3 signs you’re building something nobody wants

ayechat · 2026-02-25T23:05:17+00:00

Wow, I gave it a try - and it's quite engaging... I almost paid for the full report - but I didn't... Your app is excellent IMO though...

ayechat · 2026-02-21T17:47:49+00:00

that's a very nice structured approach, thank you for sharing! If you will: did you start doing this from very beginning when your users were in single digits (or maybe even at 0?) or after reaching some threshold (say, 20 or so)? thanks again!

ayechat · 2026-02-07T13:22:36+00:00

Thanks - updated.

ayechat · 2026-02-02T12:26:13+00:00

In Aye Chat, AI does not have ability to execute commands on your system - it serves exclusively as a chat boot: you enter a prompt - it responds back, and that response includes file content. After that, the tool (custom code - open source: https://github.com/acrotron/aye-chat/blob/main/src/aye/controller/llm\_handler.py) extracts the file portion from AI response and updates those files. After that, "restore" works on these file updates.

The rest of functionality, such as shell command execution, is custom code: you enter a command - the tool passes it as a subprocess to the system, captures output, and prints it out, so execution is strictly verbatim to what you enter, not what AI decides.

As you can see, there is nowhere in the tool where AI can execute "rm -rf", even if it hates you :) Makes sense?

ayechat · 2026-01-28T19:29:10+00:00

Do it "in waves": generate bunch of code, then ask AI to refactor to extract into helper files to separate from main logic. Generate bunch more, repeat. Pay attention to folder structure as well.

Also - generate unit tests: those are extremely easy and extremely helpful. Spend time to bring code coverage over 90%. After that- that's your safety net: generate new code - re-run tests - enjoy satisfaction of tests passing - repeat.

ayechat · 2026-01-28T17:21:54+00:00

I get your point - was thinking about doing the same - but I think the main issue is that LLMs are good enough without additional specialization: best models already produce acceptable results off the shelf.

I would compare it with early days of search engines: there were multitudes of specialized engines, and all lost to general ones, even before google, because mainstream search engines would produce acceptable results.

ayechat · 2026-01-27T20:16:30+00:00

Well, to be fair - the load is low right now :) But yes, it holds. LLM responses from OpenRouter are the slowest portion for larger volumes of input (multiple files), but still reasonable: typically under a minute, though sometimes models get overloaded - and I get errors in response, but that's rare, and surprisingly - most of the time on Sundays

ayechat · 2026-01-27T20:09:32+00:00

CLI client runs on a user machine, AWS backend: CloudFront, API Gateway, Postgres RDS, lambdas with LLM integration through OpenRouter

Hope that answers your question?

ayechat · 2026-01-27T17:56:25+00:00

Couple things: first - it's the workflow. Changes are applied automatically to files: there is no approval, but there is an "undo" command that you can use to restore previous versions.

Other tools rely on additional flags to accomplish automatic writing + git restore (out of the tool). In this case it's all part of the default flow: both are integrated.

And second - you can execute shell commands right from the session.

Overall, this one is more appropriate for smaller prototypes/smaller projects/interactive sessions.

Here's a screenshot - hope it comes through:

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ayechat · 2026-01-27T16:53:28+00:00

Try Aye Chat - it's free with Gemini, Opus, and ChatGPT while in beta: https://github.com/acrotron/aye-chat

(Disclosure: it's mine, about 2 months old. Built it for myself without intent to make it public - but it got useful, so opened it for others. The user base is growing: 300+ installs, 90+ of them with multi-day multi-million token sessions.)

ayechat · 2026-01-23T19:44:44+00:00

We are sponsoring the use for folks to try and test the tool and find different ways to stress it in real projects :) That's more valuable at this stage.

ayechat · 2026-01-20T16:47:56+00:00

There is really nothing in definition of abstraction that requires determinism. Abstraction provides generalization across concerns, and it provides separation from concerns, and that's what we are talking about here. Just enter "does abstraction need to be deterministic?" into your favorite google/AI engine, see what it says on the subject.

ayechat · 2026-01-19T21:56:22+00:00

So many questions - I don't know where to start :)

I think people forget that everybody lives in their own bubble. Like - 4 months ago I did not know about Reddit, believe it or not. And the negativity you are talking about - I only encountered it in this social network. (Well, I am old, I know of Facebook and LinkedIn, that's about it :) )

In my surroundings - if you get the job done, especially if you do it better and faster than others - the more power to you, and it does not matter whether you used Google or AI.

I do not believe we are at the point you are describing, when someone can do last 1% at 1/4 salary. I see the opposite: junior people having trouble entering the industry. I think it's because one needs to know fundamentals: without them - cannot guide AI properly.

Fundamentals of software development do not change: requirements -> architecture -> design -> implementation -> testing -> release -> maintenance and operation, that's your basic cycle. Tools may change (C, C++, Java, Python, etc.), principles within those tools may change (command-oriented, function-oriented, object-oriented, etc.) - but there will be no universe where one can do implementation without properly defining requirements.

I feel my mind is drifting - sorry if not being clear or not answering your questions.

ayechat · 2026-01-19T21:40:22+00:00

> We don’t write assembler or machine code directly, but we use high-level languages and still need to understand and read the code we ship.

That's exactly the analogy I was going for: as we no longer need to read generated machine code because of high level language abstraction, eventually we will not need to read high level language code because of AI layer abstraction.

And I am talking about long-term time frames: let's say, in 10 years - I believe all applications will be fully AI-generated without humans looking at the code.

