Mowgli – Figma for the agent era, with Claude Code and design export

Hacker News

Hi HN! We're excited to announce the public beta of Mowgli, a spec-backed, AI-native design canvas for scoping and ideating on products. The productivity gains unleashed by coding agents have made everything else an unexpected bottleneck. In an effort to make the most out of this new paradigm, we ceded a lot of ground in product thinking, thoughtful UX, and design excellence. In other words, the pace of tooling for deciding what to build has not kept up. Mowgli is inspired by, in equal parts, Figma and Claude's plan mode. It evolves a detailed specification and designs for every screen and state of the product on an infinite canvas. Owing to this UI, it can quickly mock up new features and flows, redesign existing ones, and show you variations side by side. LLMs are amazing at helping you explore vast solution spaces, but most current tooling focuses on getting narrowly perfect output based on a well-defined spec. We try to bridge that gap with Mowgli. When you're ready to build, Mowgli offers a .zip export with a SPEC.md and unopinionated design .tsx files for your screens, in a perfect format for coding agents. Or alternatively, full, pixel-perfect export of all screens to Figma. In this early stage, we support two entrypoints: (1) building a product from scratch through a guided experience, or (2) importing an existing product from Figma. We have a powerful, almost pixel-perfect Figma to code + spec pipeline that works on files of any size - from 0 to 300+ frames. We're working hard on other ways to get your existing products into Mowgli (and would appreciate hearing about what you would like!) - Timelapse of making a functional second brain app in Mowgli + Claude Code: https://www.youtube.com/watch?v=HeOoy8WDmMA - Sample project designed and specced entirely by Mowgli (demo, no login needed): https://app.mowgli.ai/projects/cmluzdfa0000v01p91l5r61e3?the... - Sample Figma import of the whole Posthog product, ready for iteration: https://app.mowgli.ai/projects/cmkl0zqng000101lo8yn2gqvd?dem... (thanks PostHog for being radically open with public Figma files!)

Visit product View on Hacker NewsFeb 28, 2026

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Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, claude · Missing: mac, macos, cursor

96%96% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Strong signals: para · Missing: supports, reddit linkedin, podcasting

84%84% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: excited, exist, existing · Missing: https docs, just released, lua

38%38% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: way, para · Missing: mobile apps, ios, personal

33%33% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

24%24% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: arr · Missing: mrr, revenue, profit

16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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