The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
Back to feedPost
Open-source AI agent platform for autonomous software development. It can write code, run terminal commands, debug applications, review pull requests, and automate engineering tasks across local, cloud, and self-hosted environments.
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
Challenges
View all
Related posts
I built ReviewIQ because technical interviews don't always test whether you can actually review code.
ReviewIQ is an AI-powered code review interview trainer built for software engineers.
You pick a role, language, and seniority, then get a realistic PR diff with bugs intentionally planted in it.
You write your review.
Then the system grades it against the actual bugs, shows what you caught, what you missed, and gives you feedback on how a stronger reviewer would approach it.
The interesting part was building the grading system so it isn't just "AI thinks your answer is good." The bugs have a known ground truth, so the review can be evaluated against something concrete.
Built with Next.js, Supabase, PostgreSQL, OpenAI, and Lemon Squeezy.
I'm interested in building more products where AI isn't just a chat box, but an actual part of the product experience.
The known-ground-truth approach is a great product decision—it makes the feedback feel earned rather than like an opaque AI verdict. I also like that the flow tests the actual review skill instead of rewarding pattern-matching in interviews.
🤖 What if AI stopped waiting for prompts — and started working toward goals?
We’ve moved from chatbots → copilots → AI agents.
The next shift, I believe, is AI systems that can plan, collaborate, execute, and adapt on their own.
Imagine giving AI a goal instead of a list of instructions:
“Analyze this problem, research what’s needed, figure out the best approach, execute the tasks, and keep me updated.”
Behind the scenes, multiple specialized agents could:
🔹 Break the goal into tasks
🔹 Research & reason over information
🔹 Use tools and APIs
🔹 Collaborate with other agents
🔹 Validate their own work
🔹 Adapt when something fails
🔹 Deliver the final outcome
That’s the direction I’ve been exploring with WhatAIUpTo — moving from “AI that answers” → “AI that gets work done.”
The interesting question isn’t “What can AI generate?” anymore.
It’s: “What can AI accomplish without being told every step?”
We’re just getting started. 🚀
#AI #GenerativeAI #AgenticAI #AutonomousAgents #AIEngineering #FutureOfAI #MultiAgentSystems #ArtificialIntelligence
Mobile AI shouldn't just talk. It should ACT. ⚡
Here is a 1-minute demo of an autonomous mobile agent I built:
🔹 Converts natural language instructions into multi-step execution plans
🔹 Interacts with native Android apps (Settings, Chrome, etc.)
🔹 Identifies UI elements dynamically and handles taps, swipes, and text input hands-free
Built with Python, LLMs, and on-device UI perception.
If you're building agentic AI, mobile automations, or looking to collaborate, my DMs are open! 🚀
#AI #MachineLearning #AIAgents #Python #AndroidDev #Automation
