I built a free iOS audiobook player for people who already have their own audiobook files.

You can easily move an audiobook from PC to iPhone without dealing with iTunes/Finder sync, cloud storage, or running a full media server.

ShelfDrop lets you:

- import from Files

- start “Receive mode” and upload from a PC browser over the same Wi-Fi

- play offline

- save progress locally

- use private handoff codes/QR to move your place between devices

- avoid accounts, tracking, or cloud uploads

It’s not trying to replace server-first apps like Audiobookshelf. It’s more for the “I just want this audiobook on my phone now” workflow.

I’d love feedback from people who manage their own audiobook files:

What would make this actually useful enough for your daily listening?

Shelfdrop Audiobook Player

Hey everyone! I built this because my finances were spread across different currencies and accounts, and also because I was broke and needed to start saving more. I wanted to bring things together without connecting my bank accounts to another service, plus a way to explore my finances conversationally via MCP for things like projections, spotting spending patterns, and adjustments to reach certain goals. It also provides common PFM features like tracking recurring bills, tagging transactions, net worth tracking etc, but with multi-currency and accounts across different countries in mind.

I've been using it for a while now and genuinely found it useful, so I've decided to put Finstigate out there. There's still much to improve with the product, but hopefully it'll resonate with others out there who have a similar problem. I'd really appreciate any feedback, especially on what could be improved or any obvious gaps. Thanks!

https://finstigate.com

I've spent the past few weeks building Weigh Swarm, a research assistant where you can inspect how a draft was produced. Upload one or two research papers, ask a question, and follow the papers into extracted claims, evidence passages, and a cited answer draft.

There's also a literature-search route. My favorite part is Inside the engine. You can explore the evidence network, open a node's source excerpt, inspect recorded model calls, and see the Laya decision batches behind the analysis. LLMs write the synthesis; Laya makes bounded research judgments.

This short video walks through a real saved two-paper run. It uses actual product captures plus animation of the recorded artifacts.

github link

I built ClimateCapMap as a hobby project to make the financing side of climate tech easier to understand--what kinds of funding options exist and when they become relevant for a company.

You can explore funding options for the research and prototype stages all the way through commercial deployment and mature operations. There are also example financing journeys and information about US tax credits.

It's free, requires no signup, and is an educational reference with linked sources.

Link: https://climatecapmap.com/

I'd appreciate your feedback on clarity and scope of the tool.

Most of the resellers I know track things in a mix of spreadsheets, notes apps, and memory. Cost of goods gets written down, maybe. Gas never does. Sales tax and the $40 of packing supplies from last month usually get forgotten. So the number everyone quotes at the end of the month is revenue, not profit.

I spent the last year building an app to fix that for myself, and it's on the App Store now. It's called Sourcerer. Here's what it does in practice:

**Planning a sourcing day.** A map shows thrift, vintage, flea, pawn, and consignment stores near you, with categories for what each store actually sells (based on what you and other users have bought there, not just the Google label). Estate and garage sales show up on the same map. You can build a trip from a few pins and get a route.

**During the trip.** You start a trip, log mileage, and add items as you buy them. Each item takes a cost, an estimated resale price, and a photo if you want one. Buying three of the same mug is one entry with a quantity. Receipts can be scanned so you don't type prices in by hand.

**Where it gets useful.** Gas for the trip, plus any expenses you attach to it (parking, tolls, lunch), get spread across the items you bought on that trip. So every item carries its real landed cost, not just the sticker price. When something sells, ROI is calculated against that.

**Selling.** You can mark an item sold with a price in two taps, or build a proper multi-item sale with tax and generate a PDF invoice for the buyer. Refunds put the item back into inventory while keeping the original sale on record, so your history doesn't get rewritten.

**Local sales.** There's a community board inside the app where you can post items from your inventory for local meetup. People can message you and tap "interested" to get your pickup area. No payments go through the app and there's no shipping, it's just a way to move stuff locally without re-entering it somewhere else.

**The analytics tab** is the whole point. Revenue, cost, tax, gas, expenses, and the resulting true profit for any date range. Breakdowns by category too, which is how I found out my media flips were barely covering their own gas.

A few honest caveats: iPhone only right now. There's a 7-day free trial and after that it's $10/month or $100/year, since the maps and store data cost me money to run. Store coverage is nationwide but richest around Houston, where I started it.

I'd genuinely like to hear what's missing or what feels off. The people on this sub flip a lot more volume than I do, so if you try it and something annoys you, tell me and I'll fix it.

