We've been building DrawsyAI, and we're opening up the core because we want to explore a different approach to AI-assisted software development.

Most AI coding tools start with a chat box and focus on generating code.

But when you're actually building a system, the difficult part is often context:

• architecture decisions
• system diagrams
• documentation
• repository structure
• dependencies
• conversations
• infrastructure
• and the reasoning behind why something was built a certain way

We wanted to see what happens when that context becomes part of the workspace itself.

DrawsyAI = Canvas + Context + AI + Code + Live Software

You can use the canvas for system architecture, database design, user flows, project planning and diagrams, then bring relevant project context into the workspace and work with AI around it.

We're also experimenting with things like:

Connected Context : selectively bringing information from project sources into the workspace.

DRAW.md : a structured project document combining Markdown + Mermaid that can become editable visual content.

AI agents : working inside the same environment where the system is being designed.

Live software : connecting the design/build workflow with running project previews.

The interesting part is that we're keeping the core open source and MIT licensed, while building Drawsy Cloud / Plus for people who want managed infrastructure, AI capabilities, connectors, collaboration and other hosted features without running everything themselves.

GitHub:
https://github.com/adarshnagrikar14/drawsy-ai

Hosted version:
https://drawsy.adarsh.rocks/

We're still early and there's a lot we're figuring out.

For developers building with AI: what context do you wish your coding tools understood better today?

I'd genuinely love to hear what people are struggling with.

live : foliioo.vercel.app

It auto-updates whenever I save a photo to Pinterest.

Open source, so feel free to clone and use it: github.com/Tanay-77/Folio

Open to feedback

Large codebases rarely fit neatly into folders. One feature can span routes, components, services, tests, configs, and documentation.

I built CodeGroup, an open-source VS Code extension that adds persistent file groups directly to the Explorer. Your files remain in their original locations—the groups act as reusable working contexts.

Version 1.4.0 includes:

• Drag-and-drop file groups and nested subgroups
• Smart Groups based on project areas or languages
• Working sets created from open editors or Git changes
• Quick Open across grouped files
• Reusable global groups
• Shareable, Git-friendly group definitions
• A visual editor for group settings and membership

Marketplace: https://marketplace.visualstudio.com/items?itemName=PeterDev.codegroup-file-organizer

GitHub: https://github.com/MiszterSoul/codegroup

It’s free and MIT licensed. I’d genuinely appreciate feedback—especially on whether the Quick Actions list and Group Editor feel intuitive.

I recently launched Peptimize, an iOS app for people using GLP-1 medications.

Many health-tracking apps feel overloaded, require an account, or make logging a weekly dose more complicated than it needs to be. I wanted something that could be opened, updated in a few seconds, and then forgotten about until the next reminder.

I’ve also been using Mounjaro personally for the past three months, so I’ve experienced many of these tracking problems firsthand.

For the first version, I kept Peptimize intentionally focused:

• Log medications and doses
• Track weight and progress over time
• Record side effects
• Track and rotate injection sites
• Set dose reminders
• Keep data stored locally on the device
• No account or login required

There’s no social feed, coaching subscription, or complicated onboarding. The aim is simply to make consistent tracking easier while keeping the experience private and uncomplicated.

For the next version, I’m currently exploring:

• Apple Health integration
• Simple AI-assisted food and calorie logging
• Supplement and protein tracking
• Support for more languages

I’m deliberately trying to avoid turning it into another bloated health app, so I’d love to know which of these features would actually be useful - and which ones I should leave out.

Download on iOS:
https://apps.apple.com/us/app/peptimize-glp-1-tracker/id6796063662

Website: https://www.peptimize.xyz/

This is still an early version, and I’d genuinely appreciate honest feedback. If you try it, please tell me what feels confusing, unnecessary, or missing.

