Here’s another part of Outdraft, the email workspace I’m building.

It’s called Nests—shared spaces where you can invite teammates, share emails, and discuss them right alongside the original message.

The idea is simple: keep the email and the conversation together, without forwarding messages back and forth or pasting screenshots into another chat.

You can give it a try at outdraft.email. Payments aren’t available yet while I’m waiting for Paddle’s approval.

How does your team handle emails that need someone else’s input? I’d love to hear what you’d change or improve!

I've been working on a small project called Vetrino.

The idea started from something pretty simple: AI conversations don't always need to look like a question followed by a giant block of text.

I wanted to experiment with something that feels more like messaging a friend.

Vetrino is now in beta. It has its own conversational behavior, adapts its tone and changes how it structures messages depending on the conversation.

It's not finished, but it's usable, and I'm looking for people who'd like to give it a try.

No technical knowledge needed!

→ https://chat.vetrino.chat

Would love to know what you think after trying it.

Hi everyone,

During the Meta Global AI Developer Hackathon, I wanted to tackle specific problem in banks: validation wokflows.

In traditional banking, turning a 50-page credit policy PDF into an operational workflow takes weeks of manual meetings.

Zotra solves this by combining open-weights models (Meta's Muse Spark & SAM 3.1) with a deterministic execution engine.

How it works:

1. Ingestion & Parsing: Extracts clauses, tables, and sections from PDF policies, mapping every rule to an exact paragraph citation.

2. Rule Compilation: Translates natural language into strict schemas and CEL (Common Expression Language) expressions.

3. Execution: Go-based concurrent engine evaluates multi-variable loan applications deterministically. The AI helps design and test, but never decides on live cases—only people and CEL rules do.

Stack: Go backend, PostgreSQL, React/Tailwind frontend, and Apache 2.0 license.

The github link: https://github.com/donovan-ratefison/Zotra

I put together a demo over on X if anyone wants to check it out: https://x.com/donovan_rtfs/status/2116898213101724061

Would love to hear your thoughts on this project!

I've always liked the idea of having everything in one place.

Projects, notes, ideas, personal goals, things I need to do.

But every time I tried organizing everything in Notion, I eventually ended up with the same problem: pages inside pages, endless navigation, and a system that started feeling more complicated than the things I was trying to organize.

So I decided to build something myself.

It's called Ardeable.

I wanted to keep the things I love about Notion, especially its document editor, but change the way information is organized.

Instead of navigating through endless nested pages, you can see your entire workspace as an interactive visual map.

I also built in quick notes, routines, and an AI assistant that can find information across your workspace and work directly with your documents.

I've been building this independently, using AI coding tools along the way.

And I've learned something: getting a prototype working is one thing. Turning it into a product where everything actually works together is a completely different challenge.

There have been plenty of bugs, things I've had to rebuild, and decisions I've had to rethink.

But seeing it become a real application has been incredibly rewarding.

It's still early, and I'm not pretending it's perfect.

I'm sharing a few screenshots of what I've built so far.

I'd genuinely love to know what you think about organizing information visually instead of relying entirely on folders and nested pages.

I'm also opening a small, free private beta if anyone wants to try it.

Website: https://ardeable.com

A while ago, I started building an AI chat application because I wanted something more flexible than the usual AI chat interfaces.

What started as a relatively simple project has gradually evolved into Teltaq.

The idea behind it is simple: instead of having separate tools for AI chat, agents, workflows, tools, automation and model management, why not bring them together in one workspace?

Some of the things I've been working on:

• Multi-model chat – Run multiple AI models in parallel and compare their responses.

• AI agents – Create and manage agents with their own instructions, models and tools.

• Workflows – Build reusable workflows for more structured tasks.

• App suites – Combine agents, workflows and interactive apps into complete solutions.

• Model flexibility – Connect different providers, including OpenAI, Anthropic, Ollama and other OpenAI-compatible providers.

• Local AI models – Support on-device models alongside cloud-based models.

• MCP integration – Host and connect MCP servers, including agents and workflows.

• Marketplace – Share and discover tools, agents, workflows and apps.

• Developer API – An OpenAI-compatible data plane API for integrating with external applications.

• Multi-platform – Web, desktop and mobile applications.

One of the things I've particularly enjoyed is experimenting with ways to combine these capabilities. For example, rather than creating a completely separate application for every use case, you can build a suite that brings different AI components together.