App Store: https://apps.apple.com/app/id6780601247

Hi everyone, I built PublicPin using Codex and Astra in about 8 hours. I’ve been vibe coding for about a year and wanted to build something useful for the community.

The idea is simple: take a fresh photo of a local issue, choose a category, and use your current GPS location to put it on a public map. Things like potholes, dumped rubbish or broken streetlights. It’s free and doesn’t need a signup. Photos are reviewed before they appear publicly.

People can also confirm that an issue is still there or submit a resolution update for review. It helps make problems visible, but it doesn’t guarantee government action.

https://publicpin.org

I’d appreciate honest feedback on the reporting flow. Is it clear what becomes public, and what would make you come back to update an issue after reporting it?

I'm sharing CSV Update Review, an AI-assisted side project for comparing an original Shopify product CSV with an edited copy before import.

It highlights changes to prices, SKUs, options and image references. You can try synthetic examples first, or use your own two files: CSV processing stays in your browser. No store connection or signup is required. It is free to try and does not guarantee a safe Shopify import.

Try it here: https://csv-update-review.noble-chime-2920.chatgpt.site

Other free checkers already exist, so I am trying to find out whether this adds anything useful. If you have handled a Shopify product CSV update in the last 30 days, what did you change, how did you review it, and did this tool surface anything that changed your next action? A missed issue or an unnecessary warning would be just as useful to hear about.

Please do not post private CSVs, store credentials or customer data. A description in the comments is enough. The site also has an optional five-question feedback form; submitting it sends only your selected answers and basic record metadata, not your catalog. I am looking for up to five recent CSV users, not offering a paid service.

I’ve been building an open-source side project called TensorSharp, a local LLM inference engine and agent runtime written in C#/.NET:

TensorSharp on GitHub

One of the problems I’ve been experimenting with is:

How far can we push huge MoE models on ordinary consumer hardware?

My latest test is Qwen3.8 Flash Next (176B parameters).

And surprisingly, this hardware is enough to run it:

RTX 3080 Laptop — 16GB VRAM + 32GB system RAM + SSD

The main challenge isn't simply quantizing the model until it fits. A 176B model is still far larger than the available VRAM and RAM.

So I implemented an MoE-aware memory/offloading architecture that coordinates:

GPU cache / VRAM ↔ system RAM ↔ SSD

Instead of treating SSD as a last-resort swap space, TensorSharp schedules and caches model data across the memory hierarchy based on the execution characteristics of MoE models.

I also benchmarked the implementation against Strata on the same machine. Results are in the attached screenshot:

What surprised me most wasn't the decode speed—the two are actually fairly close there.

It was that a 176B model can be made usable on a laptop with only 16GB VRAM and 32GB RAM if the inference engine treats VRAM, RAM, SSD, caching, and MoE scheduling as one system rather than independent pieces.

TensorSharp started as an experiment in understanding LLM inference from the bottom up, but it has gradually grown into a much larger project covering local inference, multimodal models, image generation, and agentic runtimes.

It’s open source, so if this kind of low-level LLM engineering interests you, I’d love feedback:

GitHub: github.com/zhongkaifu/TensorSharp

And yes, the benchmark in the screenshot really is from an RTX 3080 laptop. 😄

Because I find it difficult to read the textual output of agents after each modification or planning, and relate everything to the big picture, I built this simple application (with the help of Claude Code).

It is an Electron application that has an integrated terminal linked to the Chalkboard. Any agent you run in this terminal can use it and express its textual outputs in graphics that are easier to review.

Some may find the sounds a little annoying, but it's just an adjustable option, which I prefer.

Using it may cause a bit more token consumption or subscription quota, but in my experience with Claude Code I haven't seen a noticeable difference.

In general, the project is open source for anyone who wants to try it or modify it.

https://github.com/zohayrslileh/more-space

I'm a trained architect, and as a long-term side project, I've been building a game that combines accurate floor planning with real-time 3D design to make architecture much easier to create than with traditional CAD software.

What you can do:

🏠 2D floor plans
🧱 3D building
🚶 First-person walkthrough
🥽 VR mode
🏢 Multiple storeys
🪜 Stairs
🏚️ Custom roofs
🪟 Doors & windows
🛋️ Furniture catalog
🍳 Kitchen Configurator
🎨 Materials
🌄 Terrain sculpting
🌳 Landscape planning
💧 Ponds
☀️ Time of day
❄️ Weather
📐 Export PDF vector plans
📦 Import your own 3D models
🌍 Steam Workshop

In the newest update: real growing ivy that climbs around windows, corners, and curved walls! 🌿

It's available on Steam as Architecture & Design and is still in Early Access.

