GURU MBA – USE CASES FOR START-UP FOUNDERS  

Overview

Most startups fail not because founders lack passion, but because they invest resources into building solutions nobody wants. This use case guides founders through rigorous, AI-accelerated validation: defining the problem, mapping target customers, pressure-testing assumptions, and designing a business model built for sustainability.

AI Agents Used

• Business Strategy – STR
• Market Benchmarking – MBK
• Innovation & R&D – IRD
• Customer Experience – CXP
• Funding Readiness – FRD
• Regulatory Compliance – RGC

Learning Objectives

• Apply Jobs-to-be-Done and Design Thinking frameworks to define the core problem
• Conduct rapid market research using AI agents to size the opportunity
• Test and iterate business model hypotheses with real customer signals
• Choose the right revenue model (SaaS, marketplace, services, freemium, etc.)
• Build a Lean Canvas as the strategic foundation of the startup

Deliverables

1. Validated Problem Statement
2. Customer Persona Map (3 segments)
3. Lean Canvas Business Model
4. Market Sizing Report (TAM/SAM/SOM)
5. Assumption Test Results

Implementation Steps

1.  Define the problem and draft initial hypothesis with Strategy Agent

2.  Map customer segments and identify early adopters

3.  Conduct 20+ customer discovery interviews (AI-guided scripts)

4.  Analyze patterns and validate/invalidate key assumptions

5.  Design and iterate on Lean Canvas with AI feedback

6.  Finalize business model and identify top 3 risks

Success Metrics

• Problem validated with 20+ interviews
• TAM > $100M USD identified
• 1+ paying early adopter secured
• Lean Canvas v2 completed
• Top 3 risks mitigated

Overview

Investors fund stories as much as numbers. This use case teaches founders to build a compelling business plan and pitch deck that communicates vision, market opportunity, traction, team, and financial projections with clarity and conviction. Using AI agents trained on winning pitch structures, founders produce investor-ready materials in a fraction of the traditional time.

AI Agents Used

• Business Strategy – STR
• Financial Modeling – FPR
• Market Benchmarking  – MBK 
• Business Plan Generator – BPG
• Sales Conversion – SCV
• Customer Retention – CRT
• Digital Marketing – DMK

Learning Objectives

• Structure a complete business plan aligned with investor expectations
• Master the 10-slide pitch deck framework used by top-funded startups
• Build credible 3-year financial projections with multiple scenarios
• Craft a compelling founder story and team positioning
• Anticipate and prepare for tough investor questions

Deliverables

1. Complete 20-page Business Plan
2. 10-Slide Investor Pitch Deck
3. 3-Year P&L + Cash Flow Model
4. Executive Summary (2 pages)
5. Investor FAQ & Objection Responses

Implementation Steps

1.  Define company narrative and core investment thesis

2.  Build a financial model with an AI agent (revenue, costs, unit economics)

3.  Draft each pitch section with AI coaching and real-time feedback

4.  Stress-test projections against comparable funded companies

5.  Conduct mock investor Q&A sessions with AI simulation

6.  Finalize and polish all materials for distribution

Success Metrics

• Pitch deck rated 8+/10 by AI scoring
• Financial model with 3 scenarios
• 15+ investor meetings booked
• Conversion rate pitch-to-meeting > 20%
• Term sheet received

Overview

The rise of no-code/low-code platforms, AI coding assistants, and intelligent automation has fundamentally changed what a small team can build. This use case equips startup founders with the frameworks, tools, and AI agent support to design, develop, and launch a functional app or system — without a large engineering team. From product specification to MVP launch, AI BIZ GURU guides every step: defining requirements, selecting the optimal technology stack, managing development workflows, and iterating based on user feedback. Founders learn to leverage tools like GitHub Copilot, Cursor, Replit, Claude API, OpenAI API, Bubble, and Webflow to compress months of development into weeks, while maintaining quality and scalability.