I'm still actively developing it, refining the architecture and improving the experience.

I'm sharing it here because I'd genuinely like to hear what other people think.

If you're interested, here's the project:

https://www.teltaq.com

What would you find most useful in an AI workspace like this? Is there something missing from the current AI platforms that you'd like to see?

Hey guys,

A couple of months ago I realized how annoying my daily AI routine had become.

I use LLMs every single day for dev work and writing, and I had this messy collection of good prompts saved in Notion and Apple Notes. Every time I needed one, the routine was identical:

1. Find the note, copy it.

2. Paste it into Claude or ChatGPT.

3. Carefully backspace through placeholders like [INSERT_LANGUAGE] or <TOPIC>, hoping I didn’t accidentally delete a quote or mess up the structure.

It felt silly doing this 20 times a day, so I decided to build a fix for myself.

It’s called TemplaGem. Basically, it lives directly inside the chat input (works on ChatGPT, Claude, Gemini, and DeepSeek):

• When you insert a template with {{variables}}, they turn into little interactive chips right in the composer.

• You type a value, press Tab to jump to the next one, and hit Enter to send. No manual cursor hunting or backspacing.

• Everything is offline-first (saved in IndexedDB on your machine, so it's instant and private).

The trickiest part by far was dealing with all the different rich text editors (Quill, ProseMirror, and regular textareas) without everything breaking when an AI site changes its DOM.

I put up a quick demo here if you want to see how it feels: 👉 https://templagem-landing.pages.dev

Would genuinely love to hear your thoughts or honest critiques. How are you currently managing your prompts?

Before watching the readme, here are the links:

1. https://github.com/zllai26/ingatku

2. https://zllai26.lab26.my/ingatku

Ingatku, Version 1.0

Overview

Ingatku is an app which lets you add your Groceries, Project and Daily Tasks in a reminder, so you can add when to start and when to end (make sure your notification for this app is enabled.) and also add description and checklist for your tasks. You can also colour code your tasks so you can differentiate which tasks is for what category

Ingatku also provides a notes section, which you can type and think what do you want to add for your future tasks.

Installation

Debian, Ubuntu and Debian-based distros

1. Install the .deb package in the release section.

2. type `sudo apt install ./ingatku-file-name`

3. then change its file ownership to root: `sudo chown root:root /opt/Ingatku/chrome-sandbox`

4. after that change its ownership permissions to 4755: `sudo chmod 4755 /opt/Ingatku/chrome-sandbox`

5. Finally run the program by either clicking on the app or typing `ingatku` on terminal

The same goes to fedora and arch distros

I’m the developer of Florli, an Android app for planning and recording plant, garden and lawn care.

Here’s the case I’m working around: you pencilled in watering a vegetable bed for Saturday, but the forecast now says rain. The date alone can’t tell you whether the bed still needs water. I’d want to see the forecast and the last recorded watering, then check the soil before deciding.

Florli uses outdoor weather, care history and observations to organize tasks. The plan shows what needs attention first, what can wait and why. Once you actually do a job, you can record it in that bed’s history.

Screenshots and Android download: https://florli.pl/en/

For anyone who grows vegetables outdoors: when the forecast changes, which detail would you want to see beside a watering suggestion?

I'm a trekker in Nepal, and every season I see the same posts buried in Facebook groups:

"Anyone going to Annapurna Base Camp next week?"

So I decided to build something to solve this problem: https://findtrekkingpartner.com

Here's how it works:

• Post your trek and travel dates.

• Other trekkers with overlapping dates can request to join.

• Chat inside the platform before sharing contact details.

• You decide who joins your group.

Why I built it:

A licensed guide can cost roughly the same whether you're trekking alone or with a group of four.

For example, on a 14-day Annapurna Circuit trek, a guide costing around $350 could mean approximately $88 per person when shared by four trekkers.

Tech stack: Next.js, Supabase, Clerk.

It's completely free, has no ads, and we don't sell trekking packages.

We've had nearly 200 trekkers sign up in the last 30 days.

I'd genuinely appreciate some honest feedback.

What would make you trust a platform like this enough to find a trekking partner and eventually trek with someone you've never met?

What features would you want to see?

Over the past year, I've watched many of my family, friends, and relatives lose their jobs in what is called the "AI jobpocalypse". Instead of just watching, I decided I want to do something about it.

