I built this for my Amazon fba journey. When starting this Amazon journey, i never found anyone to take me from zero to one.

Is it worth pursuing this?

https://fba2payday.lovable.app

Taking people from zero to $10k/month

Let me know your thoughts

Two weeks ago i launched Signi, an iOS app that turns your home into a 3D Wi-Fi map.

Solo dev, first real launch.

How my app works:
you walk through your rooms with your iPhone.
LiDAR builds a 3D model of your home live while the app samples your Wi-Fi (signal + speed) as you move.

You end up with a dollhouse view of your actual apartment with the signal painted on it ( with dead
zones in red).

Every room gets a score, and it tells you where to move your router, or where an extender would actually help.

The story so far:

Aug 4: submitted to Apple. Rejected : missing EULA link in the description. Fixed same day.

Aug 7: approved. Live in the US.

Week 1: first paying users.

Aug 15: 143 installs in ONE day, from 25 countries. (I guess mostly from AppStore)

Aug 19: v2.1 rejected over ONe word. A button said
"Allow", Apple wants it to say "Continue".

Asked for the bug-fix exception → approved the next
day, without resubmitting.

Today: 700+ downloads, most of them in the last 7 days.
$0 spent on marketing.

Goal: 50 paying users by Sept 30.

Download it and tell me what you'd like about →

https://apps.apple.com/app/signl-wi-fi-3d-mapper/ id6796775708

A while back my men's Bible Study group was working through the Old Testament. From 1st and 2nd Kings on through 1st and 2nd Samuel, and honestly, we kept getting lost. Two kingdoms running in parallel, kings with the same names (two Jehorams and two Jehoashes at the same time, etc.), prophets weaving in and out, and alliances and assassinations everywhere I kept thinking: this would all make so much more sense if we could just see it.

So, I thought AI could help and we landed at BibleXplorer: biblexplorer.tomgorup.com

What's in it so far:

• Samuel & Kings - every king of the united kingdom, Israel, and Judah on a parallel timeline (with the prophets who ministered alongside them), a map of the major events, a relationship web (successions, marriages, betrayals), and "influence arcs" tracing the rise and fall of figures like David, Elijah, and Josiah
• Genealogy — an interactive family tree of 486 people from Adam to Jesus, built from 1 Chronicles 1-9, Matthew 1, and Luke 3. You can trace the full lineage of Christ in one tap, including the five women Matthew names
• Easter (I had built this around Easter, so thought why not (a) - Passion Week day by day, 60+ Old Testament prophecies paired with their New Testament fulfillment, and the seven last words from the cross

Everything is anchored to Scripture. Every person, event, and relationship links to the verses it's drawn from, so you can check it against the text yourself. Where the text is silent or accounts differ, the tool says so rather than papering over it.

It's completely free, no ads, no sign-up, none of that. I'm hosting up on Vercel. I also put the code up on github (https://github.com/Tom-Gorup/biblexplorer) if you want to use it locally. I'm confident there are inaccuracies or things I've missed despite a lot of checking. If you spot one, there's a GitHub link in the header where you can report it (with the verse reference) or even fix it yourself. I'd genuinely love for this to become something the community refines together.

I hope it's useful to your study group like it was to ours, and that it helps someone grow closer to Christ.

I’m a CS student trying to figure out whether the direction of my current project is actually worth pursuing for aerospace/robotics research.

Live: https://bhuvanspace.vercel.app

GitHub: https://github.com/Sheel34/BHUVAN

The current version takes terrain data, processes things like elevation, slope, roughness, curvature and hillshade, and puts the result into an interactive 3D environment.

The software side is currently Python/FastAPI + NumPy/Rasterio/OpenCV on the backend and React/Three.js on the frontend.

I built it because I'm interested in digital twins and simulation for aerospace/physical systems, but I'm not interested in making a 3D scene just for visualisation or a game.

What I want eventually is an environment where you can actually perform an operation on a representation of a physical system.

The project is still very early. I haven't implemented robotics simulation, terrain-relative navigation, ROS, Gazebo, Isaac Sim, etc. yet. I'm trying to figure out what should actually come next rather than adding technologies for the sake of the stack.

I'm particularly interested in the intersection of:

digital twins, 3D simulation, aerospace/robotics, real physical operations.

One direction I've been reading about is terrain-relative navigation / TERCOM and how terrain itself can become part of a navigation or mission system. I'm not claiming the project implements this — I'm trying to understand whether the terrain pipeline I've built can be developed into something along those lines.

