AI-Native Product Designer · Sydney

Making complex products feel effortless.

I'm Homa, an AI-native product designer who works best in the messy middle of a problem: aligning teams, untangling systems, and shipping interfaces people don't have to think about. Most recently at Canva.

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← All work

Redesigning the Hello Coach member dashboard

Hello Coach connects people with accredited coaches across every area of life. I redesigned the member dashboard from a static welcome screen into the working home of the coaching journey: discover coaches, manage sessions and track progress in one place.

Project typeCoaching platform
CompanyHello Coach
RoleProduct Designer
OutcomeA dashboard that carries the full coaching journey: discover, book, join, and track
Problem

The dashboard was a welcome screen. Every real task lived somewhere else.

Move

Rebuild it around the four things members come to do: discover, book, join, track.

Result

Every core task now starts on the first screen members see.

The challenge

The first screen after login did none of the work. Hello Coach is an Australian platform matching people with accredited coaches across career, wellbeing, relationships and personal growth. The production dashboard was a card for your coaching team, a search box and a Life Tracker summary. Being coached happened on other pages.

New members had no first step, and returning members couldn't see their next session. The most common task, checking when your next session is and joining it, meant leaving the page built to be home. The Life Tracker, the platform's signature idea, showed completion percentages with no route from the numbers to an action.

Before: the dashboard as a static welcome screenAfter: the redesigned dashboard with guided steps, coach discovery and sessions

My role

Product designer on the dashboard redesign:

  • Audited the member journey to decide which tasks belonged on the dashboard
  • Designed the onboarding, coach discovery, session and progress modules, with every state from new member to active member to empty
  • Built the screens as a documented source of truth for engineering handover

The process

Guidance before features

New members get three steps, in order, on the page where they happen. Pick from your curated coaches, add coaches for other areas of life, book. The guidance is dismissible: it teaches the journey once, then gets out of the way.

Discovery where the intent is

Finding a coach moved from a bare search box onto the dashboard itself. Natural-language search ("what would you like help with?"), deeper filters and tabs for the eight life areas: growth, prosperity, career, wellbeing, relationships, identity, mindset, connections. Coach cards show what members decide on: the face, a line in the coach's own words, experience and location, with booking one click away.

Sessions as the centre of gravity

Each session row leads with the action its status calls for. Starting now says Join, upcoming offers its prep form, finished asks for a rating, cancelled says so plainly. The most common reason to open the app became a zero-navigation task.

Progress you can act on

The Life Tracker™ became a wheel you can act from. Eight life areas with per-area progress, sitting beside goals and your coaches, so noticing a gap and doing something about it happen in the same glance.

The outcome

The dashboard shipped as the daily home of the coaching journey, not a landing page in front of it. New members get a guided path to their first session, returning members join, prep and rate without leaving, and the Life Tracker went from a report to a starting point.

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From a single-model modal to a full video creation surface

When I joined Leonardo, video generation was a modal with a single model. As new models arrived monthly, that pattern couldn't hold. I led the design of a dedicated video creation surface where users choose models and configure generations within one consistent system, growing with the models toward professional-grade output, soundtrack included.

Project typeAI video generation
CompanyLeonardo.Ai (Canva)
RoleLead Product Designer
Outcome15M+ video generations in the surface’s first year, across 25+ model releases
Problem

Every new model exposed different controls. Twenty models would have meant twenty interfaces.

Move

One surface where a new model is a configuration, not a redesign.

Result

15M+ video generations in under a year, across 25+ model releases.

The challenge

AI video was the fastest-moving space in the product. Veo, Seedance, LTX, Kling and more arrived monthly, each with its own durations, dimensions, frame rates, audio support and reference inputs. Leonardo's position depended on shipping them fast: 25+ models across video and image in a single year, in partnership with Google, OpenAI and ByteDance.

Video had started as a modal with one model in it, and every launch strained it further. Each model's controls created new edge cases: unsupported durations, dimensions that conflict with aspect ratios, audio on some models only, costs that change with settings. Handled naively, every model would need its own UI and users would relearn the product with each launch.