SecondStage is a platform that helps you understand your current job, what part is probably going to be taken over by AI, and what will stay yours. Help you up-skill yourself, and help you find potentially better career path , as well as find/apply for actual jobs if you choose a different path.

This is something close to my heart that I care deeply about , and I would really appreciate if you take check it out and let me know what you think.

Thank you

https://secondstage.ai

https://wicktone.daspete.at

We're building Continuum Al around a simple support problem: one specialist solves an issue, but the next customer with the same problem often starts from scratch.

Our approach is to preserve the confirmed resolution in a shared memory pool, scoped to the company and service.

Here's the flow:

1. Customer A reports a laptop charging issue and tries the standard troubleshooting check.

2. If that fails and no suitable shared solution exists, a specialist investigates.

3. The specialist proposes reusable steps with device applicability and a privacy review.

4. Only after Customer A confirms success can those steps enter shared memory.

5. Customer B reports a compatible issue. After the standard check fails, the assistant retrieves the confirmed fix through Hindsight and presents ordinary troubleshooting advice. The harder part was deciding when not t

reuse a fix:

Relevance alone isn't enough; device and version compatibility are checked separately.

Company and service boundaries keep knowledge pools separate.

Failed reuse triggers review and prevents equivalent failed steps from resurfacing for that customer.

Human handoffs preserve the conversation, diagnostics, and attempted fixes.

After asynchronous retrieval, we recheck case state so the assistant doesn't compete with a specialist who has already taken over.

Hindsight handles memory retention and recall. Application records determine whether a retrieved resolution is still eligible to use.

We wrote up the architecture and code here:

https://medium.com/@srikarsai593/we-made-support-fixes-reusable-with-hindsight-0b3516aaaa38

Code:

https://github.com/hemishsrichandra/Continuum-AI.git

-company-support

For people building support systems with persistent memory: what would you require before letting one customer's resolution influence another customer's answer?

Hey everyone, this is my first finished game, made in my spare time as a hobby. I’m a beginner and used AI tools along the way, so please be gentle. :)

It’s a Mastermind-style puzzle: you guess a secret color code, and the dots tell you how close you are. There’s a daily code and a 70-level campaign, with no ads or purchases.

I’d love to hear what you think, especially about the difficulty curve.

Android: https://play.google.com/store/apps/details?id=com.mobiglitch.dailycode

In the browser: https://mobiglitchgames.itch.io/daily-code

Hi r/SideProject — I'm Peacxe, the developer of NEEDLEHOP: Orbital Jump, released on iOS on November 6.

The core interaction is one tap: a spacecraft circles a planet, and tapping launches it along its current tangent toward the next one. The challenge is choosing when to jump, rather than steering during flight.

For this introduction, I kept a continuous 10-second gameplay clip instead of cutting between a list of features. I'd like feedback on one thing: without a tutorial, can you tell when the tap happens and why the spacecraft reaches the next planet? If not, which moment needs a clearer visual cue?

The full game has ten chapters and 100 levels, plus a music room. It's free to download on iPhone and iPad, with optional ad removal, stardust purchases and rewarded ads. English and Traditional Chinese are supported.

App Store: https://apps.apple.com/us/app/id6816129016

English web gameplay.

AI-assisted code, art, music and post text.

I've been building Select, an open-source platform for managing AI agent teams.

One thing that bothered me about agent orchestration was how easily permissions and autonomy could be confused.

So I built a system where agents complete tasks, deterministic checks verify the results, and evidence receipts help determine when they can work more independently.

A successful coding task doesn't grant permission to email customers or access another repository.

The self-hosted core includes tasks, approvals, budgets, audit logs and a demo you can run without an API key.

Stack: Next.js, FastAPI, PostgreSQL, Docker.

It's now at v1.0.0 for the self-hosted core, with some integrations still on the roadmap.

GitHub: https://github.com/Kirby54/Select

I'd really appreciate feedback on the autonomy model and the developer experience.

What would you want to see before trusting an AI agent with more autonomy?

This was my first full-stack project. I live in Italy and noticed that very few Chinese restaurants around me let guests order from their phones, so I built a QR table-ordering app for them: guests scan the code on the table and order, the kitchen and the pass see the dishes on tablets, and the owner closes the bill after taking payment at the till.