AI Agents Used

• Innovation & R&D – IRD
• Operations Scoring – OPS
• Business Strategy – STR
• Financial Projections – FPR
• Challenge Solver 
• Knowledge Base (Custom AI on your docs)

Learning Objectives

• Apply Product Thinking frameworks to define clear, buildable product requirements
• Select the optimal technology stack and development approach for your specific use case
• Leverage AI coding assistants (Copilot, Cursor, Claude API) to accelerate development
• Implement no-code/low-code tools for rapid prototyping and MVP delivery
• Manage an AI-augmented development workflow with minimal engineering headcount
• Build AI-native features (chatbots, recommendations, automation) into the product
• Establish DevOps practices: CI/CD, testing, and deployment with AI assistance
• Control development costs through smart tooling and AI-driven efficiency

Deliverables

1. Product Requirements Document (PRD)
2. Technology Stack Decision Matrix
3. AI-Powered MVP (functional prototype)
4. Development Cost & Timeline Plan
5. AI Tool Integration Map
6. User Testing Report (Beta)
7. DevOps & Deployment Workflow
8. Product Roadmap v1.0

Implementation Steps

1.  Define product vision and core user stories with AI BIZ GURU Innovation Agent

2.  Map functional requirements and prioritize using MoSCoW framework

3.  Evaluate and select technology stack (no-code vs. low-code vs. coded) with cost/complexity matrix

4.  Design system architecture and data model with AI assistant guidance

5.  Build MVP using AI coding tools: Cursor/Copilot for code, Bubble/Webflow for no-code layers

6.  Integrate AI features: connect Claude API or OpenAI API for intelligent functionality

7.  Set up automated testing and CI/CD pipeline with AI-generated scripts

8.  Launch closed beta, collect structured feedback, and iterate rapidly

9.  Analyze product metrics with AI and define v2 priorities

Success Metrics

• MVP launched within 8-12 weeks
• Development cost < $15,000 USD
• Core user flow completion rate > 70%
• Beta NPS score > 50
• < 5 critical bugs at launch
• AI features performing at > 90% accuracy
• Monthly active users growing > 20% MoM

Overview

Raising capital is a full-time job that competes directly with running your company. This use case gives founders a strategic, data-driven approach to fundraising: understanding dilution, crafting the right valuation narrative, identifying the right investors, and managing the full fundraising process from outreach to term sheet negotiation.

AI Agents Used

• Corporate Finance Agent
• Business Strategy Agent
• Financial Modeling Agent
• Sales Strategy Agent
• M&A & Investment Agent

Learning Objectives

• Understand funding stages, instrument types (SAFE, convertible notes, equity) and their implications
• Calculate fair valuation and acceptable dilution for each funding round
• Build a strategic investor targeting list with fit analysis
• Master the investor communication cadence and follow-up strategy
• Negotiate term sheets with confidence using AI simulation

Deliverables

1. Funding Roadmap (Seed → Series A → B)
2. Valuation Model & Cap Table Simulator
3. Investor Database (50+ targeted contacts)
4. Pitch Outreach Templates
5. Term Sheet Negotiation Playbook

Implementation Steps

1.  Map funding needs against 18-month milestone plan

2.  Model cap table scenarios across multiple funding structures

3.  Research and rank 50+ investors by fit, check size, and stage

4.  Design personalized outreach sequences with AI agent support

5.  Conduct investor meetings with AI-coached preparation

6.  Evaluate and negotiate term sheets with legal and financial agents

Success Metrics

• $500K+ raised at Seed
• Dilution < 20% per round
• 50+ investor conversations initiated
• 5+ term sheets received
• Time to close < 90 days

Overview

A great product without a go-to-market strategy is just an expensive hobby. This use case teaches founders to design and execute a GTM strategy that drives predictable customer acquisition. From positioning and messaging to channel selection, sales process design, and growth hacking — founders leave with an operating playbook they can execute immediately.

AI Agents Used

• Marketing Optimization – WFO
• Sales Conversion – SCV
• Digital Marketing – DMK
• Customer Retention – CRT
• Customer Experience – CXP
• Market Benchmarking – MBK
• Financial Projections – FPR
• Project Management – PMG

Learning Objectives

• Define brand positioning and core messaging that resonates with target customers
• Select and prioritize acquisition channels based on CAC/LTV analysis
• Build a repeatable sales process from lead generation to close
• Design growth experiments to find scalable acquisition loops
• Create customer retention and expansion strategies from day one

Deliverables

1. Brand Positioning Statement
2. GTM Strategy Document
3. Sales Playbook v1
4. Content & Channel Plan (90 days)
5. Growth Experiment Tracker

Implementation Steps

1.  Define ICP (Ideal Customer Profile) and buyer personas

2.  Craft positioning and messaging with Marketing AI

3.  Evaluate and select top 3 acquisition channels

4.  Build outbound/inbound sales process with AI agent templates

5.  Launch first 10 growth experiments and measure results

6.  Analyze conversion funnel and optimize with AI insights

Success Metrics

• 100 paying customers acquired
• CAC < 3-month revenue
• LTV/CAC ratio > 3x
• MoM revenue growth > 15%
• Churn rate < 5% monthly

Overview

Cash is the oxygen of a startup. Founders who lack financial discipline burn through their runway before achieving product-market fit. This use case installs the financial management systems, habits, and AI tools that give founders complete visibility over their finances, enabling smarter decisions on hiring, spending, and growth investment.