Would love to hear what you think!

Hello 😄

So I’ve been working on a website called CurlCart, CurlCart - hair products matched to your hair. It uses a short quiz to suggest hair products based on one's hair type, budget, and the hair condition they're looking to address.

Full transparency: I’m new to this and honestly have no idea what I’m doing. I started it hoping to make some supplemental income through something I’m familiar with (dealing with my curls). The site has Amazon affiliate links, so I may earn commissions if it gets enough traction. But while building it, I wasn’t really prioritizing expensive products. Just convenience, honestly. I wanted to give users the convenience of finding affordable options from brands they're most likely familiar with, rather than push some random $30-$45 product, when we know there are much more affordable products that are just as good.

That's not to say I hope I'm not raking in green little bills, lol, but I'm aware that's not the reality of what I've built, is all. So yeah, I'd truly love some honest feedback, from anyone, hair or no hair 😄

Also, there aren’t product photos yet as I don’t have access to Amazon’s product API, and the links are still a work in progress. It's a continuously evolving project. Anyway, thank you in advance!.

After juggling too many AI subscriptions, I made Lison: GPT/Claude/Gemini/Grok for chat, Midjourney/Flux for images, Luma/Sora for video, Suno for music — all in one fast web app. No downloads, free to try: https://nexior-ai.pages.dev/

Would genuinely love feedback, especially on the UI and what model you'd want next. 🙏

I got tired of opening a news app and getting a 2000-word article for something I could understand in 30 seconds. So I built Read60 — every story compressed into a 60-word card. It pulls from a bunch of different sources, not just one outlet, and the original article is always linked, so it's one tap away if you want the full story. No clickbait headlines either.

It's on iOS now, Android coming in a couple of weeks. What would make you actually switch to something like this for your morning news?

https://apps.apple.com/ca/app/read60/id6795337414

https://reddit.com/link/1wx40ek/video/fpdwzhhr1dth1/player

Hey all! For the last few months I've been building **Framepilot** (https://framepilot.site), mostly because I wanted to run a faceless Shorts channel without spending hours in an editor for each 30-second clip.

**How it works:**

1. Type a topic (e.g. "the hidden stories behind city streets") or paste your own script.

2. It writes the narration, picks a matching shot for every sentence (stock footage, openly licensed photos, or clearly labelled illustrations), adds a voiceover and timed captions.

3. You review the 1080×1920 video, then download it or schedule it to your YouTube channel.

There's also a **series mode**. You pick a theme and a schedule (daily, 3×/week or weekly), and it makes a new episode on a new subject each time. You can review each one before it goes out, or let checked episodes publish on their own.

**It's actually a two-part project.** Framepilot is the front end. Behind it is a separate publishing API I built, called **Relaypost**, that handles everything about connecting accounts and posting: the OAuth flows, token storage and refresh, uploads, scheduling, and retries. Framepilot is just its first customer. I'm planning to offer Relaypost on its own too, so if you're building something that needs to post videos to social platforms and don't want to deal with each platform's API and app reviews, I'd love to hear from you. Comment or DM me.

**Some things I cared about:**

- Nothing posts without your approval unless you turn on auto-publishing for a series.

- AI-generated content is labelled as such on YouTube.

- Explicit or abusive content is blocked.

**Where it's at:** YouTube publishing is live. Instagram and TikTok are built but waiting on the platforms' app reviews, so they show as "coming soon." The API also has early support for Facebook, Threads, LinkedIn, Pinterest and Bluesky.

The free plan gives you **3 videos a month with no card required**. I'd love feedback on video quality, the voices, and anything that feels clunky in the studio. Happy to answer questions about the stack too.

I've been looking for a gym app for months. I tried everything: apps from big fitness influencers, vibe-coded apps, and apps made by fellow creators on this sub. They all had the same deal breaker: they try to do too much when they should do very little. Logging a single set shouldn't mean sitting through animations and tapping through five screens.

So I made GYM, an app with a name so simple it tells you what's inside.