Before: the single-model video modalAfter: the dedicated video creation surface

My role

Lead designer on video generation through this evolution:

  • Defined how differences between models are abstracted in the interface, so choosing one never requires reading a spec sheet
  • Evolved a single-model modal into a dedicated creation surface without breaking existing users' muscle memory
  • Designed how options behave when a model doesn't support them, and aligned design, engineering and model teams as new capabilities shipped

The process

A modal can't hold twenty models

The modal grew into a dedicated surface: pick a model first, then the controls adapt to what it can do. The structure stayed stable (prompt, model, settings, references) so existing users kept their muscle memory while the surface underneath became extensible.

The compatibility problem: references, start frames, end frames

The hardest differences weren't sliders, they were inputs. One model took an image reference, another a video reference, some a start frame, fewer an end frame. Adding a start frame could change which durations were offered. Twenty-five models multiplied by every input type is a compatibility matrix no user should have to think about.

So the interface carries the matrix instead of the user. Every input stays discoverable, each model enables only what it can honour, and anything incompatible shows as disabled with a plain-language reason. Switching models keeps your prompt and references and never throws work away. For new input types like start frames, I designed the onboarding that introduced them.

Switching models reshapes the controls (duration, dimensions, speed, styles and reference inputs) while the layout stays put.

Rules, not exceptions

Controls follow rules against a model's capabilities, not hand-designed quirks. Unsupported options appear disabled with a tooltip, never hidden, never a dead end. Locked sliders keep their footprint so the layout doesn't jump. Costs update as duration, resolution and audio change. Engineering resolves each new model against the same rule set instead of waiting on bespoke design.

Launch cadence as a design constraint

With launches landing monthly, repeatability was the craft. Model thumbnails and naming in a shared design kit, onboarding patterns for new capabilities, review turnarounds matched to engineering's pace. I ran bug bashes on each release to catch what erodes trust: a missing capability tag, a reference type that shouldn't appear for video, a tooltip clipping at a panel edge.

Growing with the models

The surface absorbed bigger capabilities without changing shape. Duration choices, 4K resolution, frame-rate control for professional workflows, and audio, both native model audio and audio references, as generated video pushed toward finished output.

The outcome

15M+video generations in under a year, platform only
25+models released across video and image
75Musers on the platform

The surface held. The squad formed in April and built video generation from the ground up on an image-first platform, delivering 40+ projects along the way, from Motion 2.0 through Veo 3.1 in 4K, with me as lead designer on every video launch. Each new model landed inside the same system users already knew. What would have been twenty-five redesigns became twenty-five configurations.

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Redesigning Leonardo's media viewer

Every generation on Leonardo.Ai opens in its media viewer (internally called the focus view), the moment users judge their work and decide what to do next. I redesigned it from a simple lightbox into the platform’s central workspace: browsable, information-rich, and built to hold any modality.

Project typeAI creative platform
CompanyLeonardo.Ai (Canva)
RoleLead Product Designer
OutcomeOne media viewer at the centre of every image and video generation
Problem

The most-trafficked surface after generation itself was a lightbox, and a dead end.

Move

Turn the viewer into a workspace: info panel, browsing rail, one layout for every modality.

Result

One media viewer at the centre of every image and video generation.

The challenge

The most important moment in the product was a dead end. The media viewer is where users see their work at full size and decide what happens next: the most-trafficked surface after generation itself. The production version was a lightbox: the asset, download, organise, delete. Fine for an image platform with a handful of models, not for one spanning images and video across dozens, with editing arriving fast.

Acting on a generation meant closing it and hunting. Upscaling, animating or using an output as a reference meant leaving the view; comparing two outputs meant close and reopen. The prompt, model and settings behind a result weren't visible, so users couldn't learn from what worked or reproduce it. And the replacement had to work identically for an image, a ten-second video, an edited variant, and whatever modality shipped next.