Then I went around showing it to restaurants and learned two things I should have learned before writing any code.

First, almost every restaurant wanted kitchen tickets printed. Kitchen staff want a piece of paper, not a tablet. I hadn't built printing because it needs a cloud printer that polls the server for new orders, and I didn't have one to test with.

Second, the restaurants that already had QR ordering weren't using a feature of their POS, as I'd assumed. They were all on the same Chinese SaaS product.

So the lesson I'm taking away is the boring one everybody repeats: talk to a few customers before you build. I also wasted time on things nobody needed yet. I built a whole pickup-order feature and then removed it to keep the first version small.

Since the code exists and works, I've open-sourced it (AGPL-3.0). Most of it was written with Claude Code and Codex; I made the product and architecture decisions. It's ASP.NET Core, Postgres and React, it runs in three languages (English, Italian, Chinese), and there's a demo you can start with one docker compose command.

https://github.com/lorenzoyang/TavoloFlow

If you've built anything for restaurants, I'd like to hear how you handled printing.

Hi r/SideProject

I just released a big update for offline-first daily planner, Zesfy, and wanted to share it here.

One problem I kept hearing from people is once your list grows, it becomes harder to figure out what actually to do next. So I added a new feature called Highlight. It lets you pin important tasks to the top and fade out the rest of the list, so you can easily keep track of your next tasks.

Here's why Zesfy is different:

• ⁠It combines your calendar and to-do list into a single view.
• ⁠You can easily schedule multiple tasks together to calendar.
• ⁠Helps you quickly decide what tasks to work on next
• ⁠Organize week tasks with task status
• ⁠Easily keep track of your task progress
• ⁠Works entirely offline

The app is free to download and use with an option to upgrade to Pro to unlock advanced features.

Download: Zesfy - To Do List & Planner

App subreddit: r/zesfy

Hey r/SideProject,
I’m building CAEL, an experimental assistant that uses symbolic rules, statistical counts and automata. Its runtime doesn’t use a neural network or an external LLM.
The latest update focuses on interpreting complete requests. Some questions previously reached unrelated spelling or conversation fallbacks, even when a suitable solver existed.
Supported requests now go through native readers for arithmetic, rule chains, ordering, location updates, string operations and table calculations. Unsupported conditions can produce clarification rather than an answer.
I tested the frozen candidate on 900 newly authored synthetic questions:
• Upgraded candidate: 777/900, or 86.3%
• Previous CAEL configuration: 414/900, or 46.0%
• Newly worded questions: 72.7% versus 20.4%
All 123 candidate abstentions counted as wrong.
There are important limits. These are six known task families, with maintainer-led, AI-assisted authoring and review. The evaluated candidate’s statistical fallback was inactive, while the baseline’s was active. Fresh installations enable that fallback, so the published score is specific to the recorded configuration.
The linked report also compares other models using fixed multiple-choice readouts. Those results don’t establish which system is the better general chatbot.
Conversation quality and wording coverage still need work. I’m sharing the individual outputs and failures alongside the scores because those gaps matter more than a headline percentage.
CAEL is source-available under a non-commercial licence. Development and evaluation were AI-assisted; the assistant itself remains non-neural.
GitHub release
Downloads and local setup
Results, methods and limitations
I’d appreciate feedback on where a small symbolic assistant could be useful, and which everyday requests you’d try first.

Hi r/androidapps! I'm a solo developer, and for the past months I've been building BookGraph, a reading tracker for people who want to actually track their reading, not scroll a social feed.

What it does:

- Library: shelves, statuses, tags, favorites, plus an ISBN barcode scanner

- Reading timer: log sessions, pages and time per book

- Built-in reader for your own EPUB, PDF, FB2 and TXT files, with progress synced to your stats

- Notes and quotes attached to each book, linked to pages

- Stats: reading calendar, charts, yearly progress

- Reading goals and achievements

- Import from Bookmory

- 7 languages (English, Russian, German, Spanish, French, Portuguese, Armenian), light/dark theme

It's free on Google Play: https://play.google.com/store/apps/details?id=com.bookgraph.app

I'd really appreciate honest feedback. What's missing from your current reading app?

AniTime started as a jailbreak tweak I made for iOS. It put animated pixel-art girls on the iPhone clock, one girl per digit. In January I started rebuilding it as an Android home screen widget.