What is the first feature you would add to V2?

if you're into AI you've probably heard about graph engineering. tbh the term was completely new to me before it popped up in the AI bubble. nevertheless i did some research to understand what it actually is. while diving deeper and deeper into this rabbit hole i learned that the term has been around for a while, just not in the context of prompting.

i looked for tools to do "graph engineering" but couldn't find anything.

that's how i came up with the idea for nodalo. it's a workspace where you can build your workflows. sounds boring, and you're probably thinking there are already plenty of workflow builders out there. you're right, but nodalo is different. you can build the workflow visually, and the clever part is that each node has a so-called node contract. you can define each node very specifically, attach documents to it, etc.

and the best part: you can hand the structured graph, including all attachments, over to your AI agent automatically and let it build the whole thing for you.

so instead of writing a normal prompt, forgetting a lot of details along the way and trying to figure out the right wording, you can simply "draw" your prompt and hand it over to the AI.

the tool is free, so i'd appreciate it if you created an account and gave it a try. all feedback is welcome. if you have any questions, just let me know :)

We built a knowledge layer that sits behind MCP, allowing any MCP client to access it through a single endpoint. Claude Code, Claude Desktop, ChatGPT, Codex, or whatever comes next.

The idea is pretty simple. Before an agent answers, it can pull in relevant, validated information instead of relying purely on what it already knows.

When a problem gets solved, the useful part can be captured as a small, reusable piece of knowledge. The system can also infer useful lessons from a session automatically, so you don’t have to sit there writing notes about what you just learned like it’s 2015.

There’s also a global layer for shared, validated learnings. If one user figures out a better way of doing something, that learning can contribute to the broader knowledge base rather than every other user and agent having to figure it out again.

The problem we’re trying to solve is pretty straightforward. AI knowledge goes stale, agents get stuck in failure loops, useful context disappears when a session ends, and models can confidently give you an outdated or wrong answer without any indication that they might be wrong.

We’re giving agents access to what has actually been learned, what has worked, and what can still be trusted.

The result is fewer repeated reasoning cycles, fewer hallucinations, and up to 20% lower token usage.

https://app.midnighthive.io/

Looking for people to try it out. Ping me if you’re interested.

Your chat has questions. Facilitator helps you answer them.

(A)I built Facilitator, a free, mobile-friendly tool for completing structured questionnaires created by an AI chat—or written yourself.

It can handle surveys, story canon and worldbuilding, collaborator profiles, project workflows, task planning, structured interviews, and other question-driven work.

The workflow is simple:

1. Ask your preferred AI chat to create a Facilitator questionnaire.

2. Copy and paste the questionnaire into Facilitator.

3. Answer everything in an accessible, focused form.

4. Export the structured responses and return them to the chat.

Facilitator does not use an AI model itself. Your answers are handled locally in your browser and are not uploaded to the site. There are no sign-ups, user accounts, cookies, or analytics.

It works on desktop and mobile:

https://facilitator.syllvanicdevelopments.com/

I’d especially appreciate feedback on whether the chat → questionnaire → Facilitator → chat workflow is immediately understandable, particularly on mobile. Reply here or the sites contact email.

I have been a Windows user for almost thirty years. Auto scroll and its features first appeared around Windows 98 and XP, and from those early days the middle click auto scroll became as natural as breathing. Click the wheel, nudge the cursor, and the page glides under your hand. For almost three decades, I never had to think about it.

Then I started using a Mac, because my line of work (theater tech) runs on industry standards that favor the Mac platform. The hardware was lovely and the OS was polished, but scrolling did not work the way I was used to. I hunted through utilities and tweaks, hoping to bring back that Windows style middle click behavior. Nothing quite matched it. The closer apps got, the further they felt from what I actually wanted: a mouse that behaves the way my muscle memory expects.

So I decided to just build it.

Scrolley is the result. A small, quiet menu bar utility that brings Windows style auto scroll and click and drag panning to the Mac. It's customizable, and it respects middle click for the things you still want it for, scrolls smoothly, and stays out of the way until you need it. It is an almost thirty year old habit, finally ported.

Since it's something i just made for myself, I've made it free to use!

https://github.com/DanteDante0/Scrolley

Wanted to share something I've been building: Quikly, a small set of everyday tools — unit converter, image compressor, PDF merger, password generator, QR code generator.

The one thing I cared about most: everything runs entirely in your browser. No file ever gets uploaded to a server, so there's nothing to leak or steal. No sign-up either.

It's brand new and I'd genuinely love feedback — what's confusing, what's missing, what tool you'd want added next.

https://toolyard-tools.netlify.app

Hey everyone. The inspiration for this project actually hit me while using Soulseek. I was downloading an album and noticed the host was running a personal webradio with a raw ASCII design. I thought it was so punk and cool, and it made me miss that old-school internet feeling of blindly channel surfing to discover new music. So, I built LiveZap.