Before: the media viewer as a simple lightbox with download and deleteAfter: the redesigned media viewer with browsing rail, info panel and conversational iteration bar

My role

Led the UX direction for the redesign:

  • Rethought the surface where users view, refine and act on their generations
  • Simplified existing patterns while planning for extensibility across modalities, including how editing options appear, adapt and disable per content type
  • Aligned design, engineering and product through reviews and prototypes

The process

From lightbox to workspace

A side panel puts prompt, model, settings and metadata beside the asset, with the highest-value actions one click away. Upscale, create video, use as guide. Nothing about the asset is a mystery any more, and nothing users want to do next requires leaving. I iterated the panel's hierarchy through reviews with the founders, down to the weighting of the main action.

A rail for browsing

A thumbnail rail turned the viewer into a browser. Moving between generations became a flick of the scroll wheel or a keystroke instead of close-and-reopen, so reviewing a batch means comparing rather than navigating. Global wheel-to-browse had to coexist with scrolling inside an expanded prompt, and I caught and drove the fix when the two fought each other.

One view, every modality

The layout is defined as rules, not as an image view with video bolted on. A media area that adapts to any aspect ratio and playback type, panel modules that appear per asset (video gets its player and format options, images their guide and upscale paths), and a conversational iteration bar where users describe a change in plain language. Options an asset can't use disable gracefully instead of disappearing, the same principle I later scaled across video generation.

The outcome

Revamped the Focus Modal, which fundamentally changed how users discover the platform and interact with Leo across image and video.

The redesigned viewer shipped as the centre of gravity for the whole platform. Browsing, understanding, editing and acting on generations all happen without leaving. It carried images and video from day one and absorbed the editing capabilities that followed.

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Designing Leonardo's first audio generation experience

Leonardo was built around images, but as its video models matured toward professional-grade output, silent video became the obvious gap. I designed Leonardo's first audio generation experience: a modality with no visual output, with new controls like duration and instrumental mode, inside the generation system users already knew. It supported both paths creators needed: generating from a prompt, or referencing an existing track to guide the output.

Project typeAI audio generation
CompanyLeonardo.Ai (Canva)
RoleLead Product Designer
OutcomeLeonardo's first audio modality: one surface carrying its whole audio model family
Problem

Audio has no thumbnail. Every surface in an image-first product assumed one.

Move

Make the card do the work, and fit two mental models into the one generation flow.

Result

Three models at launch on one surface; a fourth added within weeks, no redesign.

The challenge

Professional video needs sound, and the workflow broke at its final step. Video outputs were getting long enough, and good enough, for real work, but a soundtrack meant leaving for another tool. Audio generation closed that loop and opened a new creative surface of its own. It was a true zero-to-one: Leonardo had never shipped a modality without a visual result.

Audio has no thumbnail. Grids, previews and the media viewer all assumed a result you judge at a glance; audio is judged over time, by listening. It needed its own way to be browsed, previewed and compared without fragmenting the product. And one surface had to serve two mental models: generating from scratch (a blank prompt) and steering from a reference track (closer to editing).

My role

Led the design of the audio generation experience:

  • Defined how a modality with no visual output is browsed, previewed and compared in an image-first product
  • Designed the controls (duration, instrumental mode, quantity) so musicians and non-musicians both get to a good result
  • Worked with research, engineering and product to ground the design in what the models could reliably deliver

The process

Designing for something you can't see

The card became the product. A waveform, file name and duration readable at a glance, with play and scrub built in. Audio cards follow the same grid logic as images and videos, so a new track lands exactly where a new image would. Names, durations and waveforms do real identification work when comparing files, down to how duplicate names resolve so two tracks never become indistinguishable.

Two mental models, one surface

Creating from scratch and steering from a reference live in the same flow. The reference is an input you add, and every control keeps its meaning in both modes. One surface to learn, two ways in.

Controls that speak human

The model exposed parameters; creators needed decisions. Raw settings became duration, an instrumental toggle for music without vocals, and how many variations to generate, with defaults that give a first-time user a good result from nothing but a prompt, and seeds for anyone chasing repeatability.

Native, not bolted on

The fastest way to make a new modality fail is to make it feel like a separate app. Audio reused the prompt-first flow, the same generation history and the same system, so anyone who had generated an image already knew how to generate a track.

