MathBreakers, Your Limitless Math Universe. It's a math game platform teaching fundamental grade school concepts like Fractions in an immersive 3D world with virtual manipulatives (no equations or worksheets).
Re-reading the Lean Startup to hone our GTM, market validation and growth engine.
I looked at all linked articles and could not find an example of the points (they show a square grid of points with n~=100 but no other ordering of points to show the more optimal layout(s)).
Is there anywhere an image example of a superior layout for example with n>={100,1000,10000}..? I would love to see it. I am imagining it would look somewhat like a sloppy pizza.
I just finished an implementation of CI across three codebases totalling >50k lines and I can confirm a lot of the author's pain points, especially around logging and YAML variables.
Commit with one character YAML difference? Check.
Commit with 2-3 YAML lines just to add the right logging? Check.
Wait 5+ minutes for a YAML diff to propagate through our test pipeline for the nth time today? .. sigh .. check
BUT, after ironing all these things out (and running our own beefy self-hosted runner which is triggered to wake up when there's a test process to snack on), it's .. uh.. not so bad? For now?
We use them on our cats and have found the trouble-maker cat 3 times out of 3 when needed (in an urban apartment area; most recently the cat was scared by a noise which may have kept her hidden out all night in the cold, unless we had found her/shooed her back to the house)
I would personally pay $2x market price for a Phone, Computer, Tablet that guaranteed privacy (via whatever technical means necessary) for all my interactions with the internet.
Is that so much to ask?
Could the next "Apple" produce such hardware/software stack to black box this for the consumer -- simply buy "Pineapple" products and guarantee this stuff can't touch you (user obsfuciation for all external platforms could be a hard technical challenge, I know - hence the big value if delivered)
That is also not enough. An agent could build an application that functions, but you also need to have a well-designed underlying architecture if you want the application to be extensible and maintainable - something the original dreamer may not even be capable of - so perhaps a shared extended dream share with a Sr. architect is also needed. Oh wait .. I guess we're back to square 1 again? lol
I joined a company with 20k lines of Next/React generated in 1 month. I spent over a week rewriting many parts of the application (mostly the data model and duplicated/conflicting functionality).
At first I was frustrated but my boss said it was actually a perfect sequence, since that "crappy code" did generate a working demo that our future customers loved, which gave us the validation to re-write. And I agree!
LLMs are just another tool in the chest; a curious, lighting fast jr developer with an IQ of 85 who can't learn and needs a memory wipe whenever they make a design mistake.
When I use it knowing its constraints it's a great tool! But yeah if used wrong you are going to make a mess, just like any powerful tool
Yes, better prompting is absolutely essential, and I still love to let Claude do the heavy lifting when it comes to syntax and framing. But in trying to re-write the data model for this app, Claude continually failed to execute due to prompt size or context size limits (I use Claude Max). Breaking it into smaller parts became such a chore that I ended up doing a large part "by hand" (weird that we've come to expect so much automation, that "by hand" feels old school already!)
Oh, also when it broke down and I tried to restart (the data model rewrite) using a context summary, it started going backwards and migrating back to the old data model beacuse it couldn't tell which one was which .. sigh.
As someone who walked into 20k+ loc React/Next project, 95%+ vibecoded, I can say it's a relative nightmare to untangle the snarl of AI generated solutions. Particularly it is bad at separation of concerns and commingling the data. I found several places where there were in-line awaits for database objects, then db manipulations being done inline too, and I found them in the ux layer, the api layer, and even nested inside of other db repo files!
Someone once quipped that AI is like a college kid who studied a few programming courses, has access to all of stack overflow, lives in a world where hours go by in the blink of an eye, and has an IQ of 80 and is utterly incapable of learning.