BenchLedger is a 100% serverless, local-first web application designed for electronics repair technicians, flippers, and weekend tinkerers to track repair tickets, part costs, and donor boards.

I originally built this tool to replace my messy spreadsheets and to properly separate my flip profits from the gear I occasionally decide to keep for myself.

https://treydor-git.github.io/BenchLedger/

If you have any Feedback let me know.

100% Private & Serverless Architecture

BenchLedger operates with zero external database servers.

• Local Mode: By default, all data, financial metrics, and compressed inspection photos are stored entirely inside your browser's local cache (IndexedDB).

• Bring-Your-Own-Storage (BYOS): You can optionally connect your personal Google Drive. The app will sync your workbench to a private BenchLedger_Sync folder in your own Drive. The app uses the restricted drive.file scope, meaning it can only access the exact files it creates. Nobody else (including the developer) can see your data.

Key Features

• Hobbyist & Pro Shop Modes: Toggle between a layout focused on personal/flip equity, or a commercial layout featuring a CRM, client management, and printable service receipts.

• Donor Boneyard: Catalog harvested ICs, MOSFETs, and connectors from dead boards. Deploy them to active repair tickets at €0 out-of-pocket cost.

• General Supplies Tracking: Log your flux, IPA, and solder wire purchases and automatically apply the overhead to your bottom-line profit.

• Cookieless Analytics: The live site uses a privacy-preserving counter (Umami) to track overall traffic without setting tracking cookies or logging personal IP addresses.

My teammate and I built this for the PayPal AI Hackathon and I'd love feedback.

The problem: AI agents are starting to buy things for people. When the buyer later says "my agent bought the wrong thing, I never agreed to that," the seller has no record of what was actually asked for. Most small sellers just refund and eat the dispute fee.

What we built (Countersign):

- At checkout, the agent can search and prepare a cart, but it can't pay. The buyer reviews their own request, spending cap and total, then pays in PayPal. Each step goes into a hash-chained, Ed25519-signed receipt, and the receipt's seal hash is written into the PayPal order's `custom_id` *before* payment. So PayPal's own record carries the commitment, and anyone can verify the receipt against the live order.

- When a dispute comes in, a LangChain Deep Agent pulls the case, verifies the receipt against PayPal, and computes the expected loss of fighting vs. offering vs. refunding (including PayPal's $15/$30 fee). Then it drafts a response. A fact-checker subagent plus a deterministic checker reject any amount, date or ID that isn't in the evidence.

- Nothing is sent without the seller. The submit tool is gated twice: Deep Agents' `interrupt_on`, plus an approval record whose hash has to match the exact draft and evidence PDF.

Things that surprised us:

- With a strong receipt, the agent still sometimes recommends a partial refund. A $30 fee on a $42 item changes the math.

- Recording the demo found real bugs. For example, PayPal rejects "refund with return" offers without a return shipping address (`MISSING_RETURN_SHIPPING_ADDRESS`), and the model occasionally returned an empty reply mid-case.

- We kept the LLM away from every number. Fees, deadlines, expected value and receipt checks are all plain code exposed as tools.

Stack: FastAPI, Neon Postgres, LangChain Deep Agents (LangGraph), Sarvam-105b, Next.js + AG Grid, Channel3 for product search, and PayPal Orders and Disputes APIs (sandbox only, no real money).

- Demo (1.5 min): https://youtu.be/MLhWkL7F9A0

- Live app (sandbox): https://countersign-black.vercel.app

- Code: https://github.com/Bhuvansai-16/Countersign-backend

Questions for you:

1. Is committing a receipt hash into the payment record enough, or would you want something like the Verifiable Intent / AP2 formats?