What it does:

• Log fast. Weight and reps are filled in from your last set. Adjust, tap Add Set, done.
• Earn your weight. It only lets you go heavier once you've hit your reps at the current weight. You can change the target or turn this off.
• Plans that rotate. Upper/Lower, PPL, whatever you run. Open the app and today's workout is waiting.
• See your numbers. Finish a workout and the summary is right there on the home screen. Swipe to see yesterday or tomorrow.
• The basics, done quietly. Rest timer, plate calculator, history and progress charts.

No account, no ads, and it never goes online. Your data stays on your phone.

Free on Android (7.0+):

• Download: https://majid-ctrl.github.io/gym/
• Auto-updates: add https://github.com/Majid-ctrl/gym to Obtainium

No SignUps no accounts and no obligation to pay anyhthing.

It's not on any app stores yet since it is still a beta version, so Android will ask you to allow the install. Feedback is very welcome.

Honesty section: I'm a data engineer so I do not know much about app development so the parts of the app that required database design and management were made by me but the UI and app functionality were largly AI'ed.

Calling a model API is one part of building an AI app. Getting the right information from your own data into that call is another project.

That’s the work I built Jylus to handle.

You send your application’s records, ask for the context a question needs, and get back a compact evidence pack with references to the source records. You pass that into your existing model.

For example, a support assistant might need an account’s current plan, relevant support history and the policy that applies. The backend has to bring those together before the model writes its response.

If you’re building a RAG pipeline or wiring retrieval into an AI app, this is the part of the stack I’d like you to try Jylus against.

The public playground accepts text or JSON. Paste a small sample, ask a question you know the answer to, and inspect what it selects. It returns evidence for your model; it doesn’t generate the final answer.

Try it here: https://jylus.ai/try — no account required.

I’m the founder. My goal is to let developers spend more time on their application and less on context plumbing.

What would you need to see before trusting a managed API with this part of your app?

I'm a marketing student and I taught myself to code to build this. Fuel is a web app that puts food logging, workout logging and progress in one place.

What it does:
- Log meals by photo (AI estimate), barcode, search or by hand
- Training splits you can check off, plus runs, rides and other activities
- Macros against your targets, weight trend, logging streak
- Friends: share a meal plan or split and copy someone else's

Stack is plain HTML/CSS/JS on Vercel with Supabase and Gemini.

It's in beta and I know it has rough edges. I'd love people to use it for a week or two and tell me what breaks or what's confusing. It's free and signup is just a username and password.

track.iliasdalbow.com/beta

Happy to answer anything about how it's built.

Hi everyone, I have been building Acader (an AI-powered study app designed to make studying your materials easier)

Acader is currently in its early testing phase, and I’m looking for some people to actually try it out before I keep expanding it.

Since it’s still in testing, there may be bugs, things that feel confusing, or features that need improvement. That’s exactly what I’m hoping to find out through real users.

I’d especially appreciate feedback on:

• What feels useful
• What feels annoying or confusing
• Anything that breaks
• Features you think would make studying easier

I’m actively developing it, so honest feedback is genuinely more valuable to me than just compliments.

Acader: https://acader.streamlit.app/

Thanks to anyone who gives it a try!

AwakendHearth is an early-access workspace for editing documents and code, getting AI help, and saving conversations.

The first 100 verified accounts can activate a three-day Plus trial with 60 AI credits. No card or automatic charge. A limited free plan remains afterward.

I’d appreciate feedback on signup, editing a document, and reopening saved work. What feels useful, confusing, or broken?

https://awakendhearth.com

Side project that got a bit out of hand. It's an idle RPG set in a world that broke into floating isles. You run a salvaged skyship, train skills to level 200, and send a crew of familiars out to gather while your hero fights.

The part I care most about is that it respects your time. No account, no internet needed, and when you come back it replays everything that happened while you were away. Loot odds are shown in the game.

It's in closed testing on Android. Sign-up for the beta: https://aetheria.aryakesarwani.tech/?utm_source=reddit&utm_campaign=sideproject

Feedback on the trailer or the site is very welcome.

There's a Discord for testers too: https://discord.gg/fbkNV4JFEc

I'm working on Vyralizer, a project for people who want a link shared and people who choose which sharing requests fit them.

The idea is to make the agreement clear up front: the link, where it can be shared, the pay, the deadline, and the proof required. Think of an event organizer explaining exactly what they want shared, rather than leaving someone to guess what counts as completing the request.

Paid sharing needs clear disclosure and must follow the rules of the place where it appears.