AI Agents Used

• Funding Readiness – FRD
• Financial Projections – FPR
• Financial Health & Opport. – FHO
• Risk Detection – RDT
• Cash Flow Optimization – CFO
• Strategy – STR
• Cost Optimization – CST
• Negotiation – NGT
• Tax Strategy Optimization – TSO

Learning Objectives

• Build a dynamic financial model that tracks actuals vs. projections
• Understand and control all key startup financial metrics (burn rate, runway, MRR, ARR)
• Design a budget that allocates capital to highest-ROI activities
• Establish cash flow forecasting and treasury management practices
• Plan and execute cost optimization without sacrificing growth

Deliverables

1. Dynamic Financial Dashboard
2. 18-Month Cash Flow Forecast
3. Monthly Budget Template
4. Key Metrics Tracking System
5. Cost Optimization Action Plan

Implementation Steps

1.  Map all current costs and categorize by strategic value

2.  Build financial model with Finance Agent (revenue, COGS, opex, capex)

3.  Set up automated financial reporting connected to accounting tools

4.  Define trigger-based decision rules (hiring, spending) tied to MRR milestones

5.  Run monthly financial reviews using AI-generated variance analysis

6.  Optimize top 5 cost categories using AI benchmarks

Success Metrics

• Runway extended to 18+ months
• Burn rate reduced 20-30%
• Monthly financial close < 3 days
• Gross margin > 60% (SaaS)
• Revenue forecast accuracy > 90%

Overview

People are a startup’s most valuable and most expensive asset. Early hiring decisions shape culture, speed, and success for years. This use case equips founders with frameworks for defining the roles they actually need, attracting top talent on a startup budget, onboarding effectively, and creating a performance culture that retains great people through the uncertainty of early-stage growth.

AI Agents Used

• Employee Productivity – EPD 
• Process & Policy Optimization – PPO
• Innovation – R&D Strategy – IRD
• Workflow Optimization – WFO
• Project Management – PMG

Learning Objectives

• Define organizational design aligned with current and 12-month business goals
• Build compelling job descriptions and employer value propositions for key roles
• Design a structured interview and evaluation process to hire for culture-fit and competency
• Create an onboarding experience that accelerates time-to-productivity
• Establish OKRs and performance feedback systems from day one

Deliverables

1. Org Design Blueprint (current + 12 months)
2. Top 5 Role Profiles & JDs
3. Interview Scorecard System
4. Onboarding Program (30/60/90 days)
5. OKR Framework & Review Cadence

Implementation Steps

1.  Map current team gaps against 12-month business milestones

2.  Define the 3 critical hires with role profiles using HR Agent

3.  Build recruitment pipeline using AI-assisted sourcing strategies

4.  Design culture documentation: values, working norms, decision frameworks

5.  Implement OKR system with quarterly review cycle

6.  Establish weekly 1:1 and team rituals with AI coaching support

Success Metrics

• Time-to-hire < 30 days for key roles
• 90-day retention rate > 90%
• Team engagement NPS > 60
• OKR completion rate > 70%
• Offer acceptance rate > 80%

Overview

Legal mistakes in the early stages can be fatal: misaligned co-founder agreements, unprotected IP, improper employee contracts, and regulatory non-compliance are among the top causes of preventable startup failures. This use case helps founders establish the legal foundations that protect the company, its intellectual property, and its relationships — without the $500/hour attorney fees.

