I'm not a "real developer."
I built this whole platform with AI anyway.
Hi, I'm Benjamin. I don't have a computer science degree. For years I thought that meant the things in my head would stay there. Then AI changed the rules, and I built this entire platform, feature by feature, with it.
Every time I showed it off, someone called it "AI slop." Here's what they miss. AI doesn't hand you a product. You still bring the idea, the taste, the thousand small decisions. The tool is just leverage. What you make with it is yours.
So I built the room I wished existed, a place for the rest of us: people turning ideas into real products with AI, shipping in the open, without anyone looking down on how we build. Free forever. No ads. No slop.
No credit card. No ads, ever. Browse everything without an account.
What is DevConnect?
DevConnect is a free community for people who build real products with AI. One place to share what you're shipping, meet builders who get it, and sell what you make. No gatekeeping about how you built it. Free forever, no ads.
Your projects, your stack, what you've shipped. One link that proves what you can build, not what school you went to.
Post what you're building with AI and get curiosity, not contempt. Real feedback from people building the same way.
Rooms around Cursor, Claude, a model or a stack. Set the rules, run it your way. You own it.
Talk instead of typing. Drop into a community voice room, or call someone you both follow. Your mic stays off until you switch it on.
Sell your products and templates. Creators earn fair, with no hidden platform-cut games.
Salary and stack upfront on every post. One-click apply, no recruiter maze.
Need testers for a store release? Builders test each other's apps, you test theirs back.
Talk, don't type
Some things take twenty messages, or two minutes of talking. Every community has voice rooms now, and you can call anyone you both follow — straight from their profile or a chat.
Your mic stays off. Nobody can hear you.
You can speak. Your camera stays off.
Camera allowed, off until you turn it on.
Recent from the feed
Building a 3D AI Fitness Planner: From Interactive Design to Intelligent Automation
I built a complete 3D AI Fitness Planning Platform as part of my AI Automation assignment, combining immersive web design, artificial intelligence, and business workflow automation into one functional system. The website is designed as a futuristic 3D fitness experience where users can create an account, log in, enter their fitness information, and receive personalized workout and meal recommendations. Instead of building a conventional gym website, I focused on creating an interactive environment with 3D visuals, animations, modern UI, and a premium user experience. Behind the website, I developed multiple n8n automation workflows to make the platform intelligent and functional: 1. Registration Automation User registration data is captured through a webhook and processed automatically, with user information stored in the connected database. 2. Login Attempt Automation Login attempts are processed through an automated workflow that validates incoming user information and manages the authentication process. 3. AI Tagging Automation User and fitness-related information is processed through an AI workflow that analyzes the data and generates relevant tags, helping organize and understand user information intelligently. The project was challenging because it required connecting multiple systems together while keeping the user experience smooth. I worked with web technologies, APIs, webhooks, databases, AI, n8n automation, and 3D interactive design to bring everything together. This project showed me that AI automation is not just about creating workflows. It is about connecting the entire digital experience—from the frontend users interact with to the backend intelligence that processes their data. The final result is a modern, immersive, AI-powered fitness platform that combines **3D web development, AI personalization, data management, and intelligent automation** into one complete solution.
Level 1 AI Agent in n8n (Gemini + Tools + Memory)
Just built a custom Level 1 AI Agent using n8n! 🚀 Here is what's running under the hood: - **LLM Model:** Google Gemini Chat Model - **Memory:** Window Buffer Memory for conversation context - **Tools:** Custom HTTP Request tool fetching live web data (Wikipedia API) & Calculator tool In this demo, the agent autonomously decides to call the HTTP tool to fetch live information about Tesla and formats the output smoothly. Feedback and suggestions for Level 2 features are welcome!
🚀 Built a House Price Prediction Model using Python & Machine Learning
I built a **House Price Prediction** project as part of my **Data Science Internship at Oasis Infobyte**. ## 📌 Project Overview The goal of this project is to predict house prices based on different property-related features using **Machine Learning**. ## 🔄 Project Workflow **Dataset → Data Cleaning → EDA → Feature Selection → Model Training → Evaluation → Price Prediction** ### 🧹 Data Preparation * Loaded and explored the dataset using **Pandas** * Handled missing and inconsistent data * Prepared the dataset for machine learning ### 📊 Exploratory Data Analysis * Analyzed relationships between different features * Created visualizations to identify patterns and trends * Studied factors affecting house prices ### 🤖 Machine Learning * Selected relevant features * Split the dataset into training and testing sets * Trained a regression model * Evaluated the model using appropriate performance metrics ### 🎯 Prediction The trained model takes property-related features as input and generates an estimated **house price**. ## 🛠️ Tech Stack `Python` `Pandas` `NumPy` `Matplotlib` `Scikit-learn` `Jupyter Notebook` ## 💡 Key Learning This project gave me hands-on experience with the complete machine learning workflow — from **data preprocessing and visualization to model training, evaluation, and prediction**. ## 🔗 GitHub Repository 👉https://github.com/pallavisagar07/OIBSIP/tree/ec73e94f0a9d2ea3a3fe3e65c1676d8c0af17219/DataAnalytics-L2-House-Price-Prediction-Linear-Regression #Python #MachineLearning #DataScience #DataAnalytics #ScikitLearn #OasisInfobyte #ProjectShowcase
Questions we answered properly
Shipping, hiring, reviewing AI-written code, finding people to build with: the honest answers are scattered and half of them are out of date. Every source on these pages was fetched and checked before it went live, and nothing goes up that fails that check.
Yes, in some GitHub agent flows, proposed changes are scanned for risky output before write actions and Copilot can review pull requests automatically, but that is not universal or a full substitute for review.
Break the pull request into reviewable slices, read it file by file, verify the risky parts locally, and insist on smaller follow-up PRs when the diff is still too wide to trust.
Yes. Before external testers can join, Apple requires TestFlight beta app description, beta app review information, and a feedback email in App Store Connect.
Yes. Google Play treats account verification via SMS as an invalid use of SMS permissions, and it points developers to SMS Retriever or manual code entry instead.
Project of the Week
Post what you built this week with the showcase tag. The community upvotes until Wednesday night, and the winner takes the featured spot at the top of the feed for three days.
How to build with AI without shipping slop
The difference between a real product and "AI slop" isn't the tool. It's the decisions you make around it. Six things that actually matter:
- 01Own the idea before you prompt
AI is great at "how," useless at "what" and "why." Know what you're building and who it's for. That part is still yours.
- 02Read every line it writes
If you can't explain what your code does, you don't own it, you're renting it. Ask the AI to explain until you actually understand.
- 03Ship small, ship real
One feature that works beats ten that half-work. Slop is what happens when you generate faster than you can check.
- 04Test it like a user, not a demo
AI writes the happy path. The bugs live in the edge cases you have to go find yourself.
- 05Keep the taste human
Naming, flow, what to leave out: that's judgment, not generation. It's why two people with the same tools ship completely different things.
- 06Learn the fundamentals as you go
You don't need a degree, but understand what you keep reaching for. Every "why did that work?" you chase makes the next build more yours.
A small team. A lot of AI. No VC, no roadmap deck.
DevConnect is built and run by me, Benjamin, with a small team who own big parts of it with me. Not a room full of engineers, just a few people who learned to build with AI and refused to wait for permission. If something breaks, you're talking to the person who built it.
"People kept telling me I'm not a real developer. Maybe not. But I built the thing you're looking at, and I built it for everyone who's been told the same. That's who this is for."
Frequently asked questions
Come build in the open.
It's free. It always will be, and there will never be ads.