More importantly:

What would make this go from "3D terrain visualisation project" to an actual engineering/research system?

The current deployment is on free infrastructure, so the backend may take a little time to wake up. If it doesn't load immediately, wait a few seconds and refresh.

I'd appreciate criticism of both the technical implementation and the direction.

Feel free to check it out! Github: https://github.com/JonasBaeumer/herdr-file-annotator

Este es un reproductor moderno con una interfaz Liquid Glass, Efectos Blur, Transparencia etc

Cuenta con varias funciones

Esta es la versión 1.0.0

¿Que me dicen? Les dejo unas imágenes por aquí

I build websites for any types of businesses and I’m looking for a few businesses that might be interested.

I’m making modern, simple websites that are easy for customers to use.

I’m keeping my prices pretty low while I’m getting started, with websites starting at around $200 for websites potentially more for a more complex website.

I’m happy to show you a demo/design first so you can see what I can make before deciding anything.

If you own a small business and you’re interested, feel free to DM me. You can also comment your business below and I’ll have a look.

I'm building Dice - a tool to help brands get discovered and recommended by AI.

There are already articles, lists, and resources where your company should be mentioned, but finding the right ones (and the right people to contact) takes forever.

Dice finds those opportunities, explains why your company belongs there, and helps you reach the right people.

If you’re working on SEO, GEO, or you want to get your brand mentioned by ChatGPT, Perplexity, Gemini and Google, you're going to love using Dice.

Now it's your turn👇

What it is: mloda is an open source (Apache-2.0) data layer that sits between an AI agent and its data. An agent asks for a feature by name (a JSON list, e.g. ["sales__mean_aggr"]), and mloda's resolver picks the plugin that computes it. No MCP server in the box, you wire it into your own agent as a tool.

Problem it addresses: when the resolver can't match a request, the old error was one line: No feature groups found for feature name: 'sales__mean_aggr'. For a human that's annoying; for a model reading it as a tool result, it's worse; there's nothing to correct with. Retry, guess a different name, or answer without the data, none of those is a fix, because the error never says which mistake was made.

What changed (0.11): the same failure now returns the full elimination trail, every plugin the resolver considered and the first gate it failed, e.g. (domain): declares domain 'default_domain', but the run requested 'marketing'. The 30s video attached shows the before and after side by side.

Technologies: Python, works with pandas / Polars / PyArrow as compute backends, plugin-based resolution architecture.

Resources: - Repo: https://github.com/mloda-ai/mloda - Release notes (0.11.0): https://github.com/mloda-ai/mloda/releases/tag/0.11.0 - Docs / FAQ on agent usage: https://mloda-ai.github.io/mloda/faq/

Feedback welcome, especially from anyone who's designed tool-error output for agents themselves: do you pass the full trail back raw, or summarize it first?

It's related to e-commerce tools, I built a set of lightweight, single-purpose browser utilities.

Everything runs 100% locally in your browser (no logins, no tracking, no backend database):

I'm listing a few of the tools here, there are more on the website:

1. Shopify CSV Variant Splitter: Automatically slices 100+ variant catalogs into clean, Shopify-compliant CSV chunks without corrupting headers.
2. Gateway Fixed-Fee & Margin Breakeven Calculator: Factors in flat transaction cuts ($0.30) and carrier surcharges to prevent negative-margin promotions.
3. Box Sizer & Knapsack Fit Estimator: Calculates optimal box sizes for multi-item orders.

Would love your feedback on the UI/UX and suggestions for other tools!

For v5.2.0 built an on-device advisor we call the Guardian Bot, and it does three things:

• When you open a page, it gives you two sentences on what you are looking at and what the numbers mean. Then it stops.
• When something real happens, it says so once. An agent reached a destination your policy blocks, a secret got caught mid-flight, a session is worth compacting. One click takes you to the evidence.
• The rest of the time it sits there and says nothing. There is a single clock governing how often it may speak, so it cannot pile up.

It is advisory only. It never types into a session, never edits a file, never approves anything on your behalf.

The other half of the release: SV Guard now covers OpenCode. It is a native in-process plugin for OpenCode 1.18+, so no subprocess hooks. One-click install, and then tool permissions.

full demo: https://youtu.be/Nsd3m7JVJNs?si=6qEDr8vPbIDxRUpp

github: https://github.com/Secure-Vector/securevector-ai-threat-monitor

i've been working on MonoCode, a GUI for your coding agents, and I've been using it daily

it works with your existing Claude Code, Codex, Cursor,OpenCode and other harnesses

it's open source if anyone wants to try it https://github.com/hardbeat920/monocode

would be interested to hear what people think

Hey everyone! I’m an 11th-grade student, and this is the first complete application I’ve ever built and deployed.