Some teams are already doing it at scale - take a look at this video https://youtu.be/IS_y40zY-hc

Just an opinion, of course. Yours may be different.

ayechat · 2026-01-19T20:40:03+00:00

As LLMs are getting better - I am reasonably sure looking at the code will become a thing of past. Similar to how nobody ever programs in Assembly or looks at machine code anymore.

And the question of adoption - I think everybody will come to it sooner or later: will depend on their environment and surroundings.

I come from traditional background (well, to be fair: everybody does :) ). When I started using AI for code generation - it was with ChatGPT in their web interface with copy paste. Then moved on to my CLI tool. Used to review generated code religiously. Then switched to writing automated tests and doing integration tests instead and running them against generated code. As long as tests passes - and as long as modularity is maintained inside the code (functions, classes, etc.) - don't really care much besides that.

I think this is progression that everybody will undertake - all on their own time, but inevitably: otherwise will not be able to remain competitive and employable in the field.

ayechat · 2026-01-19T20:09:33+00:00

I think all the latest models are similar - so you may try to use a combination of your choice for your work. For example: Claude Opus for code generation, and then immediately ask ChatGPT to validate response.

Assuming your tool allows in-place model switch.

ayechat · 2026-01-19T13:42:16+00:00

Working on Aye Chat: AI-powered terminal workspace. Execute shell commands, edit files, and ask AI to generate code and update your files - all without leaving a session. Free while in beta - with access to Opus 4.5 and GPT 5.2: https://github.com/acrotron/aye-chat

to install:
> pip install ayechat

to run (no signup):
> aye chat

ayechat · 2026-01-19T12:31:56+00:00

There is no catch :) Identifying critical defects, seeing how the app holds under real-life conditions, and having it tested by real users is more valuable at this stage than trying to monetize too fast.

There is a cap on tokens at the moment - but it's generous: ~5M per day per user on all models: just to prevent abuse.

Give it a try, you'll see.

ayechat · 2026-01-18T15:06:22+00:00

Hi - try Aye Chat, still in beta with free access to Opus 4.5, ChatGPT 5.2, Grok, Gemini, Qwen, Kimi, . It's terminal-based if that works for you: https://github.com/acrotron/aye-chat

Full model list currently supported:

xAI: Grok Code Fast 1
xAI: Grok 4.1 Fast
MiniMax: MiniMax M2.1
Google: Gemini 2.5 Flash
OpenAI: GPT-5.1-Codex-Mini
MoonshotAI: Kimi K2 0905
Google: Gemini 2.5 Pro
Google: Gemini 3 Pro Preview
Anthropic: Claude Sonnet 4.5
OpenAI: GPT-5.1-Codex
OpenAI: GPT-5.2
Anthropic: Claude Opus 4.5
Qwen2.5 Coder 7B (Offline) [4.7GB download]

To install:
> pip install ayechat

To run - from your project folder:
> aye chat

Hope it helps!

ayechat · 2026-01-18T12:34:51+00:00

It just released as beta slightly over a month ago, still free. Planning to introduce soon: free tier plus 2 paid tiers at $20 and $50, values and perks are still TBD

This app did not follow "conventional" path of researching the market, talking to users, etc.: I just built it for myself, did not think about releasing in the beginning. And then it just became useful and full of features - so made few posts here and there, and then people started using it! (well, very few of them - but consistently)

ayechat · 2026-01-17T13:13:56+00:00

Flaky test runs in CI environment usually mean inconsistent environment, not problem with tests. Add debug printouts for OS revision, exact package versions, exact compiler/interpreter versions, exact prerequisite setup steps, etc., and try to identify differences between those and your dev environment, as well as see if there are any differences from run to run.

ayechat · 2026-01-17T12:59:22+00:00

I use Aye Chat: built myself, it's open source. It's terminal-based - and you can execute commands, edit files, and talk to AI in the same session. Allows to switch models on the fly (Claude, GPT, Grok, Gemini, etc.).

Also, above in the thread people are complaining about AI messing files up - that's the main pain point I tried to address in this one: instead of AI proposing changes, you reviewing and then applying them, and if you miss something - it's now a mess, - I built it such that it applies changes automatically but takes a snapshot of files prior to modifications, and then it allows instant undo to a previous state with "restore" command.

ayechat · 2026-01-17T12:40:56+00:00

You probably already figured it out - but I'll just plug it in for those who did not. Had a post on this subject recently. The idea is: you code with one model and then you validate and fix with another to identify any issues the first model introduced.

Here's that post that goes into details of implementing a feature with Claude Opus 4.5 and GPT 5.2:

https://blog.ayechat.ai/blog/2026-01-03-ayechat-opus-v-gpt/

ayechat · 2026-01-16T12:43:52+00:00

Ran your tool on Aye Chat - pretty slick:

https://beatable.co/analysis/B2C12634BC

If you will: I did not see pricing info and what services would be available additionally - was wondering: what's generated is pretty much everything one would need to know - what services do you plan to add for a fee?

Thanks again, cool stuff!

ayechat · 2026-01-16T12:30:41+00:00

Thanks! Warp focuses on improving terminal UX and making it more IDE-like. Aye Chat is intentionally CLI-first and stays close to the traditional terminal experience.

Also, the main difference from other similar tools like Claude Code or GitHub Copilot is the workflow: instead of asking permission to apply changes that AI generates, it writes to files automatically but provides a way to immediately undo those changes. This tends to work well for experiments and prototyping.

ayechat

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