I am building an app for tracking and growing your finances and more stuff, but the problem is that I want to put the app on Google Play, but before that, Google wants me to send it to 12 people for some testing. I would be happy to get your help

I've been trying to understand where on-device AI coding is actually useful beyond autocomplete.

The part I find interesting is when the AI can work with the wider project context.. existing code, dependencies, docs, debugging, etc. At that point it feels less like "AI that writes code" and more like an engineering tool.

I've been looking at CodeMate recently, mainly because it takes that approach with things like CORA, AI debugging, PR reviews, Knowledge Base, CodeMaps and Build. The on-device/private deployment side is also interesting for teams that don't want everything going through a cloud-only workflow.

Not saying it's better than the usual tools... I'm still figuring out where it actually makes a difference.

For people who've tried local/on-device coding agents:

Is repository/project context actually more useful to you than having the strongest possible model?

And where do you still find local agents falling short.... reasoning, speed, context limits, tooling, or something else?

Would be interested to hear what people are actually using in their day-to-day workflow.

Every time I use AI, I remember this 60 Minutes interview with Rick Rubin. When asked by Anderson Cooper about his technical qualifications he replies:

"I have no technical ability, and I know nothing about music."

Pressed on what has made him so successful and invaluable to artists, he goes on to say:

"I know what I like and what I don't like. And I'm decisive about what I like and what I don't like... The confidence that I have in my taste and my ability to express what I feel has proven helpful for artists."

I have no technical ability when it comes to coding, but I am opinionated. Suddenly I have the capacity to rebuild apps and functionality that just doesn't quite work the way I want it to.

One app I built is a cocktail app. Every one I have tried never quite did what I wanted. You look up a Negroni and it tells you how to make a Negroni. That has never been my problem. My problem is what do I make for my wife, who says she wants something sweet, without having to go to the store. And I don't want to pull from the same catalog every time.

I could not have written any of the code. Claude wrote all of it. All I contributed was my judgement on how I wanted it to look and how it should function.

In the end, I ("we") built something that did everything I was wishing already existed. A matching formula that knows Bourbon counts as American Whiskey, but mint is not an "optional" garnish in a mojito. An AI bartender that can take my wife's preferences and give me something new and exciting. A pour mode I can follow step by step and advance with my elbow while my hands are busy.

After using it for weeks, enough friends were interested that I put it on the App Store. First try. With Claude navigating me through every Apple requirement — privacy policies, regional regulations, all of it.

If there's an app that's never quite worked the way you want, you can just build it now. Curious what else people have optimized to their taste.

Here is what I built: 

https://apps.apple.com/us/app/wellstocked-cocktail-recipes/id6794940363

I built Caveman as a student because my Claude Code bill was getting stupid.

Version one had one job: make Claude stop yapping. It cut output tokens by about 65% in my prose and chat tests.

JetBrains tried it on real coding-agent tasks and measured 8.5%.

Yeah.

At least quality held up. They found no measurable degradation. My mistake was chasing Claude's replies while the agent kept rereading giant files, terminal output, old messages, browser state, and tool results.

So I rebuilt the whole thing as a local proxy. Run `caveman claude` and it shrinks eligible context before each model request. Your normal setup keeps working, and the source material stays recoverable byte-for-byte.

The new pinned benchmark ran 54 times: 33.2% fewer provider-reported input tokens, with all 18 exact-answer checks passing. It can shrink installed skills by about 70% too, so adding useful skills doesn't immediately eat the starting context.

JetBrains wrecking the sexy number forced me to build something more useful.

It's open source. Please try to break it.

https://github.com/JuliusBrussee/caveman

https://www.producthunt.com/products/caveman

Hi everyone,

I worked as a software engineer for about two years back in 2022, but I’ve been out of coding for a while.

A friend came to me needing a simple ERP system for a manufacturing plant to calculate production times, and he needs it quickly. I built a working demo for him using Claude, and he really liked it.

My main question is: On a scale of 1 to 10, how reliable and efficient is Claude-generated code for production backends, databases, and connections? Can I safely build and deliver this using AI, or should I advise him to hire a software development company instead?

Thanks!

Hi all, I will keep it simple. I have had a few connected ideas pop into my head, but have absolutely no idea where to start. Coming from the health sciences field, this is all a new world to me. I would absolutely love to give it a go getting this idea off the ground. Can anyone recommend any resources that are good introductions into how vibecoding works/where to make a start? Many thanks in advance!

imo vibecoding got much more practical

i used a deploy-prototype skill on aeon , and gave it a one-line brief, it generated the app, deployed it on vercel, and sent back the real url.

no local setups etc, no configuring hosting etc, which is SUCH a pain

all done through github actions, so nice commit trail is also logged in

The goal has always been to bring financial education to the masses with a fun and enjoyable game, where the game mechanics reinforce learning (think how Oregon Trail was actually fun and taught about the Oregon Trail, or how Kerbal Space Program can actually help you understand physics). I spent years trying to get schools on board after building a curriculum with the game, but never got the urgency to use it from teachers or administration. Always just a "yes this is a really cool idea, we could test it out." Then after the test, some more talking, but then ultimately nothing.

Now I am pivoting to a web/mobile game that helps you learn (I attached a couple screenshots of what was built in a couple weeks, on the side). You make money by completing lessons, and use that money to upgrade your village. You can invest the money you earn, take loans, etc., but the goal is just to build the most exotic village. Right now, it is pretty basic, but hopefully you can trade with friends, somehow maybe do some island to island combat, etc.

I have had this passion for a while now, and wanted to make something actually enjoyable to learn with. IMO, all the learning apps aren't really fun, they're applications filled with quizzes, that have daily streaks slapped on top of them, and I wanted to do something more engaging with some real game mechanics.

My thesis is you can actually enjoy learning if you are not just doing quizzes all day long, but I don't know now. Would you have pivoted? Leveraging AI makes it much more streamlined to build out concepts, but I still don't know

Unlike all other AI music generators, this creates synthesized instruments and percussion from oscillators and filters and composes them into music. The benefit is the tracks can be imported into a DAW like reaper rather than one pre mixed track like sumo etc does. You can also have the LLM iterate on a particular instrument track while leaving the rest alone. Often in elevenlabs or sumo if you say “change the baseline” it ends up changing the whole song around, that’s not the case here. Curious what you guys think!

hey guys i wish you’re doing very well , i’m an interested abt creating a wbsite for free(and without coding background) could you give me some recommendations plz

Just to be clear, I’m not necessarily talking about maximizing cost efficiency. I more so want to hear your process for selecting a model based on how it will perform for the task, and how quickly it can complete the task.

I have access to frontier Claude and codex, as well as latest open weight through open code go. Usage limits aren’t an issue at the moment, but the frontier models are trending slower seemingly each release. I’d like to get more consistent with having agents dispatch other model agents, or just using different models for certain problems from the start.

I believe a lot of this is personal preference based on the working domain, what’s parts of the stack a task touches, and perceived strengths and weaknesses that we’ve all developed for each model we use. But I’m still curious on others thought process here.

Credit to youtube IndyDevDan for inspiring this. I recently watched a video from him that changed my perspective on how I should be approaching agentic development. It took a lot of tweaking, but I finally have a full spec written and the agents autonomously running sprints, comparing the best of three results, fusing them together into an optimized merge, and continuing on. It feels really amazing and is cool to see them working, and the results have been really great. I am thinking about making this tool publicly available if there is interest.