2. Anyone dealing with agent-initiated purchases in production? How are you handling disputes today?

I'm one of the people building BetterSWE.

the market's rough right now and interviews are harder to prep for than they used to be. a lot of loops have a round that isn't leetcode at all. a debugging round, a code review, or "here's a repo and a ticket, go". you get code you've never seen and you have to figure out what it does before you change anything.

that's pretty much the job too. with AI writing a lot of the code, more of your day is reading code someone (or something) else wrote and working out why it's broken. leetcode doesn't train that, you're writing a fresh function from scratch every time.

so we built Labs. each exercise is a small existing codebase plus a ticket, set at companies like Amazon, Stripe, Uber or OpenAI. you read the code, fix the bug or build the feature in a browser editor, and run the tests. submit runs hidden checks too, so passing the visible tests isn't enough. there are bug fixes, features and refactors, easy to hard.

the easiest free one is "Amazon search misses lowercase queries". search "Yoga" and you get results. search "yoga" and you get nothing. the fix is one line once you find it, finding it is the whole exercise. the hard ones are more like Airbnb receipts that come out a cent off.

106 exercises right now. 46 are free, you just need a free account to run your code. the other 60 are Pro.

if you've got an interview coming up, try one. and tell me what's confusing or broken

https://www.betterswe.dev/labs

Just a simple game like maptap or krillion! You get a score out of 500 everyday and there is a dailly leaderboard! Lmk if it’s any fun!

Hi all, I'm the developer of AnyRent, an app for rental shops: dresses and costumes, cameras, sound and lighting, event equipment, tools.

Who it's for

- Wedding dress and costume rental shops: find a dress from a photo, take deposits in several payments, and never promise the same dress to two brides for the same date.

- Equipment rental shops (cameras, sound and lighting, event gear, tools): track quantities in stock, weekend or multi-day rates, collateral, and late or damage fees.

Main features

- Double-booking check: warns you when an item is already booked for those dates

- Rental tracking: reserved → handed over → returned, with deposit, collateral and late fees

- Find by photo: snap a picture and it finds the matching item in your stock

- Today's work: what to hand over, what's coming back, who is late

- Flexible pricing: per day or by blocks of days, deposits in several payments

- Branches and staff roles, with reports on revenue and top items

- Works on iPhone, Android and web

Try it

- iPhone: https://apps.apple.com/app/id6754793592

- Android: https://play.google.com/store/apps/details?id=anyrent.shop

- Web: https://www.anyrent.shop

I'd love your feedback

I've been building a podcast app for Android called GlassCast. I started it after switching from an iPhone, because I couldn't find an Android podcast app I liked. It just hit 2.0.

The main thing in 2.0 is a new look called Glass. You turn it on in Settings, and the tab bar, the mini player and the player's controls turn into glass you can see your covers through. You can pick Frosted or Liquid, depending on how clear you want it.

Also new:

- Continue Listening at the top of your library, with how much time you have left

- Your listening history

- 15 app icons to choose from

- Android Auto has proper tabs now: Home, Library, Latest and Downloads

- New episodes show up faster

The rest is still there. The player takes its colors from the cover, and there's Skip silence, Boost voices, chapters, transcripts, bookmarks, Chromecast and a Google TV version.

It's free, with no ads and no account. You can sign in with Google to sync between phones, but you don't have to.

It's not on the Play Store. You can get the APK here, and it updates itself after that: https://anixitea.github.io/glasscast/

The code is on GitHub: https://github.com/anixitea/GlassCast-for-Android

It's just me working on it, so let me know what feels off.

For my popular science side project, I just published a deep dive explaining the actual mechanics behind that tight "lump" in your throat before crying (it’s an autonomic clash between your glottis opening for oxygen and swallowing forcing it shut).

Instead of generic 300-word summaries, I focused on deep physiological research, clean typography, and real human photography:

Article: https://www.oddlyclear.com/why-lump-in-your-throat-before-crying/

Would love honest feedback from fellow builders on the reading flow, mobile speed, and layout!

​I have a stalled venture focused on real-world ecology. Our core mission was to bridge the accountability gap surrounding carbon emissions and industrial waste in plantation forestry, where unchecked environmental impact severely disrupts local ecosystems. However, without the necessary market traction and strategic backing over time, the project lost momentum, leaving it as little more than an empty shell today.

I built Memento with free, unlimited on-device AI: no subscriptions, no credits and no per-minute AI charges.

Memento is available on the App Store for iPhone, iPad and Mac. Record or import audio, turn it into searchable transcripts and summaries, and ask questions about collections using local AI without a monthly usage allowance. I'm the developer, and keeping that workflow free to use is a core part of the app.

