Alternatives
Products that do what NotBuiltYet– Open-source library of civilisation problems worth solving does
an open-source, community-vetted repository of real-world problems that AI could solve but nobody's building yet. Each idea goes through a process: Someone identifies a real inefficiency — something that could be 10x or 90% better with AI The community researches market size, existing solutions, technical feasibility, and potential impact Domain experts vote, critique, and refine Ideas that survive get a viability score and a detailed blueprint — ready for someone to pick up and build Everything is MIT licensed. The goal is simple: give builders a head start on problems that actually matter.…
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AI has made building fast and cheap, but finding the right problems still feels hard. I built World’s Backlog (https://worldsbacklog.com ) to collect real problems directly from people working inside different industries. Contributors post workflow pain, others validate it, and builders can study severity, frequency, and willingness to pay before building anything. Would love feedback from builders and people who feel real pain at work.
Dec 2025 · worldsbacklog.com
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2020 · opensource.builders
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2015 · realproblemhunt.com
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I've been exploring the (not so=) amazing potential of AI in coding and have compiled a list of tools. From AI-powered IDEs to code generators, this resource is my contribution to the community. I'm still on the fence about including txt2sql projects, as their functionality seems too basic to me. And I'm personally maintaining this, so your feedback is wellcome.
2025 · aicode.danvoronov.com
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2024 · github.com
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We recently open-sourced Hive after using it internally to support real production workflows tied to contracts totaling over $500k. Instead of manually wiring workflows or building brittle automations, Hive is designed to let developers define a goal in natural language and generate an initial agent that can execute real tasks. Today, Hive supports goal-driven agent generation, multi-agent coordination, and production-oriented execution with observability and guardrails. We are actively building toward a system that can capture failure context, evolve agent logic, and continuously improve…
Feb 2026 · github.com
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Hi there, I've created this side project to make it easier to find interesting repositories using AI. There's still a lot of work to be done to improve it, so any suggestions for enhancements would be greatly appreciated. Thank you!
2024 · awesome-repositories.com
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2025 · github.com
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I'm a VP of Engineering with 20 years in the field. I've been thinking deeply on why AI is breaking every engineering practice, and it led me to the conclusion that the Agile Manifesto's values need updating. The core argument: AI made producing software cheap, but understanding it is still expensive. The Manifesto optimizes for the former. This addendum shifts the emphasis toward the latter. Four updated values, three refined principles, with reasoning for each. Happy to discuss and defend any of it.
Mar 2026 · github.com
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Humans compete to improve their AI agents on benchmarks. But what if agents could collaborate and compete on their own? We built Hive, a crowdsourced platform where agents can evolve solutions together. One agent begins to tackle a task, iteratively improving its code. Then other agents join. They read each other’s runs, fork the best ideas, propose new ones, and push the solution forward together. We already have agents working on benchmarks like Tau2-Bench, Terminal-Bench, and ARC-AGI-2, with more tasks coming soon. We also support the new OpenAI Parameter Golf Challenge, and you can…
Mar 2026 · hive.rllm-project.com
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I kept noticing the same pattern: my AI coding agents solve the same problems over and over across sessions. Coding problems, version specific bugs and general guidelines, solved once through multiple agent interactions and context windows and then forgotten by the next context window. So I built OpenHive, a shared knowledge base that agents contribute to and query from. The idea is simple: when an agent solves a problem, it posts a structured problem-solution pair. When another agent hits a similar issue, it searches the hive first. How it works: - REST API with semantic search (pgvector +…
May 2026 · openhivemind.vercel.app
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Hi HN, I’m a solo founder. I built ProblemHunt after noticing a common pattern: many founders start with ideas and solutions, but don’t spend enough time understanding real problems. ProblemHunt is a simple place where people share problems they actually face in work or life. Developers and founders can browse these problems and use them as a starting point for building products. So far: – ~5,000 users – 150+ real problems submitted – 100% organic growth This is still early, and I’m trying to understand if this is genuinely useful. I’d really appreciate feedback: – Would you use something…
Jan 2026 · problemhunt.pro
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Hey HN! When implementing an AI-powered feature for a project, we—and many people we've talked to—often reach a point where we have to choose an AI model but aren’t sure which one best fits our constraints or where to even start. Unfortunately, the advice to "just use chatgpt" is not always a good one. What if I want an open-source model? What languages does it support? What about context window size or the number of parameters? There are thousands of AI models already out there and many of them are perfect for certain problems. That’s why we’ve carved out this part of our product as a free…
2024 · app.elementera.ca
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Hello! Introducing geniusrise, an agent framework and component ecosystem for building AI agent networks that are as flexible as your team. landing page: https://geniusrise.ai (fancy but useless) docs: https://docs.geniusrise.ai (please check this out) github: https://github.com/geniusrise (for dear devs) ## Thought process Since the ChatGPT disruption, I've been pondering on what the tooling layer is going to look like for building LLM-interfacing agents. Saw a plethora of tools coming out as we witness here every week. I'd broadly categorize them into the…
2023 · github.com
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The first ever AI peer reviewed research article just got approved. It’s kinda crazy how advanced AI have come to replace researchers. I've just been using Deep Research on ChatGPT and Perplexity a lot to write and research complex technical reports for my boss. He loves the reports and it has decreased my workload a ton but I still have some frustrations with it. None of them provide an API that gets me the same quality of output you would with the applications. I wanted something with more control on the LLMs, swappable with the reasoning new models that came out. Not just prompt →…
2025 · github.com
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Hi HN, Martin, Nils, and Jannes here. We are building Legit, an open source version control and collaboration layer for AI agents and AI native applications. You can find the repo here https://github.com/Legit-Control/monorepo and the website here https://legitcontrol.com Over the last years, we worked on multiple developer tools and AI driven products. As soon as we started letting agents modify real files and business critical data, one problem kept showing up. We could not reliably answer what changed, why it changed, or how to safely undo it. Today, most AI…
Jan 2026
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