Duration: 10 Weeks

Sessions: 1–2 sessions per week (90 minutes each, live or recorded)

Learning Style: Hybrid learning (Live Cohorts + Self-Paced Videos + Slack Labs)

Capstone Project: Research, design, build, and deploy a fully functional AI agent with a custom UI, backend automations, and real data workflows

Best For: Mid-size to enterprise teams in Product, Ops, HR, Legal, CX, or Innovation—especially non-technical professionals ready to lead AI initiatives

Includes:

• Live mentor support
• Hands-on tool labs (Replit, Figma, n8n, Make.com)
• UX prototyping + prompt engineering
• Final pitch day + certification

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

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.

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.

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.

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.

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.

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.