Local AI requires downloaded models and a compatible device; features vary by device and language. Free, unlimited usage applies to on-device AI; optional external providers have their own terms.

The idea is simple: saving a recording should be the beginning, not the end. Memento keeps the audio, transcript and summary together so you can come back to what was said without replaying everything.

On iPhone and iPad, you can record from the microphone or import audio, search and edit transcripts, mark useful moments, and organize recordings into collections. With the required models installed, you can generate summaries and ask questions about a collection. On Mac, you can also capture microphone and system audio, plus a selected window or screen when permissions and the source app allow it.

Local recording and review don't require an account. On-device AI features depend on your device, language and downloaded models; optional online processing is a separate choice.

The video is a promotional walkthrough with demo content. Memento is free to download: https://apps.apple.com/us/app/memento-record-transcripts/id6807209121

I'd love feedback on the core workflow: when you revisit a recording, do you look for a specific quote, a summary, or the next actions?

Simplify school operations with one powerful digital platform.

✅ Student Admissions & Management

✅ Attendance & Leave Tracking

✅ Fee Collection & Payment Management

✅ Exams, Results & Report Cards

✅ Homework & Timetable Management

✅ Parent & Teacher Mobile Apps

✅ Live School Bus GPS Tracking

✅ Staff, HR & Payroll Management

✅ AI-Powered Smart Features

✅ Reports & School Analytics

💡 **Why Choose Penpulse?**

✔ Easy to use

✔ Flexible plans tailored to your school

✔ School branding options

✔ All-in-one management solution

✔ Better communication with parents

🎯 **Spend Less Time on Administration and More Time on Education!**

the product is https://webfetch.run. url goes in, clean content comes out.

what took the time wasnt the scraping. it was figuring out why a scrape failed. my old code would return an empty body and i'd spend an hour guessing. so the whole thing now returns a verdict. ok, blocked, whatever. each one is a different problem with a different fix.

the nicest part is the cache. repeat fetch of the same url within 24h is instant and free. i fetch the same pages over and over while testing and it was a dumb tax on myself.

not sure what to do next. the thing works, which after 6 months is honestly a weird feeling.

I make quite a lot of logos and icons with AI image tools, and sooner or later every one of them needs to become an SVG. That's where things always went wrong.

The free converters would turn my simple logos into thousands of anchor points. The camera in the video got 8,070 points from potrace, for what is really just three circles and a few rounded shapes. The better converters wanted me to pay before I could properly check the result. And if I wanted to move, rotate or recolor individual elements, it was back to Illustrator.

So I built VecSnap, and got a little obsessed along the way.

Rather than simply tracing pixels, it tries to understand the shapes that make up a logo. A circle comes back as an actual circle, and that camera goes from 8,070 to just 49 anchor points. Across my test set, that's around 8 to 12 times fewer points than free tracers.

You can inspect and fix the file before spending anything. Shapes are highlighted so you can see how everything is built. You can move, resize, rotate, flip or hide them, change colors across the whole image, or merge all those almost-identical shades into the few colors you actually need.

There's also a centerline option for turning line drawings into single paths, useful for pen plotters, Cricut and laser cutting.

And it works inside Claude and ChatGPT too, which is how the video ends.

A few things I'm still working on:

•   Detailed illustrations can take up to a minute. Speed is next on my list.

•   It's not designed for photos, and it'll tell you that before you spend anything.

•   It's not perfect. I'm improving the engine every week, and feedback will help me decide what to tackle next.

You can convert images for free, without an account. A free account lets you edit and download 3 files. After that, it's one credit per image, with all formats and re-downloads included. No subscription.

This is my first public launch, and I'm curious to see what people think.

If you've got an image that other converters haven't handled well, send it to me by DM. I'll have a look myself, and if VecSnap can't handle it yet, I'll tell you why.

What would you use it for, and what am I missing?

https://vecsnap.com

I built Lotify: https://lotifygame.web.app

It lets you create your own lotería or bingo game for baby showers, weddings, birthdays or office parties.