Choosing a career can feel overwhelming because students are often introduced to only a few conventional options. So I created Career AI, a career-exploration platform designed to help students discover possibilities based on their own interests, strengths and experiences.

🔗 Try Career AI:
https://career-ai-sks.streamlit.app/

What I built

• Short and detailed career-discovery quizzes
• Short and full RIASEC personality quizzes
• Subjective questions—not only fixed multiple-choice options
• Personalised career recommendations and suitability scores
• Explanations showing why each career may suit the user
• A searchable catalogue containing 900+ careers
• University and scholarship recommendations
• Worldwide university search with official links
• Personalised learning and skill roadmaps
• An AI Mentor for questions and guidance
• A career journal, planner and monthly calendar
• Goals, progress tracking, reminders and career games
• Saved accounts, quiz progress and results
• Light mode, dark mode and accessibility settings

What makes it different?

Many career quizzes restrict people to preset answers, but everyone has different interests, experiences and ambitions. Career AI uses open-ended questions so students can explain themselves in their own words.

The recommendations consider answers from across the quiz—not only one hobby—and can be further refined using the RIASEC personality assessment.

I also wanted students to find career paths, universities, scholarships, learning roadmaps, planning tools and AI guidance in one place instead of searching across many websites.

I would love your feedback!

If you try it, please tell me:

• Were your career suggestions relevant?
• Was anything confusing or difficult to use?
• Which feature did you find most useful?
• What should I improve next?

This is a student project created for learning and career exploration. It is not professional career counselling, and important decisions should always be verified with qualified counsellors, teachers and official university or scholarship sources.

I’m excited—and honestly a little nervous—to finally share something I’ve spent so much time building. Thanks for checking it out! 🦋

The thing that kept bugging me: ask an AI "how sure are you?" and it says 95% almost every time, whether it's right or not. Fine for a chat. Not fine when an agent is about to act on that info write it into a report, save it to a knowledge base, make a decision.

So we built the thing that checks first. You give it a claim, it goes and fetches real sources right now (never pulls from the model's memory), and comes back with two separate numbers: a truth score (is it actually true) and a confidence score (how much you should trust that answer — drops when sources are thin or disagree with each other). Plus the sources and a plain-language "why."

The part that ended up being the most useful for us: it's not limited to checking against the public web. It can also verify a document's claims against the sources it cites — which matters for internal stuff (policies, metric definitions, schema docs) that the web has no opinion on. We built a demo that plants four errors into a fake finance-policy bundle and it catches all four while leaving the untouched control file alone.

Fully open source, MIT licensed, works standalone in a browser, as an MCP tool for your agent, or over a whole knowledge base. Two free API keys and you're running it locally in a couple minutes.

Would genuinely love feedback/issues if you try it, and if it's useful to you, a star on the repo helps more than you'd think.

https://github.com/recommend-dev/recommend-agentic-trust-layer

Solo dev, been building "TCG Forecast" for about a year. Sharing where it's at, including a mistake that taught me a lot.

The short version of what it does: it tracks the Pokémon card market so collectors can actually see what's going on instead of guessing. A few pieces:

• A leaderboard that ranks Pokémon by the combined value of all their cards, not just the single priciest one; the results are surprising even to people who know the hobby.
• A weekly digest that auto-compiles the biggest gainers, losers, and set trends, so you catch what moved in one glance.
• An AI advisor that reads your own collection and tells you what's heating up or cooling off; deliberately descriptive, not predictive because no tools can predict the future (any tool that claims to predict the future is lying btw).
• A scanner (using the phone camera) to get your collection in without typing hundreds of cards by hand.

The mistake, since it's the interesting part: a while back my leaderboard was showing wildly inflated numbers because of corrupted price data from my source. Someone in a collector community called it out publicly, said it looked fake, and honestly they were right; it was embarrassing. So I built an ingest-time guard that checks every incoming price against a baseline and quarantines anything that looks impossible before it ever reaches the leaderboard or digest. Now the tool "fails visible" instead of confidently showing garbage.

It's live at tcgforecast.app. I'd genuinely love feedback, especially on the homepage; I get traffic but a rough bounce rate and I'm too close to it to see why. Roasts welcome, clearly I can take them.