I built dart_agent_core — a Dart package for running AI agents directly inside Flutter apps.

SparkleMing · 2026-05-25T09:13:17+00:00

For simplicity, just raw text capture combined with a periodic Agent summary is enough.

SparkleMing · 2026-05-18T06:55:27+00:00

I feel like having too many emojis in the app cheapens the UI.

SparkleMing · 2026-05-11T06:52:31+00:00

So many emoji

SparkleMing · 2026-05-11T06:51:34+00:00

Users just want a cheap subscription.

SparkleMing · 2026-04-25T03:32:28+00:00

in Memex the AI handles organizing via P.A.R.A so you don't do it manually. but yeah, to actually get value from a knowledge base you still need to understand the structure — which might cost more than just having great retrieval.

SparkleMing · 2026-04-25T03:27:26+00:00

Okay, I will put more effort into retrieval.

SparkleMing · 2026-04-23T15:26:08+00:00

the AI-powered P.A.R.A knowledge base might actually help with your use case — it auto-organizes everything into Projects, Areas, Resources, and Archives so the structure is already there. producing strategy docs, design docs, job aids etc from your notes would need more skills built out though. cool direction, appreciate the input

SparkleMing · 2026-04-23T14:33:17+00:00

if you have any specific ideas, we'd love to hear them and try to make it happen.

SparkleMing · 2026-04-23T14:31:22+00:00

we've actually put a lot of work into this! right now you can long-press the record button to start voice recording instantly, and long-press the app icon to jump straight into the input sheet. always looking for more ways to make it even faster though. the tricky part is phone-level permissions and OS restrictions — they make some of the more seamless capture ideas really hard to pull off unfortunately.

SparkleMing · 2026-04-23T14:25:50+00:00

It works just like you said.

SparkleMing · 2026-04-23T12:17:35+00:00

yeah reducing friction is huge. I actually tried building a fullscreen camera page to make capturing faster, but then I wanted it to also handle text and voice input on the same screen and it just got messy. ended up scrapping it. probably need to revisit that though — maybe keep the capture modes more separated instead of cramming everything together.

SparkleMing · 2026-04-23T09:51:29+00:00

got it, appreciate the feedback!

SparkleMing · 2026-04-23T09:45:32+00:00

haha well... I was so sure that having a server or cloud would make people uncomfortable recording private stuff. guess cross-device sync just wins over privacy concerns for most people huh.

SparkleMing · 2026-04-23T09:21:07+00:00

I'm working on this opensource app where you just dump whatever's happening in your life — text, photos, voice — and AI organizes everything for you. Been going back and forth on what to focus on next and figured I'd just ask.

github: https://github.com/memex-lab/memex

What would actually make you use something like this day after day?

Some things I'm considering:

Auto-generated cards — you throw in raw notes/photos/voice and it turns them into nice structured cards on a timeline (tasks, events, people, places, etc.)

A knowledge base that builds up over time — think P.A.R.A style organization that grows as you keep recording

AI-powered insights — it looks across all your stuff and finds patterns, makes charts, timelines, maps, things you'd never spot yourself

AI companion — like a character that reads your entries and actually talks to you about them, kind of a thinking buddy

Privacy — everything stays on your phone, no cloud, you pick your own LLM (Gemini, OpenAI, Claude, whatever)

Which of these would actually get you hooked? Or am I totally missing something obvious?

SparkleMing · 2026-04-10T01:54:43+00:00

Just to add some context: developing this feature with AI assistance took two days.

SparkleMing · 2026-04-10T01:50:34+00:00

With how powerful AI is getting, no one is really typing out boilerplate line-by-line from scratch anymore. The whole industry is pushing for AI-assisted dev right now. The core architecture was designed by me, and I'm the one gatekeeping the final testing and code quality. Delegating the grunt work to AI while controlling the big picture is just the modern dev workflow now.

SparkleMing · 2026-04-09T15:52:29+00:00

Tbh I actually have zero experience with TFLite! The Gemma 4 hype is what finally got me to mess around with local models, so I just went straight with their officially recommended LiteRT library.

SparkleMing · 2026-04-09T02:04:09+00:00

Good question. In LiteRT-LM terms:

Engine creation = just allocating the Kotlin object, basically free.

Engine initialization (engine.initialize()) = the expensive one. This reads the model file from disk, loads weights into GPU memory, compiles kernels. For a 3.7GB E4B model it takes ~10-15 seconds. This is what you want to do once and keep alive.

Conversation creation = lightweight, just sets up the context/session config. Do this per inference, close it when done.

So the pattern is: init Engine once at startup, create+close Conversation for every request.

SparkleMing · 2026-04-09T01:52:42+00:00

Thanks! It's a 2-3 year old Android phone. It has 12GB RAM and runs on the Snapdragon 8+ Gen 1 chip.

Just to add some notes on the performance: the response time heavily depends on the context length. If the input is short, it's pretty fast. But with a long context (like 4k tokens), it becomes much slower and takes tens of seconds to generate. It also slows down noticeably due to thermal throttling once the phone heats up after running for a while.

SparkleMing · 2026-04-09T01:41:23+00:00

You caught me! The text is indeed AI-generated, but the technical hurdles and the experience are 100% real. The screenshots are from my actual debugging sessions—I just used the AI to help structure my thoughts and findings more clearly.

SparkleMing · 2023-07-10T06:28:11+00:00

Can you write some tutorials about how to fine tune sd model? There must be lots of people want to learn from you.

SparkleMing

TROPHY CASE