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AI Factory Sales Playbook

This document helps you (and future sellers) position, qualify, and pitch the AI Factory to potential customers. It is written for sales, product, and business development teams.

The AI Factory is ConnectSoft's core product—an agentic platform that generates production-ready SaaS microservices. This playbook provides the framework for identifying ideal customers, understanding their problems, and positioning the Factory as the solution.

Tip

Strong Pitch: "The AI Factory transforms how you build SaaS. From idea to production-ready microservice in days, not months—with Clean Architecture, DDD, and observability built-in. Your team owns all generated code, and we provide the platform that makes it possible."

Ideal Customer Profile

Segment Characteristics Red Flags
Mid-Market SaaS Companies 50-500 employees, building SaaS products, .NET/Azure stack No engineering team, no Azure commitment
Enterprise Platform Teams Internal platform teams, building microservices, need consistency No .NET/Azure, prefer low-code/no-code
Startups with Technical Founders Technical founders, building SaaS, need speed No budget, prefer open-source only
Consulting/Professional Services Building custom solutions for clients, need efficiency No .NET expertise, prefer generic tools
ISVs Building SaaS Products Independent software vendors, building products No Azure commitment, prefer other clouds

Red Flags to Watch For

  • No Engineering Team - Factory requires technical team to operate
  • No Azure Commitment - Factory is Azure-centric
  • Prefer Low-Code/No-Code - Factory generates real code, not low-code
  • No Budget - Factory requires investment
  • No .NET Expertise - Factory generates .NET code

Problems We Solve

Problem 1: Slow Delivery

Symptoms: - Months to deliver new microservices - Long development cycles - Slow time-to-market

Factory Solution: - Days to first running microservice - Automated code generation - Consistent architecture patterns

Problem 2: Inconsistent Architecture

Symptoms: - Different patterns across services - Technical debt accumulation - Hard to maintain

Factory Solution: - Consistent Clean Architecture - Standardized patterns - DDD and event-driven by default

Problem 3: Lack of Platform Team

Symptoms: - No dedicated platform team - Ad-hoc infrastructure - No standardization

Factory Solution: - Factory acts as platform team - Standardized templates and libraries - Consistent CI/CD and infrastructure

Problem 4: High Development Costs

Symptoms: - Expensive development teams - Slow development velocity - High maintenance costs

Factory Solution: - Reduced development time - Lower maintenance through consistency - Faster feature delivery

Key Value Messages

Value Message 1: Speed

Message: "From idea to production-ready microservice in days, not months."

Supporting Points: - Automated code generation - Pre-built templates and libraries - Standardized CI/CD pipelines - Reduced manual coding

Value Message 2: Quality

Message: "Production-ready code with Clean Architecture, DDD, and observability built-in."

Supporting Points: - Clean Architecture patterns - Domain-Driven Design - Event-driven architecture - Observability by default

Value Message 3: Ownership

Message: "You own all generated code—no vendor lock-in."

Supporting Points: - Code committed to your Azure DevOps - Full source code ownership - No runtime dependencies - Standard .NET/Azure stack

Value Message 4: Consistency

Message: "Consistent architecture and patterns across all services."

Supporting Points: - Standardized templates - Consistent libraries - Uniform CI/CD pipelines - Predictable structure

Discovery Questions

Architecture Maturity

  1. How many microservices do you currently have?
  2. What patterns do you use for microservice architecture?
  3. How consistent are your services across the organization?
  4. Do you follow Clean Architecture or DDD principles?
  5. How do you handle service-to-service communication?

DevOps Maturity

  1. What CI/CD tools do you use?
  2. How long does it take to deploy a new service?
  3. Do you have standardized deployment pipelines?
  4. How do you manage infrastructure?
  5. What observability tools do you use?

Appetite for AI-Generated Code

  1. Have you used AI coding tools (GitHub Copilot, ChatGPT, etc.)?
  2. How comfortable is your team with AI-generated code?
  3. What concerns do you have about AI-generated code?
  4. How do you currently ensure code quality?
  5. What's your code review process?

Business Context

  1. What's your biggest pain point in building microservices?
  2. How long does it take to build a new microservice today?
  3. What's your team's capacity for new development?
  4. What's your budget for development tools and platforms?
  5. What's your timeline for next microservice?

Typical Objections and Responses

Objection 1: "We're not comfortable with AI-generated code"

Response: - Factory generates code following proven patterns (Clean Architecture, DDD) - All code is reviewed by your team before deployment - Factory acts as a senior architect and developer, not a replacement - You own all generated code and can modify it as needed

Objection 2: "We don't use Azure"

Response: - Factory is optimized for Azure, but generated code can run anywhere - Azure provides best integration and support - Consider Azure for new projects or hybrid approach - Factory can generate code for other clouds (with limitations)

Objection 3: "We prefer low-code/no-code solutions"

Response: - Factory generates real, production-ready code - No vendor lock-in—you own the code - Full control and customization - Better for complex business logic

Objection 4: "We have our own patterns and standards"

Response: - Factory can be customized to your patterns - Templates can be adapted to your standards - Factory ensures consistency across teams - Reduces deviation from standards

Objection 5: "It's too expensive"

Response: - Compare cost to hiring additional developers - Faster delivery means faster time-to-market - Reduced maintenance costs through consistency - ROI through faster feature delivery

Packaging and Next Steps

Packaging Options

  • Factory-Only - Factory access for code generation
  • Factory + Platforms - Factory + Identity/Audit/Config/Bot platforms
  • Factory + Squads - Factory + AI Squad team
  • Full Stack - Factory + Platforms + Squads

Next Steps

  1. Discovery Call - Understand customer needs and pain points
  2. Technical Assessment - Assess architecture and DevOps maturity
  3. Pilot Proposal - Propose pilot project (1-2 microservices)
  4. Pilot Execution - Execute pilot and demonstrate value
  5. Full Engagement - Expand to full Factory engagement

Tip

Sales Process: 1. Qualify - Use discovery questions to qualify 2. Demonstrate - Show Factory capabilities 3. Pilot - Start with small pilot project 4. Expand - Expand based on pilot success 5. Scale - Scale to full Factory usage