LoopyTop 5Deep-reviewed
by Arjun Shah
What they're building
Loopy is the fully autonomous product-building agent that builds, tests, and just keeps going until it thinks it's done. Give it a starting point, and it researches the market, plans the product, builds it, tests it, tracks progress in Linear, fixes issues, iterates, and keeps going until it decides the product is ready. It sends the user constant emails with progress updates, and users can even provide their input to Loopy, and it will incorporate that in realtime. Loopy uses Nebius to power the main agent, Tavily and Firecrawl for deep research, and Composio as the execution layer across tools. It manages the full project in Linear, creates and updates GitHub repos, and maintains four core Markdown files that act as its operating system: goals, specs, issues, and progress. The hardest problem was memory. A real autonomous build loop can run for 6+ hours, but stuffing the entire session into context is expensive, slow, and brittle. To solve this, we integrated Mem0 for long-term memory across Nebius and the coding agent. We also integrated Supercompress, an open-source compression tool that reduced token usage by ~65% while retaining 98.7% of critical information. The result: Loopy can stay coherent across long build sessions without drowning in context. The magic is that the human does almost nothing. Start a loop, go to bed, and wake up to a tested, validated, deployed product that is ready to market. For founders, this means product development no longer has to consume the whole day. They can spend more time on distribution, customers, and strategy while Loopy handles the build loop. Loopy is fully open source, runs locally on the user’s device, and plugs into 40+ CLI tools including Claude Code, Codex, and Cursor. Because it runs locally, users keep control of their data and workflow.
AI code reviewrepo: real
Genuinely substantial autonomous build agent: 8,448 LOC package, 819-line multi-turn orchestrator (loopy/orchestrator.py) wiring Tavily research -> Nebius planning -> Composio execution. All three sponsor SDKs are imported AND called: Tavily search() with search_depth=advanced (research/tavily.py), Nebius via OpenAI client pointed at api.tokenfactory.nebius.com driving the entire plan/follow-up/email loop (nebius_client.py), and Composio tools.execute() as the load-bearing GitHub/Linear/Gmail/Firecrawl layer (integrations/composio_ops.py). 18 test files; deps declared in pyproject. Demo is a Loom video plus a polished product/docs page (loopy.yachts); it is a local CLI so no clickable hosted app, and the Loom video was rate-limited during verification. ⚑ Demo is local-CLI + Loom video rather than a hosted clickable app; Loom video could not be played during review (rate-limited). Some pitch extras (Supercompress 65%/98.7% claims) not independently verified.