Jay SethiSelected work & ideas, Overview Toronto, Canada Remote

Product strategy / Experience architecture / Applied AI

PORTFOLIO / 2026

Make the complex clear.Then make it work.

I’m Jay Sethi. I help teams make sense of complex problems, choose a direction and turn it into a useful product or way of working. My work connects customer insight, experience architecture and hands-on delivery.

20+ years across agency & enterprise.
Selected employment and client work.

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01

Selected work

Five interactive case studies ↗

Different problems.
Decisions you can follow.

Each case follows the thinking: what to investigate, what to change and how to make the work useful.

NJM / Competitive intelligence

Make the research reusable.
Not just the presentation.

I built an AI-assisted research harness that retains sources, applies consistent criteria and turns a competitive assessment into a repeatable intelligence capability.

11 carrier ecosystems12 synthesis dashboards

Research architecture · Information architecture · AI workflows

Explore the intelligence system
The thinking, the decisions and the system behind each project.Earlier experience design work , (2024 PDF)
02

Capabilities

Where I’m most useful

From “what should we do?”
to “here’s how it works.”

01 /

Find the
right problem.

Clarify the customer problem, compare the options and help the team agree on a direction before the roadmap hardens.

What I makeDiscovery plans, opportunity maps, product direction and prioritized briefs.
See the diagnostic approach
02 /

Make the
experience coherent.

Make journeys, information and reusable components work as one experience. Define the details that carry through to delivery.

What I makeInformation architecture, service models, workflows and build-ready requirements.
See the product architecture
03 /

Make expertise
repeatable.

Turn useful methods into AI-assisted workflows people can use again, with supporting evidence, meaningful checks and clear review responsibilities.

What I makeResearch systems, working prototypes, review standards and reusable team capabilities.
See the operating approach
Ways to work togetherFocused diagnosticProduct & experience strategyTeam & capability leadership
03

Experience & résumé

Agency + enterprise + independent

Set the direction.
Stay close to the work.

I bring 20+ years across product strategy, UX, information architecture and client leadership. My work spans commerce, financial services, insurance, healthcare, pharma and enterprise software.

Today, I bring that experience to hands-on AI-assisted development: framing opportunities, working through trade-offs and building systems a team can test and improve.

Strategy matters most when people can act on it.

Request a tailored résumé
LinkedIn

Independent

Strategy + systems

Consulting and product development across conversion diagnostics, agency workflows, competitive intelligence and source-backed information products.

Ascendis / RONA

Experience strategy

Connected commerce journeys across navigation, search, product pages, cart, checkout and fulfilment.

BMO Harris Bank

Product ownership

Digital banking direction, roadmap ownership and alignment across an approximately 30-person cross-functional team.

Havas

Experience leadership

Client-facing discovery, experience architecture and direction of multidisciplinary work across enterprise and life-sciences engagements.

Lone Wolf

Design team lead

Managed a five-person design team while remaining hands-on with enterprise financial software experiences.

Earlier & additional experience

MaRS Discovery District: UX Design Lead
General Assembly: UX & Product Design Instructor
Baywood FHO: Digital Transformation Consultant
Brightworks: Information Architect
TUI / First Choice Travel: UX Designer

04

Writing & field notes

How I think about the work

Compare the options. Explore the next question.

These guides compare the landscape. The notes explore what a team could do next.

Short field notes

01 / OPERATIONS

An AI-native agency needs a workflow, not a prompt collection.

The useful question is not only how quickly a model can generate variants. It is whether strategy, evidence, creative judgment and review can move together without losing the context that makes the work usable.

I’m interested in connecting those handoffs: reusable briefs, explicit claims, bounded generation, meaningful checks and human decisions. The output is an operating capability, not simply a larger pile of content.

See this thinking in the AI sprint
02 / EVIDENCE

A source link is the beginning of trust. Not the end.

A system can retain the page a fact came from and still misunderstand the fact. Source identity, document versions, meaning and review decisions deserve separate attention.

That distinction shapes my evidence systems: make the supporting passage inspectable, preserve uncertainty and test the interpretation, not just the plumbing. Better prompts cannot substitute for a clearer information model.

See the lesson from AIKG
03 / ARCHITECTURE

Information architecture has a human and a machine audience.

For a person, useful content needs a clear purpose, a meaningful place and a next action. For a machine intermediary, the source, entity, context and relationships need to remain legible too.

I treat those as connected design questions. Can the person find what matters? Can a system retrieve it? Does the context survive the handoff? My competitive research keeps those questions separate enough to answer honestly, and connected enough to inform experience strategy.

Explore the competitive harness
04 / EXPERIENCE

The problem is often underneath the screen.

A confusing interface may be expressing an unclear rule, an awkward handoff or a mismatch between content and intent. Redesigning the surface is only part of the work.

In the RONA review, I would keep useful returns information and factual warranty details. The recommendation is narrower: only use the optional warranty callout when an applicable benefit supports it. The display rule changes, not the facts.

See the component decision
05 / APPLIED AI

Use Jev to suggest the macro, not authorize the action.

A macro trigger is only one decision. I would also test where a statement belongs in a SOAP note, which reusable component fits, and whether it needs a supported modifier, another component or more context.

Adding a stated qualifier is not the same as filling a gap. Repeated edits may reveal that a template needs redesign, but fixing today’s note and changing the shared library should remain separate, reviewed decisions.

Jev would help propose those choices, not write undocumented findings or authorize clinical actions. I would judge the workflow by preserved meaning and less clinician correction, not by how much it automates.

The full field note develops the idea with a synthetic conversation, four kinds of component mismatch and a practical evaluation plan.

Research-informed proposal, not a tested clinical integration. The full article includes the evidence and limitations.

Read the full Jev & SOAP field note

What are you trying
to move forward?

A customer journey. A new product. A team’s next chapter.
Let’s start with the problem and make the next move clear.

Email JayConnect on LinkedIn
Open to select leadership roles, consulting and advisory engagements.Based in Toronto · Working remotely

Find something in my work

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