The outcome

Audio shipped in mid-2026 as Leonardo's first non-visual modality: three models at launch, spanning music, sound effects and dialogue, on one generation surface. Because the design abstracted the surface from any single model, a fourth model slotted in within weeks of launch without a redesign.

Within days of shipping, teams were demoing audio to Leonardo's largest enterprise customers, and it became how creators finish a video with its soundtrack without leaving the product.

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Goals Platform: a design system that powers agentic prototypes

The Goals Platform is one of Canva's most public initiatives. Its landing page couldn't scale: every new region meant an expensive rebuild, the content was written by the public, and each launch started from zero data. I helped reframe the relaunch as a systems problem, and built a design system that people and AI agents can both build with. It carried the platform across regions, became the foundation for the team's agentic product prototypes, and gave me a practical way to help product design change how it works with AI.

Project typeDesign system, AI enablement, web platform
CompanyCanva
RoleProduct Designer
OutcomeOne system carrying three regions and powering the team's agentic product prototypes
Problem

A landing page rebuilt for every region, filled with content nobody controls, launching each time with zero data.

Move

Reframe the page as a platform on a variable-driven design system that agents can build with, not just people.

Result

Three regions and 40,000+ goals on one system, and a foundation for agentic prototyping across the team.

The challenge

Asking people everywhere what future they want to help create, and giving a voice and a platform to those goals. It starts with one simple question: what's one goal you'd like to see achieved in your lifetime, for your community, your country, or the world?
Melanie Perkins, Canva co-founder

Phase 1 was a single landing page. Phase 2 arrived with a hard campaign deadline, a named next region, and a growing dataset nobody was seeing. Three constraints shaped everything: a fixed timeline, future regions certain but undefined, and public, anonymous submissions of any length and language, arriving at an unpredictable rate.

Underneath the brief sat three design problems:

  • Scale without rebuilds. Duplicating the site per region multiplies design and engineering cost and lets regions drift apart. Marginal cost per region had to approach zero.
  • Content we don't control. One word or a thousand characters, in any language or script, including right-to-left. Localisation was a first-class requirement from day one, and the layout had to absorb all of it while still feeling like it came from real people.
  • Data that starts at zero. A region launches with no submissions and grows to thousands. The same page had to be honest and compelling at both ends of that curve.
BeforeAfter

My role

Drove the UX of the platform's hardest surfaces:

  • Defined how unpredictable, user-generated content is abstracted into a system the interface can rely on
  • Built the design system underneath the platform: colour, type and spacing as variables mapped per region, on a fluid layout, so every new region ships fast and stays consistent
  • Shaped the data visualisation: how community themes are ranked, when a pattern is real enough to show, and how the story stays honest at any volume
  • Simplified submission to the fewest possible decisions (every field optional, anonymous), on one interaction model that survives translation, right-to-left scripts and every viewport
  • Set the design system up so AI agents could build working prototypes with it, and helped drive AI enablement and change management across product design
  • Kept design, engineering and marketing aligned so system decisions held under campaign deadlines

The process

A platform, not a page

We weighed a fast bespoke USA page against a themable system, and chose the system. It cost more upfront and made every region after it nearly free. The same foundation shipped the USA, Wollongong and a global edition.

A design system built to scale fast

Colours, type and spacing were defined once as variables and mapped per region, on a fluid layout that holds from mobile to widescreen. That is what made "a region is a configuration" true in practice. Launching a region means setting a handful of values, not redrawing screens, so every region looks like its own while staying consistent underneath. It also kept us fast under a fixed campaign deadline: a change was made once and carried across every region and every viewport.

We stress-tested the claim with the hardest case available: a full right-to-left Arabic localisation. If the system survived RTL, any new region was trivial.

From design system to agentic prototypes

Because the system lives as variables, components and written rules rather than pictures in a file, AI agents can read it as well as people. That made it the foundation for the team's agentic product prototypes: agents build working prototypes on the real tokens and components, so what comes out looks and behaves like the product instead of a generic mock-up.

Getting there was as much change management as design. I helped product designers move from static mock-ups to prototyping with agents, starting from a system they already knew, so trying the new workflow didn't mean giving up the craft standards they cared about.