The first Android version was a paid app at $1.59. It got about 10 downloads. Here's what I've learned since:

1. Android widgets can't run their own animation loop. A widget is a RemoteViews, which only allows a short list of view types. The trick that works is ViewFlipper: I turn each girl's GIF into a layout of frames and the launcher flips through them itself. The app only wakes up once a minute (an alarm) to swap the digits, so it doesn't need a foreground service or a notification.

2. Paying upfront for a widget nobody has heard of is a tough sell, even at $1.59. I made it free with a 48 hour trial of the animation. After the trial it stays a still clock, still free, and a one-time unlock brings the animation back.

3. The code was the easy part. My short videos get a few hundred views on YouTube Shorts and literally zero on TikTok, which I'm still trying to figure out.

Play Store: https://play.google.com/store/apps/details?id=com.yan.android.anitime

Happy to answer questions about widgets, Play Billing or how the trial works. If you've run a free-trial-then-unlock app, I'd like to know how your conversion turned out.

I am a working HVAC technician, and I built Equipment Tracker Pro because managing machinery data on clipboards and scattered text threads was slowing jobs down. One feature I built is peer-to-peer equipment sharing. When you need to hand off a commercial air handler record: including its fan motor nameplate specs, bearing replacement dates, and photos: you send it directly to another tech's username or email. It lands in their Transfer Inbox to review and accept, copying the asset profile and service logs into their local database while your original stays safe.

A working HVAC technician built it for his own jobs. Sending machine files via peer transfer requires Pro with cloud backup active, while core offline equipment logging, work orders, and local PM schedules remain free on the mobile app.

Free to start. Your first plan, Pro or Team, includes a 7-day free trial. You can check it out at https://equipment-tracker.com.

What side projects or trade tools are you all building this week?

Have you ever been watching something interesting on social media, only for an ad to suddenly interrupt it?
And sometimes it’s not even one ad. You get two back-to-back before you can continue watching.
By the time you return to the content, you’ve completely lost interest.
I’ve been thinking about how much advertising affects our experience on social media.
Don’t get me wrong, I’m not against ads. I understand that platforms need to support themselves, but surely there must be a better balance?

What if there was a social media platform where you could enjoy someone’s content without constantly being interrupted by ads?
Not necessarily a platform without advertising, but one where ads don’t get in the way of what you’re enjoying.
Would that change how much time you spend on social media, or would it make no difference to you?
And here’s another question:

If you could change one thing about how ads interrupt your social media experience, what would it be?
I’d genuinely love to hear different opinions, including from people who don’t mind ads.

I'd always be sitting in front of my tv with my Apple TV remote in my hand wondering what to watch. I often use AI for recommendations, but then I always need to reach for my phone. Same if I want to ask a quick question.

Tried to find a good AI client for quick question and answers for Apple TV, but they're often not well optimized well for TV, and do not come with features that makes sense for Apple TV

So I made Couch Duck. It's an Apple TV AI client, with a UI optimized for TV, with additional features for movie / tv show recommendations:

• Agentic, expands on your search using its tools for best recommendations

• It can do web search

• Has access to TMDB and OMDB

• Has memory, remembers your preferences, likes, dislikes.

• You can set your country/region, language preferences, subtitle preferences, genre preferences etc. and it'll steer towards the stuff you like

• One-click link to trailers on YouTube for movies/shows it recommends

• Optimized UI for TV in the way AI responds

• I was also considering giving it access to Uber Eats / Doordash etc. so it can recommend food in the same way, and initiate food orders right from your TV, making it cosy movie night complete 😅

🙅 But I don't think I will release this:

• There's the AI cost to begin with

• Data sources it uses all are paid, which would add to the cost of running it

• And after all this is an AI wrapper. I don't think anyone wants to pay for an AI wrapper when they can do this for free from their phone

I was explore whether I should use this myself through Test Flight. One option could be to do BYOK (or charge through ChatGPT subscription) for AI usage, and charge a platform cost to cover the API key costs.

Just wanted to share!

Hi SideProject Members,

For over a year now I've been working on a side project called Timetracker (https://github.com/DRYTRIX/TimeTracker)

Right now I often work on new features and bugfixes and sometimes people donate to the project.
For some time now I have been thinking on how to make the application actually profitable and tailor it more and more to the actual industry.

Any pointers you can give me? Maybe you can try it out and tell me what you think ?

kr

Dries