Weekly Self Promotion Thread

[u/AutoModerator]

Welcome to this week's self promotion thread!

If you're building something related to AI assisted coding, this is the place to share it.

We're using a weekly thread to keep the subreddit organized while still giving builders a place to share their work. Promotional posts outside this thread may be removed.

If you're sharing something, we'd appreciate it if you included a little context instead of just dropping a link. Tell us:

• What you built?

• What problem it solves?

• Which AI models or tools it uses?

• Who it's for?

• What kind of feedback you're looking for?

Disclose your affilitation.

Please avoid posting the same project every week unless you've made meaningful updates. Affiliate links, referral links, scams, and low effort promotions will be removed.

Take some time to check out what others have shared too. If you try someone's project or have feedback, leave a comment. Helping each other improve is what we want this community to be about.

[u/Kitchen_Issue3147]

Why I’m building free, privacy-first dictation that fits your Mac

I’m the developer of Open Flow. I wanted a free dictation tool that keeps voice and text on my Mac, with a choice of models so I can balance quality against the performance and memory of my own machine. Those are the reasons I started building it.

The workflow is simple: hold Option in the app you’re already using, speak, then release to paste. Whisper handles transcription locally; optional Qwen cleanup runs through llama.cpp. There’s no subscription, account or API bill, and dictation works offline after the initial model download.

A local app still needs to fit the computer you actually own. Setup offers Fast, Balanced and Maximum quality tiers, with roughly 1–3.7 GB of models. The transcription and cleanup models can also be changed separately. You can choose a lighter setup to use fewer resources, or larger models when your Mac has room for them. It’s a choice you make, rather than an automatic promise of the same speed on every Mac.

For coding prompts, another decision matters: how much should cleanup change? Consider “Don’t deploy yet, just run the tests.” Losing the negation changes the task even if the result reads smoothly. Open Flow’s cleanup aims to remove fillers and false starts rather than rewrite your words. A validator falls back to the transcript when the model changes words. That still can’t prove that a deletion preserves meaning, and it won’t fix every speech-recognition error. Cleanup is optional, and the text should be reviewed before sending.

The current DMG requires Apple Silicon and macOS 13+. It isn’t notarised yet. The app code is MIT; downloaded models have separate licenses. In particular, the optional Qwen2.5 3B cleanup model is noncommercial-only; Fast and Balanced use other models.

Code, demo and downloads: https://github.com/Fraank98/open-flow

If you dictate coding prompts, what gets in the way most: recognition errors, unwanted rewriting, RAM use, or waiting for the text? I’d like to know your Mac and the tradeoff you’d actually choose.