Agentic UX & Copilot Blueprint

Architect AI agents and copilots your users will actually adopt — not fight. 2 weeks · €8,999 — strategy and UX sprint in one.

Most teams adding agents or copilots get the model right and the experience wrong. Users don’t know when to trust the agent, what it can do, or how to recover when it fails. This sprint architects the full agentic layer — where automation belongs, where it doesn’t, and the UX that makes every agent decision feel earned rather than arbitrary.

Why agentic UX fails without an architecture-first approach

⛔️ Traditional Approach:

  • UI team adds “AI mode” to existing feature
  • 3+ months of iteration to find the right automation scope
  • Users confused by what the agent does — support tickets spike
  • Agent UX is rebuilt every time a new agent feature ships
  • 3+ months, fragmented decisions, trust erosion

Poplab Agentic Blueprint:

  • Agentic behavior mapped before any UI is built
  • Decision model defines every automation boundary upfront
  • Each agent action is legible, reversible, or confirmable by design
  • Reusable agentic framework your team extends independently
  • 2 weeks, one sprint, a system that scales

Who this is for

This service is built for:

  • Seed–Series B product teams adding agents, copilots, or autonomous workflows to an existing product
  • Founders who’ve built the model but don’t know where — or whether — to surface it in the UX
  • Teams whose early agent features generated confusion, support tickets, or churn
  • Products where automation is being blamed for mistakes that were really UX failures

The problem (and what it costs you)

Your current agent or copilot probably:

  • Automates things users didn’t ask to be automated — eroding trust before it’s been earned
  • Has no clear boundary between “do it for me,” “suggest it,” and “ask me first”
  • Generates errors users can’t interpret, retry, or meaningfully override
  • Feels like a chatbot bolted on top of your product — not native intelligence embedded in a workflow

Every sprint you invest in agent UI without a clear decision model is sprint debt. You’ll pay it back in confused users, escalated support, and churn from the people who needed that feature most.

What you get

€8,999 · 2 weeks · Strategy + UX Sprint

  • Agent opportunity map — where agents should and should not exist in your product, with the rationale behind each boundary
  • Decision model — a structured framework for what’s fully automated, what’s suggested, and what requires explicit user confirmation
  • Prompt and context blueprints — input/output design, context window scoping, and data boundary documentation your engineering team builds against
  • 3–5 high-fidelity flows for key agentic moments — task delegation, error recovery, confirmation loops, progress visibility, and override patterns
  • Dev-ready specs — component annotations and interaction notes formatted for handoff
  • Agentic UX principles document — a reusable framework your team applies to every future agent feature without starting from scratch

No overlapping outputs. One sprint, one coherent architecture, ruthless focus on the moments that make or break agent adoption.

Process (2 weeks)

Week 1 – Architecture & Decision Mapping (Days 1–7)

  • Day 1–2: Kickoff + AI capability audit + competitive agentic UX teardown
  • Day 3–4: Decision model workshop — define the full automation spectrum
  • Day 5–6: Agent opportunity map + context blueprint drafts
  • Day 7: Review session — align on scope before design begins

Week 2 – UX Design & Dev Handoff (Days 8–14)

  • Day 8–10: 3–5 high-fidelity Figma flows for key agent moments
  • Day 11–12: Synthetic user testing through each flow
  • Day 13: Dev-ready specs + agentic UX principles document
  • Day 14: Loom walkthrough + implementation Q&A call

Outcomes you can expect

  • Agent features adopted in the first session — not after three support interactions
  • Fewer “why did the AI do that?” tickets — every agent decision is legible and recoverable
  • Faster engineering execution — your team builds against a decision model, not competing instincts
  • A reusable agentic architecture that extends to every new agent touchpoint without rebuilding the logic

Pricing, timeline, and terms

  • Price: €8,999 (excl. VAT)
  • Timeline: 2 weeks from kickoff to handoff
  • Payment: 50% to reserve, 50% on final delivery
  • Availability: 2 Blueprint slots per month

Trusted by AI startup founders from pre-seed to Series B

The brands and organizations we’re privileged to work with.

Mimecast
Prohibition Partners
Atalis
LettsArt
TKart
Geologie
Maistro
Aeonvis
Youdera

What Founders & Leaders Say

Brute-Force Outcomes. Measurable Impact. Real Voices from AI-Driven Product Teams.

“With Poplab’s AI-powered prototyping and UX/UI Design, our artists now launch galleries 36% faster—AI-first user flows translate directly to time-to-value.”
— Product Lead, LettsArt

“AI-driven user research and agile roadmapping unlocked a new era for our subscriptions. Churn dropped, and every new feature doubled as a growth engine.”
— Product Owner, Jot

Aeonvis

“Poplab’s blend of AI analytics and experience design not only improved our site’s look—it increased qualified leads by 32% and conversions by 36%.”
— Head of Digital Transformation, Aeonvis

Curious how these outcomes were achieved?

Ready to build an agentic experience users will actually trust?

Book a quick fit call and see if this sprint is the right lever to turn your AI capability into a product advantage — not a support burden.