Designing the AI practice at Lextech.
Agent profiles, workflow frameworks, and integration roadmaps that help mid-market organizations adopt AI effectively — without disrupting team structure.
Help mid-market clients adopt AI effectively across Finance, HR, Engineering, and Leadership — designing agent profiles, workflow frameworks, and integration roadmaps that fit their teams.
Senior Product Designer and AI Experience Strategist — leading cross-departmental discovery, designing agentic AI solutions, and shaping the internal home for Lextech's AI Practice and AI Skills division.
Stronger stakeholder buy-in through collaborative facilitation, more targeted and implementable AI solutions, and an internal AI Practice site referenced in client engagements.
The challenge
AI is here, but most organizations don't know what to do with it — and the conversations that need to happen feel threatening more often than they should.
Mid-market companies want to adopt AI without dismantling the team structures and workflows they've built. The hard part isn't the model — it's identifying the right use cases, validating them with the people who'd actually use the agents, and designing integration paths that respect existing roles. That's the work this practice exists to do.
My charge at Lextech: lead the design of AI agents, workflow frameworks, and integration strategies that make emerging technology accessible and actionable for real business teams. And build the internal home — the AI Practice site — that supports our consultants and gets referenced in client engagements.
How I approach the work
Less "AI strategy" presentation, more sitting with the people whose work is about to change.
Cross-departmental interviews
Discovery sessions with Finance, HR, Engineering, and Leadership stakeholders — refined to feel collaborative, not threatening. That posture is where stronger buy-in starts.
Designing agent profiles
Defining what each AI agent should *be* — its scope, its boundaries, its handoffs back to humans. Treating an agent like a teammate, not a tool.
Workflow frameworks
Mapping how agents slot into existing workflows — not replacing them, augmenting them. Where the human stays in the loop, and where they don't need to be.
Integration roadmaps
Sequenced rollout plans that respect organizational reality — what to ship first, what depends on what, where the friction will be, and how to staff for it.
Decisions that mattered
Collaborative facilitation as the unlock
AI conversations get further when stakeholders feel like partners, not subjects. Refining how I run discovery — fewer slides about "the AI opportunity," more honest mapping of what the people in the room actually do — has been the difference between buy-in and resistance.
Agents as teammates, not features
Designing each agent as if it were a new hire — with a role description, clear handoffs, and boundaries — makes the integration question obvious instead of theoretical.
Build the internal site like a product
The Lextech AI Practice site is for our own team, but I designed it like a client-facing product — clean IA, real content strategy, an experience that consultants are proud to reference. Internal tools deserve product thinking.
What's changed
Specific examples covered in the full case study (request access below). Public-facing highlights:
Discovery interviews that surface stakeholder reality lead to AI solutions that are actually implementable — not theoretical.
AI agent design work spanning Finance, HR, Engineering, and Leadership — different audiences, shared facilitation approach.
Lextech's AI Practice site — used by internal teams and referenced in client engagements as a credibility surface.
Led UX for an AI-generated insights dashboard for GSK in parallel — see the GSK case study.
What I'd carry forward
The unlock for AI adoption is human, not technical. The conversations that turn AI into actual workflow change are the ones where stakeholders feel safe — and that's a facilitation skill, not a deck.
Agentic AI is design work. Defining boundaries, handoffs, and trust signals for an agent looks a lot like product design — the same craft, applied to a new collaborator.
17 years of "translate complex systems into human-centered products" turns out to apply directly to AI. The category is new; the discipline isn't.
Want to see the actual work?
The complete AI Practice case study — with framework artifacts, discovery outputs, and Lextech AI Practice site detail — is available as a password-protected PDF.