AI Agents Used

• Legal Audit – LAU
• Patent & IP Portafolio – PIP
• Innovation – R&D Strategy – IRD
• M&A – Due Diligence – MAD
• Regulatory Compliance – RGC
• Cybersecurity Assessment – CSA
• Fraud Audit – FAU

Learning Objectives

• Understand the essential legal documents every startup must have from day one
• Design founder and shareholder agreements that prevent future disputes
• Protect intellectual property through trademarks, patents, and trade secrets
• Ensure compliance with data privacy regulations (GDPR, local laws)
• Evaluate legal risks in contracts with partners, customers, and employees

Deliverables

1. Founders Agreement Template
2. IP Protection Strategy
3. Standard Employee Contract Package
4. Privacy Policy & Terms of Service
5. Legal Risk Assessment Report

Implementation Steps

1.  Audit current legal status and identify critical gaps

2.  Draft and review founders agreement with Compliance Agent

3.  File trademark and define IP protection strategy

4.  Build standard contract templates for customers and suppliers

5.  Implement data privacy compliance framework

6.  Establish monthly legal risk review process

Success Metrics

• All founders documents signed
• Trademark filed in 30 days
• 100% employee contracts compliant
• Data privacy audit passed
• Zero contract disputes in Year 1

Overview

The journey from product-market fit to scalable growth requires a fundamental shift in how the company operates. What worked at 10 customers breaks at 100. This use case prepares founders for the operational, financial, and cultural transformations required to scale: building repeatable processes, implementing data-driven decision making, and transitioning from founder-led to team-led execution.

AI Agents Used

• Business Strategy – STR
• Operations Scoring – OPS
• Financial Projections – FPR
• Cost Optimization – CST
• Workflow Optimization – WFO
• KPIs Pyramid – KPI
• Process & Policy Optimization – PPO
• Customer Retention – CRT
• Sales Conversion – SCV
• Digital Marketing – DMK

Learning Objectives

• Diagnose and address the operational bottlenecks that limit growth at scale
• Implement OKR and data-driven management systems across all functions
• Design scalable processes for sales, customer success, and operations
• Build a management layer that extends founder leverage
• Develop a Series A narrative grounded in proven unit economics

Deliverables

1. Growth Diagnostic Report
2. Scalable Operations Playbook
3. Series A Readiness Checklist
4. Management Dashboard & KPIs
5. 18-Month Scaling Roadmap

Implementation Steps

1.  Conduct comprehensive growth diagnostic across all functions

2.  Identify and eliminate top 5 operational bottlenecks

3.  Implement company-wide OKR system with quarterly reviews

4.  Build playbooks for sales, CS, and operations to enable hiring

5.  Design and launch management dashboard with AI-generated insights

6.  Prepare Series A narrative with 12 months of KPI data

Success Metrics

• Revenue tripled within 12 months
• Gross margin sustained > 65%
• NPS > 50 at scale
• Time-to-close sales cycle reduced 30%
• Series A raised at target valuation

Overview

Strategic partnerships can compress years of growth into months. Whether through distribution agreements, technology integrations, co-selling arrangements, or channel partnerships, the right alliances give startups access to customers, credibility, and capabilities they could never build alone. This use case teaches founders to identify, structure, negotiate, and manage strategic partnerships that create sustainable competitive advantage.

AI Agents Used

• Business Plan Generator – BPG
• Valuation – VAL
• Cash Flow Optimization – CFO
• Risk Detection – RDT
• Negotiation – NGT
• Contracts Generation – CGE

Learning Objectives

• Map the partnership landscape and identify high-value alliance opportunities
• Design mutually beneficial partnership structures (revenue share, co-sell, OEM, etc.)
• Build a compelling partner value proposition that wins executive buy-in
• Negotiate partnership terms that protect startup interests
• Create partner management systems that scale beyond the first deal

Deliverables

1. Partnership Landscape Map
2. Top 10 Target Partner Profiles
3. Partner Pitch Deck
4. Partnership Agreement Template
5. Partner Success Playbook

Implementation Steps

1.  Map ecosystem participants and identify strategic white spaces

2.  Score and prioritize 20+ potential partners by strategic fit

3.  Design a partnership model with value quantification for each partner

4.  Build and execute a partner outreach campaign with AI support

5.  Negotiate and structure the first 3 strategic agreements

6.  Implement partner management cadence and joint success metrics

Success Metrics

• 3+ strategic partnerships signed
• 30% of new ARR from partner channels
• Partner NPS > 70
• Partnership pipeline of $2M+ ARR
• Co-marketing reaches 10x baseline

Strategy

AI Agents

Finance

AI Agents

Operations

AI Agents

Innovation

AI Agents

Marketing & Sales

AI Agents

HR & Culture

AI Agents

Legal & Compliance

AI Agents

Data & Analytics

AI Agents

Standard Access

$249 USD/month

Full platform access

Program Access

$99 USD/month

60% sponsored discount

vs. Traditional MBA

$100,000+ USD

Same knowledge base