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ADO Pro

Role

Product Designer

Timeline

2024 to Present

Org

Omission

With

Afaan Muhammad | AI Engineer

Mike Wu | Full-stack Developer

Mohammed Shomis | Full-stack Developer

Selin Çakmak | Full-stack Developer

The Mission

Building an AI reporting tool for people who don't trust AI and don't love computers.

Arbeidsdeskundigen (Dutch occupational health experts) spend hours retyping information from medical files, employer statements, and job analyses into long-form assessment reports. The work that matters is the judgment. The work that eats the day is the transcription. We had three months to ship an MVP that would change that. I owned the product design end to end: research with practicing arbeidsdeskundigen, concept exploration, interaction and interface design, usability testing, and part of the front-end implementation alongside Mike.

Research collage with sticky notes, document folders, and product screenshots

The real constraint wasn't the deadline

Our users are experienced professionals, often later in their careers, and generally not confident with software. Several told us their previous reporting tools cost them time rather than saving it, they'd tried, and given up.

That reframed the problem. We weren't competing with manual work. We were competing with distrust of software itself. A tool that was powerful but confusing would fail the same way the last one did. Two things followed from that: Every AI output had to be inspectable and editable. Not a black box that produces a report, but a draft the expert corrects. The professional judgment stays theirs; the product just removes the typing. Complexity had to be spent carefully. Three months meant we could build one thing well. Not a flexible workspace with many entry points.

Phases
Uitnodiging (testcase)
Eerste verkenning
Eerste dossier
Zelfstandig werken
User actionsWhat is each step of the user journey?

Receives invite email for the testcase

Opens the link on desktop

Creates an account / signs in

Looks around the empty product

Tries to understand where work starts

Hesitates before uploading anything

Uploads medical / employer files

Waits for AI analysis

Reviews generated draft sections

Edits and corrects the draft

Starts the next dossier alone

Reuses the same upload → review path

Generates a complete report

Touchpoint

Invite email

Sign-in / landing screen

Home / empty state

Navigation

Help / tooltips

Sample language in UI

Upload entry point

Progress hints

Support contact

Upload drop zone

Analysis / processing state

Section review UI

Inline edit controls

Source document viewer

Save / continue

Dossier list

Familiar step flow

Report export

Return session

Key metricsWhat is the user trying to accomplish?

Invite opened

Account created

First session started

Time from invite → login

Reached upload CTA

Started a dossier

Abandoned before upload

Time on first screen

Files uploaded

Analysis completed

Sections heavily edited

First dossier finished

Second dossier started

Reached step four first session

Time to complete report

Return within 7 days

Pain pointsWhat's not working well? What causes friction? How many people does this affect? On a scale of 'nuisance' to 'show-stopper', how bad is this pain?

Unclear what ADO Pro is for

Low trust in yet another reporting tool

Fear of wasting time on setup

Too many possible entry points

Software anxiety: previous tools failed them

Unclear what documents are needed

No sense of how long it will take

Worry that AI will invent content

Black-box output feels unsafe

Hard to see what came from which file

Edits feel slow or fragile

Unsure when the draft is 'good enough'

Abandons mid-dossier without feedback

Still unsure about authorship / liability

Doesn't know if the tool is worth switching

OpportunitiesHow might we address these pain points? How big is the opportunity if we correct this pain point? What are new ways to serve this person?

Promise: assistant, not replacement

One clear next step after login

Single drop zone: no decisions yet

Show the path: upload → review → report

Use their language, not product jargon

Visible progress while files process

Reassure: every output stays editable

Inspectable, editable AI drafts

Link claims back to source docs

Keep judgment with the expert

One linear dossier flow, not a toolbox

Instrument abandon points in Mixpanel

Track which AI sections get edited most

Measure first-session completion to step 4

EventsTracking Events
invite_openedsignup_completed
empty_state_viewedupload_cta_clicked
dossier_createdanalysis_completedsection_edited
dossier_completedreport_exportedreturn_session

Results

70%

Time saved on administrative tasks

99%

Accuracy in document analysis

3X

Faster complete reports

what we learned, and what I'm testing next

We stayed in direct contact with the first users rather than inferring behaviour. Their language shaped the positioning: the recurring concern wasn't accuracy, it was authorship. The answer we'd designed toward: assistant, not replacement, became the product's central promise.

We learned that conversation is high-fidelity but low-coverage. We only heard from users willing to talk to us. So I proposed instrumenting the product with Mixpanel and instead of starting from events that were easy to log, I went back to the user journey and mapped the moments that would actually tell us something: where people abandon a dossier, which AI-generated sections get edited most heavily, and whether anyone reaches step four on their first session.