-the-rails, approach would be the kinds of things that would make more sense to push more broadly.
I know there are traditional testing frameworks that can detect jitter and frame drop to a certain level. We could potentially start having agents build that in.
If we had concrete designs and specs on every project, that would also be helpful, but in a fast-moving startup, that gets delegated to the builders. That puts a human back in the loop every time.
Curious to hear what anyone else does to fully adopt a software factory pattern.
Right now I'm working on a declarative UI framework which can help me along here. My thought is that if I sacrifice a little control for sane primitives, that will make that spec /build loop easier.
I think ClayUI is a really interesting "reduced instruction set" for UI. I don't know that immediate mode UI is the right call for anything web related (that's how you get React lol) but his reduced primitive layer is very interesting to me
After your first para, I was about to suggest exactly that (well, maybe not writing your own). I find that frameworks (both front-end and back-end) constrain the LLM's choices and result in both sensible defaults and improved consistency.
Of course, you will immediately hit the problem all frameworks have: customer requirements that the framework components don't quite meet.
Still, great for RAD.
I suspect that the vendors out there who have not adopted AI development and are losing market share to competitor who has are not vocal about not being an adopter, they are just complacent.
Preferably ones that I could validate myself instead of just having to take someone's word for it.
May I ask what you’re making that somehow is improved by turning everyone into chat bot controllers?
The downside, however, is they are also unknowingly digging themselves into holes. For example, we have AI-generated skills that are thousands of lines long and include Python scripts with hundreds of lines of tests. Some of these Python functions are literally just emitting MCP tool names.