Figma AI Make Prototype vs Runway Act-Two

“The interaction model here is exactly right: Make Prototype doesn't introduce a new surface or modal — it reads what's already on the canvas and adds connections back into the same noodle-and-arrow system Figma designers already know. That means the output is editable, not magic-boxed. The real craft decision that earns the ship is that it respects existing component and variant semantics rather than generating flat, dumb connections — hover states actually wire to their counterpart variant. My one pointed concern is error handling: when the AI misreads a layout ambiguity, the failure mode is silently wrong connections rather than a surfaced warning, which can torpedo a client demo if you don't sanity-check.”

“The output is not cinematic — you're getting sensible default easing curves and standard dissolve transitions, not bespoke motion direction. But that's actually the right call: the taste layer here is deliberately minimal, leaving the designer in control of anything that matters for brand expressiveness while automating the grunt work of wiring 40 frames together. The editing surface is the full Figma prototype panel, which means refinement is identical to hand-wiring, so there's no skill cliff when you need to fix something. The fingerprint is low: generated prototypes are indistinguishable from hand-built ones, which is the correct outcome for a tool like this — you want your design to be the thing with a signature, not the prototype scaffolding.”

“The output is genuinely uncanny in the right way — a reference clip of someone walking becomes a fantasy character doing the same walk, with weight and momentum that doesn't feel like a puppet. The taste layer here is baked in: Runway has clearly trained on motion data that preserves physical plausibility, so output doesn't collapse into the liquid-limb horror that plagued earlier video gen tools. The editing surface is thin — you get the generation, not a timeline you can keyframe — but for the use case of 'I need this character to do this thing once,' it's actually good enough to ship.”

“The direct competitor here is ProtoPie and the half-hour a senior designer currently spends wiring flows before a usability test — and against that bar, Make Prototype wins clearly for standard linear flows. Where it breaks is conditional logic: any prototype that branches on user input, persists state, or simulates API responses is still entirely manual, and that covers maybe 40% of real usability test scenarios. What kills this in 12 months isn't a competitor — it's scope creep from Figma's own roadmap; if they ship smart-animate improvements and variable-aware connections, this feature either grows into something genuinely powerful or gets quietly deprecated as a stepping stone. I'm shipping it because the 60% it handles well represents hours of saved work per week for a design team.”

“The direct competitor is Kling's motion transfer and Adobe's Project Neo pipeline, and Act-Two holds up — the full-body fidelity is meaningfully better than what I've seen from Kling on complex locomotion. The scenario where this breaks is multi-person reference footage, fast cuts, or anything requiring consistent character identity across shots: you'll get a good single clip and a continuity nightmare the moment you need a second one. What kills this in 12 months is Sora or a native Adobe tool shipping motion transfer inside an NLE, at which point Runway's standalone credit-burning model competes on price it can't win — but that hasn't happened yet, so ship.”

“The job-to-be-done is precise: 'wire up a prototype fast enough that I can test it today instead of tomorrow,' and Make Prototype nails that single job without trying to also be a motion design tool or a handoff tool. Onboarding is essentially zero — if you've used Figma's prototype panel before, you invoke this from a right-click or command bar and the connections appear; there's no configuration screen. The completeness question is the honest limitation: you can't fully switch off manual prototyping because anything involving conditionals or data still requires hand-wiring, so it's a time-saver within an existing workflow rather than a workflow replacement. The specific product decision that earns the ship is that the output writes back into Figma's native connection format rather than a proprietary AI layer — your prototype remains yours and is fully editable without touching the AI again.”

“The thesis Act-Two bets on: within three years, the bottleneck for character-driven content will be performance direction, not production cost — and motion transfer is the primitive that makes amateur direction usable. That's a plausible bet, and Act-Two is early enough on the motion-transfer trend line that it's building the training data and user intuition before the curve steepens. The second-order effect nobody's talking about is that this decouples actor likeness from actor performance at scale — reference footage becomes a commodity input, and the implied rights framework hasn't caught up. The dependency that has to hold: Runway needs to maintain model quality leadership for 18+ more months against well-funded Chinese labs that are closing fast.”

“The buyer here is a mid-tier content creator or small studio, and the budget is 'generative AI tools' — a line item that's already crowded and getting scrutinized. The problem is the pricing architecture: credits burn per generation, which means a creator doing iteration-heavy work hits cost unpredictability fast, and the Unlimited plan at $95/mo is the only escape valve. The moat question is the real issue — Act-Two is a feature inside Gen-3, not a product, and Runway's defensibility depends entirely on model quality staying ahead of Kling, Pika, and whatever Adobe ships inside Premiere. The moment a platform player bundles 80% of this into an existing NLE subscription, Runway's standalone pricing story collapses. Good feature, shaky business.”