AI

AI.

Useful in the product. Useful in the work of making it.

Less brings design, product, frontend and AI capability to real tasks: the interaction people use, the workflow around it, and the system that helps a team build and maintain it.

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Where it is showing up.

Merchant activation

Less explored an AI-assisted path through quotes, contracts and onboarding using product design and code prototypes.

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Merchant activation prototype
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Design the work around the model.

An AI-generated offer is useful when a sales person can understand it, change it and move the merchant forward. For DoorDash, Less prototyped the product experience around a generated quote: commercial terms, human review, signature and activation in one working flow.

The prototype makes the generated content, the human decision and the status of the deal visible together.

DoorDash prototype screen showing an AI-generated merchant offer, proposed rates, contract access and a send-for-signature action
Prototype screen · AI-generated quote ready for review and signature

Make the generated offer inspectable.

The sales user sees the proposed plan and rates, opens the contract, adjusts the offer and decides when it is ready to send. The controls connect AI output to a real commercial decision.

DoorDash prototype quote screen showing pending signature status and activity history
After the send. The quote, signature state and activity history stay visible, so the next action is clear.
DoorDash prototype deals screen showing merchant offers in draft, pending signature, signed and activated states
Across merchants. Deal states make it possible to track drafts, signatures and activation as operational work.

Selected screens from a working prototype. Want the decisions behind them?

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Four kinds of practical work.

AI product design

Design the screens, controls and states around AI output: waiting, uncertainty, review, correction, approval and undo.

Interaction models · State inventories · Detailed product flows

Human–AI workflows

Map the task across people, AI and existing systems. Define decision rights, handoffs, exceptions and recovery.

Workflow maps · Handoff rules · Operational interfaces

Design systems for AI-assisted development

Make Figma and code legible to each other through semantic tokens, component properties, naming, guidance and build tests.

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Code prototyping

Test real behavior before committing to a build: representative inputs, responses, approvals and failure paths.

Interactive prototypes · Tested scenarios · Implementation decisions

AI changes the delivery system too.

When tools begin to read design files and generate code, component names, semantic variables and usage rules become working product infrastructure.

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What are you trying to make work?

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Make AI work in the product—and in the way the product gets made.