UX/UI & Product Innovation Accelerator

Design Smarter. Build Better. Get Future-Ready.

A 6-week accelerator for founders, creatives, and non-technical builders to master UX/UI design, AI-integrated product development, and launch-ready prototyping.

  • Program Overview

    The **Phazur Labs Information Architecture, UX/UI, and Product Innovation Accelerator** is a rigorous, project-driven program designed to transform students into world-class UX/UI designers, product innovators, and interface architects ready to excel in today’s most competitive design and technology sectors.


    Throughout the course, students will:


    - **Identify** the core principles of user-centered design, information architecture (IA), and UI design innovation through guided discussion and applied examples. *(C1 – Remembering)*

    - **Describe** the role of UX personas, user flows, and wireframes in the UX/UI process, using class templates and examples. *(C2 – Understanding)*

    - **Apply** basic prototyping and layout principles to create responsive interfaces using tools such as Figma. *(C3 – Applying)*

    - **Follow** step-by-step exercises to conduct user interviews, build personas, and organize information via card sorting. *(P2 – Guided Response)*

    - **Complete** scaffolded UX/UI projects with peer and instructor support that reflect common design workflows. *(P2 – Guided Response)*

    - **Respond to** user testing feedback and critique sessions by making low-level design revisions and documenting reasoning. *(A2 – Responding)*

    - **Participate in** team-based design challenges that simulate freelance or stakeholder scenarios, including pitch and client proposal development. *(A2 – Responding)*

    - **Use** provided templates and best practices to assemble a complete digital portfolio including wireframes, IA diagrams, research summaries, and polished UI screens. *(C3 – Applying)*


    Graduates of this program will leave equipped not just with technical skills, but with the critical thinking, user empathy, storytelling ability, and product development acumen necessary to succeed as elite UX/UI professionals, startup founders, or product leads.

  • Course Breakdown & Tools

    Program Goal

    Empower non-technical professionals to confidently lead AI initiatives by learning how to:


    • Think strategically and identify high-impact opportunities
    • Structure and validate real-world use cases
    • Design intuitive, AI-powered user experiences
    • Build intelligent agent systems with custom interfaces and automated workflows

    Program Format

    Hybrid Learning Experience - Includes live cohort sessions, self-paced video modules, and ongoing support through our collaborative Slack Labs community.


    Core Tools You'll Use

    • AI & Automation - OpenAI, Claude, Make.com, n8n
    • UI & UX Design - Figma, Notion
    • Frontend & Data - Replit, Replit DB, Airtable
  • Stage 1: Innovation Thinking + Structural Research (Pre-Build Phase)

    Module 01: Innovation by Industry

    • Duration: 2 hours
    • Outcome: Learn frameworks to uncover pain points in industries like Healthcare, Finance, Retail, HR, and Government. Analyze current trends and operational inefficiencies.

    Module 02: Persona & Journey Mapping

    • Duration: 2 hours
    • Outcome: Develop primary and secondary personas. Map “day-in-the-life” workflows to identify high-friction areas ideal for AI automation.

    Module 03: Writing R&D Scope of Work (SOW)

    • Duration: 2 hours
    • Outcome: Learn to write a clear and structured SOW for AI projects—defining objectives, stakeholders, constraints, and data flow requirements.

    Module 04: SOP + PDD Documentation

    • Duration: 2 hours
    • Outcome: Standardize your proposed solution with SOPs (Standard Operating Procedures), Process Decision Documents (PDDs), and logic blueprints.

    Module 05: Domain Field Study + Validation

    • Duration: 2 hours
    • Outcome: Conduct interviews and desk research to validate your concept. Define success metrics using real-world insights.
  • Stage 2: UX Design Thinking + Systems Modeling

    Module 06: Information Architecture + Card Sorting

    • Duration: 2 hours
    • Outcome: Structure how users will interact with your AI system. Organize concepts into workflows and define navigation and content strategy.