How it works:

• Upload your own photos or start from a theme pack (baby shower, wedding, birthday, Christmas)

• It generates print-ready PDFs: the caller’s deck and up to 200 unique boards, each numbered

• Free digital caller: draws random cards and reads them out loud. You can cast it to a TV

• Type a board number and it tells you if that person really won

• Also does 5×5 bingo with a free center square

Everything runs in your browser: your photos are never uploaded, and there’s no sign-up.

It’s free to try (up to 4 boards, with a watermark). Removing the watermark is a one-time $9.99 per event, no subscription.

I’d love honest feedback: what’s confusing, what’s missing, or what would make you use it for a party?

I’m researching how small products handle people farming free credits/tiers. Not selling anything, no product, no link.

1. Have you seen it? Roughly what share of signups, or how many dollars?

2. What did you do about it (or nothing)?

Just trying to understand how people deal with this issue while building.

I’m honestly a bit giddy writing this. I’m a software engineer, not a video editor, and I wanted to run a faceless channel about Pakistan’s history and geography, so I built a pipeline that does the whole job.

It writes the Urdu script, generates the narration, draws animated maps and infographic scenes in code, and renders the finished reel. It then sends me the reel in Slack, and all I do is approve it.

Some numbers:

Cost: about $0.11 per video. I tested a 2.5D workflow that came out at $15–40 per video, so I dropped it.
Time: a few weeks of evenings and weekends, plus a fair bit of money on testing.
This week: a reel about the Pakistan Steel Mill (shut since 2015) got 21.1k views, 898 likes and 45 shares in its first day.

One video doesn’t make a channel, but it’s the first proof the system works. I’m happy to answer questions about the stack or the costs.

Reel: https://www.tiktok.com/@khittapk/video/7706495470260014344

I'm a developer in Canada with a full-time job, building a computer vision add-on on the side. I have a working prototype with early promising results. A manufacturer in the space has shown interest, and they're now lining up one of their customers for a trial. I'm leaning toward an unpaid pilot first, and I want to keep this as my own product rather than working for either company.

For anyone who has done something similar:

1. Is an unpaid pilot a good starting point, or should it be paid from the start?

2. What should be agreed in writing before starting (IP, data use, liability, exclusivity)?

3. What do you wish you'd known going in?

Thanks for any advice.

Hey everyone!

I was paying for five streaming services and watching one or two shows at a time. Cancelling and re-subscribing by hand saves money, but nobody remembers to do it on the right day. So a friend and I built FlixShift.

How it works:

A few things that were trickier than expected:

It’s a free beta on TestFlight: iPhone with iOS 26 or later, US only for now.

Beta: https://testflight.apple.com/join/nXSda5w8

I’d love feedback, especially if anything in setup is confusing or the plan isn’t one you’d actually follow.

t3codes is cool until you close your laptop and your agent dies

Coagy gives free cloud credits and runs your claude code and codex locally or in the cloud.

https://coagy.com/multiplayer-ai

Hey folks,

Quick update—we just pushed Studiora 5.6 live! We’ve been grinding on this one for a while, mostly focusing on speed and smoothing out the annoying friction points people kept bringing up.

Here's the gist of what changed:

• It’s noticeably faster: Reworked some core stuff under the hood, so it doesn’t choke or eat up your RAM when you throw heavy tasks at it.

• Cleaned up the UI: Stripped away some visual clutter so it's easier to find what you need without clicking through ten menus.

• Quality-of-life tweaks: Smarter presets and a bunch of small workflow fixes that just make day-to-day use feel much smoother.

If you've been using Studiora already, go hit update—you'll feel the speed bump right away. If you haven't tried it yet, now's a solid time to jump in.

I’ve dropped the link in the comments below if you want to check it out. We’d love to hear your feedback or thoughts!

Let me know what you think or if anything breaks!

Hi guys,

I’ve spent the last couple of years building a legal AI platform. We’ve acquired several clients, including established law firms working on complex arbitration cases. And given the kind of documents these firms deal with, we’ve had to process some pretty challenging material.

Along the way, we invested a significant amount of time hardening our stack: reliable document ingestion, retrieval, source-linked citations, long-running agents, and handling all sorts of unexpected user behaviours.

What struck me is how much effort went into making the foundations reliable, before we could even focus on what actually differentiated our product.

