Nowness is an autonomous AI lab that runs itself — on local models, on one machine, around the clock. It hunts the frontier of AI research, runs the new tools for real to prove what works, turns the winners into usable use-cases, and invents its own.
Finds the newest AI research and tools the moment they appear.
Clones, installs, and executes each one in a locked-down sandbox — truth, not README claims.
Turns what actually works into real, usable use-cases.
Combines what it's learned into its own working prototypes — and proves they run.
One thing it proves: 1,230 AI repos it actually ran, and a third don't work.
Everyone judges AI by the demo. Nowness runs the code — and only surfaces what's real.
Paste any public GitHub repo and your email. Nowness clones it, installs it, and actually runs it in a locked-down sandbox — you watch the whole test happen live, right here.
Here's exactly what lands in your inbox:
→ 2,001 repos tested by the lab so far
Every day Nowness features ONE repo from its verified winners — ranked purely by real execution evidence (tests that passed, installs that worked, demos that ran), never by stars, and never an obvious big name. A fresh verified gem, daily.
Prax is an agent runtime that enables LLMs to perform autonomous tasks using 'test-verify-fix' loops.
Prax is an agent runtime that enables large language models to perform autonomous tasks through test-verify-fix loops. It supports multi-model orchestration and cross-project memory while automating the execution of code and tests. The lab's run proved the system can successfully execute and verify tasks, achieving a high volume of passing tests and a successful exit status.
This project earns its spotlight by addressing the fact that AI agents often hallucinate or fail to verify if their code changes actually work. Prax provides a structured environment for execution and verification. It handles tasks ranging from automated bug fixing and pull request triage to scheduled data scraping and content creation.
Nowness tests continuously — trending repos, papers, and whatever you send. This is live from the sandbox.
Every card below was actually executed by the lab — under-the-radar repos that installed clean and did what they claim, verified in the sandbox, not guessed from the README. From 2,001 repos tested so far.
CodeGraph is a GraphRAG framework that transforms codebases into a Neo4j knowledge graph containing structural entities (classes, functions) and semantic vector embedding.
Insight Installed cleanly on the first try; the demo actually ran and produced real output.
github.com/Abhishek-Aditya-bs/CodeGraph ↗An AI-powered command-line tool that parses codebases into semantic graphs to provide deep code intelligence.
Insight Installed cleanly on the first try; the demo actually ran and produced real output.
github.com/al1-nasir/codegraph-cli ↗A production-grade Rust library for GBNF (GGML BNF) grammar-constrained decoding.
Insight Installed cleanly on the first try.
github.com/Michael-A-Kuykendall/schoolmarm ↗A research repository providing three micro-scale adversarial game environments (Hex-Line, Quantum Match, and Shift-3) designed for studying small state spaces.
Insight Installed cleanly on the first try.
github.com/Devanik21/Micro-State-Space ↗A framework for implementing and training Structured State Space (S4) sequence models.
Insight A framework for implementing and training Structured State Space (S4) sequence models.
github.com/state-spaces/s4 ↗VMamba is a computer vision backbone that adapts the Mamba state-space model for visual data.
Insight VMamba is a computer vision backbone that adapts the Mamba state-space model for visual data.
github.com/MzeroMiko/VMamba ↗Nowness will tell you whether that trending repo actually works — with the evidence.