Content we don't control

Goals render as handwritten postcards. One handwriting font per region, encoded as a component so the decision outlived the design file. Postcard sizing followed the real 1,000-character data, not idealised one-liners.

Data that stays honest

Theme bars scale proportionally, labels relocate when bars get small, and the display caps at four categories. Past that, slivers read as noise. Since a region's launch day is its emptiest day, the zero and low-data states are an invitation to participate, with a submission flow that lowers every barrier: all fields optional, anonymous in seconds.

The outcome

3regions on one foundation: USA, Wollongong, global
8,000+goals in Wollongong’s opening weeks, against a 20,000 target
40,000+goals collected across all sources

Phase 2 shipped on deadline in mid-2026, and the systems bet paid off. The same variables and fluid layout carry every region, so each new one is a configuration pass rather than a design project, and the phase that followed was built directly on the system rather than rebuilt. The same system now does a second job: it is what the team's agentic product prototypes are built on.

Reflection

When a brief says "relaunch the page," the leverage is usually in questioning the noun. Reframing a page as a platform cost us harder conversations early and saved every team that came after. It also stayed collaborative under pressure, with designers and engineers resolving edge cases together in threads rather than throwing files over a wall. The bigger lesson came later: a design system written clearly enough for agents to use is also the easiest way to bring a team into working with AI.

About Homa Sheikh

Hi, I'm Homa, an AI-native product designer with 17+ years in design, drawn to complex product problems and the craft of making them feel simple.

A bit about me

Outside of product work I paint: my pieces have shown at the Stencil Art Prize in Sydney and at fortyfivedownstairs in Melbourne, and that art practice is where a lot of my visual instincts come from.

The rest of my time goes to travel, cooking, and camping: I'm happiest planning the next trip, feeding people, or somewhere off-grid with a tent.

I also volunteer with DanceWize, supporting safer festival and event communities.

Experience

  • Product Designer
    Canva · Sydney
    2026 – Present

    Product designer in Canva's MarTech group, helping drive AI enablement and change management across product design. I build the design systems that power our agentic product prototypes, and help the team change how it designs with AI day to day.

  • Product Designer
    Leonardo.Ai (Canva) · Sydney
    2024 – 2026

    Designed across the core generation experience of an AI creative platform that grew to 75M users. Lead designer on video generation (from a single-model modal to a surface that carried 15M+ generations in its first year) and on Leonardo's first audio modality.

  • Senior Digital Designer
    Webqem · Sydney
    2023 – 2024

    Led high-fidelity prototypes, wireframes, UI and brand guidelines for digital products at a Sydney digital agency, across clients in advertising, education and Web3, translating complex briefs into clear interfaces on tight timelines.

  • Product Designer
    Hello Coach · Sydney
    2023

    Redesigned the member dashboard into the working home of the coaching journey: guided onboarding, coach discovery across eight life areas, status-driven session management and goal tracking on one screen.

  • Senior Product Designer
    NFTuence · Remote (UK)
    2022 – 2023

    Designed apps and websites end to end for a Web3 agency, from user flows to high-fidelity prototypes, and led ideation for new NFT products, including pitch work that helped win the MUSESS project.

  • Earlier design roles
    Art direction & graphic design
    2007 – 2019

    Art director and graphic designer across brands, agencies and startups, including Oticon, RVD, Digistyle and ZoodFood: the visual and brand foundation behind the product craft.

Education

Bachelor of Graphic Design.

Technical skills

Design & systems

Figma: components, variables, multi-brand theming and design systems; responsive and accessible design.

Adobe Creative Suite

Illustrator, Photoshop, InDesign, After Effects, for illustration, motion and brand work when the project calls for it.

Prototyping & testing

High-fidelity Figma prototypes, coded and AI-assisted prototypes, moderated and unmoderated user testing.

Delivery & collaboration

Engineering handover and QA, bug bashes, design reviews, sprint workflows and stakeholder alignment.

Exhibitions & volunteering

  • Stencil Art Prize · Finalist, Sydney, 2019
  • SMALL, fortyfivedownstairs · Group exhibition, Melbourne, 2022
  • DanceWize · Volunteer