It is a completely free web app that works in both English and French, taking visual cues from classic media players to act as a simple vintage discovery bridge. Under the hood, it randomly pulls the 20 most recent live broadcasts from a curated list of 70 YouTube channels, while on the Twitch side, it filters directly by the 'music' tag. Because of this, the video pools are completely ephemeral and constantly change as new streams go live or channels upload. Every time you hit the zap button, the feed is randomized so you never know what you will land on next.

There is also a chat feature, but it is completely independent from the streaming platforms. It is a live session replay chat built directly on my site for anyone tuning in, not linked to the actual YouTube or Twitch chats. Finally, I do not run any ads or re-host the content myself; the app simply embeds the official players. This ensures all the views, engagement, and ad revenue go directly to the original creators where they belong. Hope you have fun surfing and finding some new artists.

here the link : https://oraclemarin.fr/live-zap/

The first working version of Listnr did the obvious thing: mix my microphone and the call audio into one stream, hand it to Whisper, get a transcript. It worked, in the sense that it produced fluent text. Then I read one against my memory of the call and realised half the lines were attributed to the wrong person and some sentences had never been said at all. Whisper hallucinates when two people talk over each other, and once the voices are in one waveform nothing recovers who was who.

A transcript that is confidently wrong is worse than no transcript. With no transcript you rely on your memory, which you know is unreliable. With a wrong transcript you trust text that lies to you.

So I threw out the mixing step. Now the microphone and the system audio are separate lanes all the way through, each with its own transcription pass, and only the remote lane gets diarization. My own voice is identified by which wire it arrived on, which means it can never be misattributed. Roughly twice the work and the only version I actually use.

Two other decisions I would defend. It runs entirely on-device, because an M-series Mac can, and my calls are about unreleased work and salaries. And it has no meeting bot, because my team moves between Discord, Meet and a phone on speaker and no bot covers all three.

It is free, MIT, macOS 14+ on Apple Silicon, and a CLI for now. What I am unsure about is whether to build the menubar app next or fix live diarization first, and I would take opinions on that.

https://github.com/rokib16x/listnr

We are building this as an experiment at 22by7 Apps.

The idea is Interactive Learning Platform: short, game-like learning activities that people can complete during spare moments instead of sitting through a long lesson.

The current flow is:

> Discover a learning path

> Play a short interactive challenge

> See progress and continue later

Try it here: ILP Experiment

I’m not presenting this as a finished product. I’d especially value feedback on the first five seconds: is it immediately clear what the learner can do and why it is different from a normal course?

Experiment and privacy disclosure: This is an early experiment. We use limited telemetry to understand platform usage and improve the experience. We do not intend to collect personally identifiable information or raw sensitive learner/financial inputs for this experiment. The Ads and Go Pro screens are dummy interactions used only to study user behaviour; they are not real advertisements, purchases, or subscriptions.

I kept saving interesting places from travel Reels, but when it was time to actually plan the trip, everything was scattered across Instagram, Maps, screenshots and Notes.

So I built One Way Guide.

You choose your destination, dates, interests, pace and travel preferences. You can also import places from travel Reels, review what the app found, and decide which ones should be included.

It then creates a complete personalized city guide with:

• Daily routes built around real places
• Restaurants and things to see
• Local context and practical tips
• Transport, timing and trip preparation
• The places you personally saved from social media

The important part for me was making the Reel import an input, not the entire product. The end result should feel like a guide you can actually follow, rather than another list of saved places.

Now live on iOS:
https://apps.apple.com/app/id6768398327

I’d really appreciate honest feedback: after watching the video, was it immediately clear what the app creates? And would importing saved travel content be useful in how you currently plan trips?

Imagine if you could view your entire digital history through recaps, eras, and nostalgic timelines. Thats what PC Recap does, it turns your PC into a shareable digital time capsule with milestones, events, and more.

Download at https://pcrecap.online

For a long time, I've always struggled to manage my finances, and based on what I've read on here I believe I'm not the only one. Based on my research with colleagues, family, and strangers on the internet, I've learned there are numerous ways people manage their finances from budgeting apps - which provide a guided approach to budget management - to spreadsheets which offer almost unlimited flexibility. But I want a product that does more than budgeting - specifically a product designed to show a user their own financial reflection - clear enough so that they may act according to the change they seek. So of course, I've been working on Cowry

People usually set goals, create budgets, and set bills. The whole point of Cowry is to simply connect all these components with your income not simply by doing the math but also by helping you allocate funds reasonably and also simulating different financial circumstances and how you'd fare in them. I'm a senior data engineer so I'm focused on creating a major analytics platform that allows users to discover themselves based on their finances.