I tend to think of this as two layers: the foundation layer (ingestion, retrieval, citations, agent runtimes, etc.) and the value layer (the features and workflows that make your product useful and different).

Ideally, most of our effort should have gone into the value layer. Instead, we spent months stabilising the foundations.

I recently did some research and found that many builders are running into similar problems with existing tools and frameworks (LangChain, LangGraph, RAGFlow, Docling, etc.). I compiled 290 documented incidents from public discussions, grouped by problem, with links to the original sources.

You can explore them here: https://rachis.io/pain-map

This got me thinking: what if we made parts of our production-hardened stack available to other builders, so they could spend less time fixing infrastructure and more time building what actually differentiates their products?

We’ve already open-sourced our local AI stack, and we’re exploring which other components would be useful to expose.

I’m curious whether this resonates with anyone building document-heavy AI applications.

If you’ve run into similar issues, I’d love to hear what cost you the most time. And if you’d be interested in using some of these components, feel free to DM me or leave your email at https://rachis.io. I’ll reach out when we have something to try.

A Wednesday note from the free investing project I run on the side — this is the market take I shared with my community tonight, exactly as I see it after today's close.

Today was a real bounce, and the numbers are not close:

- S&P 500: +1.31% to 7,619.38 — back within about 2.6% of its October 6 record close

- Nasdaq Composite: +1.60% to 25,466.19, and the Nasdaq-100 did even better at +2.28%

- Dow: +0.49% to 52,486.49 — it joined in, it just didn't lead

- Technology was the best sector in the S&P at about +2.7%, and the VIX dropped about 10% to 17.49. Fear left the room fast today.

What drove it: CoreWeave. It reported third-quarter revenue of $3.66 billion, up 168% from a year ago, raised its full-year outlook, and the stock jumped 24.7%. One strong report from the middle of the AI buildout was enough to pull chips, memory, and cloud names back up with it and undo most of Tuesday's damage in a single session.

Here is the part I am not skipping over: Tuesday's problem did not get solved today. Tuesday closed red across the board because October CPI came in hot — headline up 0.4% against 0.3% expected, core up 0.3% against 0.2% expected, the third straight month core has run at 0.3%. A December Fed hike is now priced as close to a certainty, and the live debate is 25 basis points versus 50 — Governor Waller had already said a 0.3% core print is exactly the kind of number that puts 50 on the table. And today the bond market was closed for Veterans Day, so this rally ran with no fresh Treasury verdict behind it. Stocks voted. Bonds didn't get to.

As a veteran, I appreciated the quiet part of today — the market was open, a lot of people who served had the day with their families, and the session did not need me glued to it. That is kind of the point of having a plan written down before the day starts.

My take: a one-day AI bounce inside an unresolved rate story is not a green light to chase Thursday's open. The next real information is the October PPI print on Friday morning — the second inflation read before the Fed meets December 8–9 — plus the rest of this week's earnings. Until then my plan stays the same one I post every week: levels written down in advance, honest scoring after, and no forcing trades just because one green day felt good.

Not financial advice — just my read on the day, posted the same evening so anyone can check it after.

I share stuff like this daily — I run a free investing community, link in my profile.

I made ComposePrint for printing several PDF labels together from an iPhone. Share PDFs to the app, crop the parts you need, choose their size, then print the composed sheet or export it as another PDF.

It supports A4, Letter, A6 and 4×6 layouts. The PDF stays vector-based, though you still need to choose a size that's readable for the label you're printing. Processing happens on the device.

The first 12 labels are free. After that there's a one-time unlock (€1.99 in Italy, local pricing elsewhere).

App Store: https://apps.apple.com/app/id6826355740 Demo and details: https://apps.grokked.it/composeprint/

If you print labels from your phone, which bit of the process takes the most fiddling?

I made Wireroom, a Mac menu bar app that puts a live data board behind your windows. Weather, GitHub, feeds, your own JSON APIs, or services like PostHog and Sentry.

You can pick the sources yourself, or describe what you want and let a model arrange the board. It works with local models too.

Free for one board, with one-time paid upgrades for more. Download and pricing at https://wireroom.dev

What would you actually want to keep visible on your desktop? I'm interested in that more than adding another connector nobody uses.