AI tool comparison
Figma Make vs Intent
Which one should you ship with? Here is the side-by-side panel verdict, pricing read, reviewer split, and community vote comparison.
Developer Tools
Figma Make
Figma designs to production React components, synced with GitHub
100%
Panel ship
—
Community
Paid
Entry
Figma Make converts Figma designs into production-ready React components and maintains a live sync with a connected GitHub repository as designs evolve. It enters open beta for Professional and Organization plan users, positioning itself as a bridge between design handoff and frontend development. The tool is AI-native, using AI to interpret design tokens, layout constraints, and component structure into idiomatic React code.
Developer Tools
Intent
Describe a feature. Agents build, verify, and ship it — in parallel.
75%
Panel ship
—
Community
Free
Entry
Intent, from Augment Code, reimagines the coding agent as an orchestrated team rather than a single assistant. You write a feature spec in plain language. A Coordinator Agent breaks it into tasks. Specialist Agents execute those tasks in parallel inside isolated git worktrees. A Verifier Agent checks results against your original spec before surfacing anything for your review. The spec is "living" — it updates as work progresses, and when requirements change, updates propagate to all active agents. This is meaningfully different from one-shot prompting or even multi-step agentic coding. Intent is designed for enterprise teams working on large codebases where a single feature might touch dozens of files across multiple services. The built-in Chrome browser lets agents preview local changes without leaving the workspace. It integrates with existing git workflows rather than replacing them. Launched in public beta February 2026 (macOS only, Windows on waitlist), Intent got its highest visibility yet when it hit Product Hunt with 302 votes this week. Augment Code has been quietly building toward this: their previous focus on large-enterprise codebase indexing gives Intent's retrieval layer an advantage over agents starting from scratch.
Reviewer scorecard
“The primitive here is a bidirectional design-to-code sync layer: Figma as the source of truth, GitHub as the output artifact, AI as the translator. That's a real problem — design handoff is where intent goes to die. The DX bet is that developers accept AI-generated React as a starting point rather than a canonical output, which is honest and probably right. My concern is the moment of truth: what does the generated component actually look like when your design uses a custom constraint system or a non-standard grid? If the output requires heavy manual cleanup, this is just a fancier inspect panel. The GitHub sync is the feature that earns the ship — if diffs are clean and components track renames correctly, that's a workflow nobody has nailed yet.”
“The parallel worktree approach is genuinely smart — agents don't step on each other, and the living spec means you're not herding a single agent through a long task linearly. For features that touch multiple modules, this could cut agent coding time dramatically. macOS-only is a real limitation though.”
“The direct competitors are v0, Locofy, and Anima — all of which have been promising production-ready code from Figma for years and delivering 'close enough, fix the rest yourself.' Figma's advantage is distribution: they already own the design file, so they don't need a plugin handshake or an export step. The scenario where this breaks is any codebase with an existing component library — if Make generates new Tailwind components instead of mapping to your existing Button and Input primitives, it creates drift, not savings. What kills this in 12 months isn't a competitor, it's that Figma's GitHub sync produces code that developers don't trust enough to merge without rewriting, and the workflow dies at the PR review stage. To be wrong about that, the AI would need to produce genuinely idiomatic code that maps to user-defined design systems, which is a hard problem Figma hasn't publicly solved.”
“Multi-agent coordination sounds great until the Verifier Agent approves something the Specialist Agents hallucinated together. Coordinated AI errors are harder to catch than single-agent errors because they have the veneer of consensus. I'd want to see extensive user testing on real enterprise codebases before trusting this in production.”
“The interaction model that matters here isn't the UI of Make itself — it's whether the sync loop between design changes and code output is legible to the designer making the change. If a designer renames a component or adjusts spacing and the GitHub diff is clean and traceable, that's a workflow artifact worth respecting. The failure mode is the classic one: the AI interprets absolute positioning as inline styles, padding becomes magic numbers, and the code output stops reflecting design intent within two iterations. Figma has the unique position of owning the design token layer, which means they could produce semantically meaningful diffs rather than pixel-value noise — if they've done that work, this earns a strong ship. That specific decision — whether output references design tokens or raw values — is the one I'd audit first.”
“The buyer here is the design-engineering team lead at a mid-market SaaS company, and the budget comes from the engineering productivity line — not the design tool budget. Figma is smart to bundle this into existing Professional and Organization plans rather than charging separately, because it removes the procurement friction and makes adoption a product decision instead of a budget decision. The moat is real and specific: Figma owns the design graph, which means competitors building outside Figma have to reverse-engineer intent from a static export while Make reads the live constraint tree. The stress test is whether this survives when GitHub Copilot and cursor start reading Figma files directly via MCP — and the answer is probably yes, because Make's value is the sync loop, not just the one-shot generation, and that requires deep Figma API access nobody else has yet.”
“Intent is the most concrete vision I've seen of what software development looks like when the unit of work is a feature spec, not a file edit. The living spec abstraction — where truth lives in intent, not implementation — will age well. This is the direction the whole industry is heading.”
“The built-in browser for previewing changes without leaving the workspace is a small detail that shows good UX thinking. For product builders who move between design specs and implementation, having a feature spec drive coordinated agent work — and seeing a live preview — is exactly the kind of tight loop that makes creative work faster.”
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