    Module 07: UX Pilot Design in Figma

    • Duration: 3 hours
    • Outcome: Design low-fidelity wireframes of your agent’s interface. Create prompt layouts, feedback loops, and key interaction flows for desktop and mobile.
  • Stage 3: Agent + UI Engineering Stack

    Module 08: Replit UI Bootcamp

    • Duration: 4 hours
    • Outcome: Build the frontend of your AI agent using HTML, CSS, and JavaScript in Replit. Create inputs, buttons, and display areas. Connect APIs and store user data using Replit DB.

    Module 09: Automating with n8n (Open Source)

    • Duration: 4 hours
    • Outcome: Set up backend workflows to automate actions triggered by user inputs. Integrate tools like Notion, Google Suite, and CRMs to create dynamic, responsive systems.

    Module 10: Make.com Deep Dive

    • Duration: 4 hours
    • Outcome: Visually orchestrate AI task flows. Automate document creation, alerts, follow-ups, and more using Make.com’s drag-and-drop interface.

    Module 11: Creating & Querying Datasets

    • Duration: 3 hours
    • Outcome: Build structured datasets using Replit DB, Airtable, or JSON. Enable your agent to query, search, and respond using this data within a UI-driven experience.
  • Stage 4: AI Prompt Logic + Safety Systems

    Module 12: AI Workflow Engineering

    • Duration: 3 hours
    • Outcome: Design advanced prompt flows using ReAct, Tree-of-Thought, and Chain-of-Thought methodologies. Implement fallback logic, confidence scoring, and modular prompt structures for reliability.

    Module 13: Responsible AI + UX Testing

    • Duration: 2 hours
    • Outcome: Learn the principles of ethical AI deployment. Conduct bias checks, red-teaming exercises, accessibility audits, and scenario-based error testing to ensure your agent is safe, inclusive, and effective.
  • Stage 5: Final Delivery + Pitch Day

    Module 14: Final Agent Project

    • Duration: 5 hours
    • Outcome: Bring everything together in a polished, working AI agent system.

    Final project must include:

    • A custom frontend interface
    • Backend automations and logic flows
    • Integrated datasets and prompt structures
    • Supporting documentation (SOW, SOPs, UX design)
    • A live walkthrough or recorded demo

    Pitch Day: Present your solution to peers, mentors, and potential partners. Showcase how your agent solves a real-world problem from insight to interface.

  • What Students Walk Away With

    By the end of the program, students will have:


    • A fully functional AI agent system, complete with custom UI, automation, and data integration
    • A documented innovation pipeline including SOWs, SOPs, and user journey artifacts
    • UX prototypes and design files built in Figma, with information architecture and interaction flows
    • A hosted frontend interface and working backend logic (no-code or low-code)
    • A practical understanding of prompt engineering, system logic, and AI workflow design
    • Ethical deployment knowledge with testing frameworks for bias, safety, and accessibility
    • Templates, tools, and repeatable frameworks to replicate the process for new use cases
    • A final project demo ready to pitch internally or publicly

    This isn’t just a certificate—it’s a real-world portfolio project designed to showcase leadership in AI innovation.

Ready-to-Launch Use Case ExamplesS

Examples of real-world agent systems students can build and deploy by the end of the program:


  • Product Teams: Idea validation assistant or feature request router with automated stakeholder feedback loops
  • Sales Departments: Proposal or pitch deck generator based on deal stage and client persona
  • HR Teams: AI-powered hiring and onboarding assistant with form collection, scheduling, and FAQs
  • Operations Teams: SLA tracker that monitors workflows and auto-generates response templates
  • Legal Departments: Internal compliance and policy Q&A bot with built-in ethical guardrails
  • Customer Experience Teams: Sentiment-aware support assistant that routes tickets and suggests responses
  • Innovation Leads: Cross-functional AI prototype for internal R&D, powered by prompt-based workflows


These use cases are just the beginning—students will leave with the tools to build, scale, and adapt agents across any industry.