@MatthewBerman yeah. sticking with it for now. Great product. There is something about seeing code and being able to change it, when I feel like it.
my .openclaw folder is a Cursor project
I'm an avid user of #JournalApp on the #ios . I think it's a great product and a very smart component that Apple has developed.
I wish more app developers would use the API.
https://t.co/jYuSZ4lia7
We are going to flatten a stack of roles in an org. First, we asked designers to write html, now we have VC augmented by AI managing multiple hands on roles.
I own a company - @Hustle - that makes enterprise software. I recently added the responsibility of being their CEO (I'm still CEO of @socialcapital ). I did this because I felt I was losing the specific details of how to build well-run companies in 2023. I was becoming too much of a talking head and not enough of a hacker/doer.
On Tuesday, I met with some of our team to tackle a problem that was leading to increasing volumes of customer support needs. So I offered to try and tackle this using AI.
By the close of business yesterday, I had been able to complete the following steps: initially using OpenAI, then redoing it in Anthropic, and finally writing some basic Python in Replit in a crawl, walk, run sprint:
1) Initially configured a new GPT with OpenAI and added some specific knowledge that helped it learn edge cases, allowing us to create a simple way of helping our customers avoid the problem upstream. This should improve their experience with our tool and impact the error rate in a way that decreases the OpEx to serve these customers (TBD and will confirm when I know for sure) - this seems applicable to many companies.
2) Moved this to Anthropic to expand how/what it could learn (ie does increasing tokens add to accuracy/value to us?). Also TBD.
3) Built it in Replit so that our eng team could fork it, make it less janky and actually integrate it into the product. Replit is nice.
Here are my observations over this past week as someone who was never a great coder, didn't have a dev environment that had evolved beyond vi and had only talked about AI up until now without actually doing anything with it:
1) The abstracted way to create functionality is really impressive. I wrote and edited the "PRD" in a text file in human english. This feels profoundly disruptive by increasing the top of the funnel of those who can now build products.
2) Adding knowledge to the model was easy, but once you hit a threshold, fine tuning is the only way. I haven't started this process yet so will have to report back on how hard this is.
3) Every single tool I used was excruciatingly slow and unusable in any reasonable production setting. I know it’s early, but man, it’s slow. Super slow. Did I mention how slow it is?!?! Whoever can help solve this will be a big winner...
Will report back as I learn more and try new things with AI to help this company grow…
h/t to @sundeep for showing me that i could do this
User stories are supposed to be unclear. They're anything from a word to a sentence long with no implementation details. (They describe the user's work, not yours.) They are a reminder to have a conversation just before and during implementation. Fill in the details during Sprint Planning or equivalent��just enough detail to start, not finish. Collect additional details with more conversations as you work. Collecting lots of detail up front is just a waterfall requirements-gathering phase. No agility there.
@carlvellotti Remind me of an early days of the @AppStore and how various interactions were tried and failed. Now, guidelines and interactions are pre of less established.