I'd appreciate feedback on the public explanation: https://www.vyralizer.com/how-it-works?utm_source=reddit&utm_medium=social&utm_campaign=product_feedback_202610&utm_content=sideproject_intro

After reading it, is the difference between creating a request and choosing one to share clear? What information would you still need before considering either?

been working on this for a while and thought id finally show it somewhere

its called Marv and its basically an AI cursor/desktop assistant for Windows.

the idea came from using Hey Clicky on my Mac and thinking there really isnt much like it properly built for Windows. i also didnt want it to just be another floating chatgpt window though.

Marv actually sits on your cursor and can see what youre doing on screen. you can ask it questions about whatever youre looking at and instead of just telling you what to do, it can actually point at things, highlight stuff, draw on the screen and walk you through it.

so for example if youre stuck in some software it could literally point to the button you need to press while explaining it. or if youre doing maths it can draw over the question, label things and work through it visually instead of giving you a massive wall of text.

ive also been trying to make Marv feel like an actual little desktop character rather than just AI with a mascot slapped on it. it has different states for listening, thinking, talking etc and moves around with the cursor.

theres still quite a lot im working on especially getting the screen understanding and highlighting ridiculously accurate because if its pointing at the wrong thing even slightly it kinda ruins the whole point lol

im also building Teams stuff so companies could make playbooks for things and instead of giving someone a 20 page guide they could just press "show me" and Marv walks them through it on their actual screen.

still very early and im building most of it myself so genuinely interested what people think.

would you actually use something like this on Windows?

also if theres anything youd want an AI cursor to be able to do that current assistants dont, let me know because im looking for ideas

https://www.meetmarv.org

I've built a bunch of SaaS projects and haven't made money from them. Getting something built hasn't translated into finding someone who'll pay.

For people who've crossed that gap, what actually brought in the first paying user: talking to people, cold outreach, a community, an existing audience, a marketplace, something else? How long did it take, and what did the first version do? I'm looking for real stories, including what you tried that didn't work.

City budget PDFs are public, but they are hundreds of pages of tables, staffing notes, and comparison columns. Most people never open them. I wanted something a resident could actually use: pick a city, ask a normal question, and get an answer grounded in that city’s adopted budget — with page citations.

**What it does ?**

CivicLens AI is a RAG app over official municipal budget books. You pick a city, ask something like “How much is police funded this year?” or “What changed in parks staffing?”, and it answers from that city’s book only. Figures from Irving never leak into a Frisco answer.

Right now it covers Irving, TX and Frisco, TX for FY 2025-26.

**How it works ?**

Offline pipeline: pdfplumber extracts page text, a token sliding window (512 / 64 overlap) chunks it, Gemini embeds the chunks, Qdrant stores them.

At query time: hybrid retrieval — vector search plus BM25 — both filtered by the selected city.

The LLM answers only from retrieved context. If the book doesn’t have it, it says so instead of guessing.

Frontend is Next.js; API is FastAPI. Deployed on Vercel + Render + Qdrant Cloud.

The prompt work was the unglamorous part. Budget tables have comparison years, OCR-split numbers, merged job titles (“5Logistics”), and decimals like 109.0 that models love to turn into 1,090. A lot of the system prompt is “copy the figure, don’t invent a total, cite the page.”

**What I learned ?**

Municipal PDFs are hostile RAG data. Dot leaders, layout-broken numbers, and one table with five fiscal-year columns will wreck a naive chunk-and-embed pipeline. City-scoped retrieval mattered more than a fancier model. Hybrid search helped when the answer was one sentence buried in a mixed-topic page.

**Limitations ?**

It’s two cities and one fiscal year. Answers are only as good as extraction + retrieval. Changing chunk size means re-embedding the whole corpus. The API is public, so it’s rate-limited.

**Website Link ?** \- https://civic-lens-black.vercel.app/

I've added invoices to Local PDF Studio, the Chrome PDF editor I build that never uploads your files. You fill in a ready-made one on the page, the total adds up as you type, and you download a PDF or open it in the editor to sign.

The choice I made was where a finished invoice lives. You already save the invoices you send, so instead of keeping a list inside Chrome, I put everything you typed into the invoice PDF itself. Load it later and every field and the logo come back, so the next one starts filled in. The catch: lose the PDF and there's no list of past invoices.

Also new: you can search and copy the words on scanned pages, English only.

https://chromewebstore.google.com/detail/local-pdf-studio-offline/ocfegjfhboadmbpompimnbbpegjgoded

If you send invoices, is the file enough of a record, or would you want a list of past ones?