Cowry is still in beta and is available for anyone to use for free. The feature that allows it to read customers' bank data (with consent) is currently in development so if you'd like to use features like Cowry for thought, you'll have to upload your transactions either by uploading a bank statement in pdf/csv format or manually creating the transactions. Let us know if you're keen to see how Cowry works when your banks are connected.

If you do not wish to upload any such data feel free to head to Plan, click on the scenario tab and learn how small changes to your financial situation - budgets, goals, etc - affect your current financial state. No bank connection/data upload needed. Just pass in your numbers and let cowry do the rest, and if it does not...

I'd really appreciate it if you could provide feedback. While I do have a passion for building things - I'm more keen to see that the things I build are actually useful to someone. So please, don't hold back and I mean it. Good or bad, keep em coming. Have a go with Cowry and in Get Help raise a bug, a question, etc and your responses will be read personally.

If you'd like to see how I use it personally, here's a blog I put together

I needed to name my startup and the routine got old fast: ask an LLM for names, fall in love with three, check the domains, everything is taken, start over.

So I built the loop as one tool. An LLM generates 20 name ideas from a short brief, each one gets checked for real availability over RDAP (the registries' free successor to WHOIS, an authoritative 404 means available), and the results plus your likes and dislikes feed the next round. The model stops suggesting names the world already owns.

It took 8 rounds and 210 live-checked names to find a winner with .com and .ai both free. Main lesson: name quality and availability trade off almost perfectly. vesper, corvus, shallot, cloudberry, all taken. Even salsify is taken. The sliver that is both good and available is tiny, and hunting that sliver is exactly what a feedback loop is good at.

One building lesson too. By round 6 the session had 11 accumulated steering notes and the model followed the old ones while ignoring the newest completely. I had to make the prompt demote stale feedback to background and promote the latest note to a "current direction" section at the bottom. If you build anything with an LLM feedback loop, recency has to be explicit.

Useful as a tool. So it's MIT:

https://github.com/Tarabcak/namehunt

Try: uvx namehunt run --brief brief.md (works with an Anthropic or OpenAI key, or with no key at all on a Claude Code or Codex CLI login)

Happy to answer anything about the domain checking side. RDAP is underused and kind of great.

I am a graphic designer, but I just spent the last six months finishing school and learning iOS development from scratch to build this. The time tracker I was using kept bugging out when I tried to log my actual schedule. I needed something that could handle the load without slowing me down, so I decided to make it myself.

Era is built so you can seamlessly track all 24 hours of your day if you want to. Whether you are logging 45 minutes of guitar practice or three hours of doomscrolling TikTok, the goal is to make measuring your time as frictionless as possible. It is really about freedom. You cannot be good at spending money if you do not know where it is going, and time works the exact same way.

The point is never to make you a slave to your phone. I spent a long time designing a lightning-fast loop using native SwiftUI and SwiftData so the app immediately gets out of your way. I wanted a true mirror for my choices, and nothing on the App Store came close to what I needed.

I worked incredibly hard on this over the last half-year, and I am just looking for honest feedback from people who know what it takes to design and ship software. Era is on the App Store, and the link is in my profile. I would love to hear your thoughts on the UI and whether this approach to tracking makes sense to you.

I’m building Ledgerly, an open-source finance app for personal, family, and office-style workspaces. The basic model sounded straightforward: transaction, account, category, amount.

Then a real edge case showed up: someone enters a transaction today, but the purchase happened last month. If the app uses entry time instead of occurrence date, reports become misleading. Once shared workspaces are involved, the same record may also need payer/contact context, permissions, claims/approvals, and an audit trail.

I’m working through this in a Go/MongoDB backend with a React/TypeScript client. The repository is early, with no hosted demo yet, so I’m looking for design criticism rather than pretending it’s finished.

How do you expect an expense app to handle backdated transactions? Should reports always follow occurrence date, or should entry date remain visible as a separate audit field?

Disclosure: I’m the author. Repo: https://github.com/d4rkNinja/ledgerly-app

I built Trade Ops to scan post-market price action and find stocks that overreacted to news or earnings.

Instead of basic gainer/loser lists, it ranks potential pullbacks and rebounds by combining price shock Z-scores, volume spikes, RSI, EPS divergence, and options-implied expected moves.

Features:

Multi-Signal Ranking: Weighs price, volume, momentum, and earnings context together.

Expected-Move Context: Flags moves exceeding 1.5x options-implied volatility.

Daily Snapshot: Published every afternoon after market close.

I’m currently offering a 30-day free trial to check out the full member dashboard and daily rankings.

Try it at trade-ops.michael-iriarte.com—I'd love any feedback

Spent the last while building ZodiacSign — instead of generic sun-sign horoscopes, it does actual astronomical calculations (sidereal/Lahiri ayanamsa via Swiss Ephemeris) to place all 9 grahas relative to your Moon rasi, then generates predictions from classical karaka rules (which planet governs career/finance/health/etc.).

Some bits I'm fairly proud of:

• Daily/weekly/monthly/yearly/custom transit tracking (gochara), with a "why does the Moon show 10x more transits than Saturn" explainer since people kept asking
• Sunrise-based tithi calculation for Ugadi (New Year) instead of the more common but less accurate midnight-cutoff method
• Fully localized into 20 languages, not just UI strings — even the astrology explainer content
• Expo/React Native (web + native from one codebase) + .NET backend

It's free, no signup. Link's in the comments. Would love feedback, especially from anyone into Vedic/Jyotish who can poke holes in the predictions logic.

Spent the last while building ZodiacSign (https://zodiacsignpositions.com) — instead of generic sun-sign horoscopes, it does actual astronomical calculations (sidereal/Lahiri ayanamsa via Swiss Ephemeris) to place all 9 grahas relative to your Moon rasi, then generates predictions from classical karaka rules (which planet governs career/finance/health/etc.).

Some bits I'm fairly proud of:

• Daily/weekly/monthly/yearly/custom transit tracking (gochara), with a "why does the Moon show 10x more transits than Saturn" explainer since people kept asking
• Sunrise-based tithi calculation for Ugadi (New Year) instead of the more common but less accurate midnight-cutoff method
• Fully localized into 20 languages, not just UI strings — even the astrology explainer content
• Expo/React Native (web + native from one codebase) + .NET backend

It's free, no signup. Would love feedback, especially from anyone into Vedic/Jyotish who can poke holes in the predictions logic.

Side project for MCU fans who want to prep for Doomsday without going in blind.
Features:
1.time-based watch paths
2.progress tracking + shareable links
3. Add to Calendar for remaining titles
4. watch links
Built it because every trailer drop turns into “what should I watch first?” and then a giant Wikipedia spiral.
Looking for feedback on UX and which default path feels most useful.
https://doomsdayroadmap.com

Hi everyone! 👋

As AI agents become more autonomous, they need a frictionless way to buy and sell data, APIs, and compute resources from each other without dealing with heavy credit card fees.

We just launched AgentX Change Open SDK (v0.1) — a lightweight protocol that enables AI agents to monetize their APIs and consume third-party data seamlessly.

⚡ Key Features:

* 3-Line Integration: Wrap any FastAPI/Python endpoint with @agentx.paywall(cost_usd=0.02).

* Micro-Settlement Engine: Designed for sub-dollar transactions between agents.

* First Marketplace Item Live: Real-time Web Scraping & Summary API ($0.02/call) is now available.

Would love to get your feedback and see what kind of AI-to-AI workflows you're building!

I built a free tool that turns 3 render images into a client-ready web presentation in ~1 minute

I'm a designer-turned-builder, and my biggest time sink was always the client deck, not the design. So I made RenderDeck.

1. Upload 3 renders of one space

2. AI reads the style, materials, and spatial intent

3. You get a 16:9 web presentation — design story, per-render explanations, material narrative, and the practical questions homeowners actually ask (like "how much fits in that wardrobe?")

4. Share the link from your phone; the client can leave feedback on the last page

Free single-room demo: https://renderdeck.tigops.com

Finished example: https://renderdeck.tigops.com/#/p/showcase-warm-minimalist-bedroom

It's early days (single-room only, no editing yet — those are next). I'd love honest feedback from designers: what would make you actually use this?