Building a Custom CRM with AI-Assisted Development
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the gist
Brian Casel demonstrates a systematic approach to building internal business tools by using AI to transform high-level requirements into a structured, milestone-based development plan, bypassing the bloat of off-the-shelf SaaS.
The Philosophy of Internal Tooling
Most business software is designed for mass-market appeal, resulting in bloated interfaces that bury essential features. The most effective way to manage internal workflows is to build custom, lean applications that do exactly what is required and nothing more. By treating software development as a learnable skill rather than a black box, business owners can leverage AI to build tools that fit their specific operational needs without the overhead of enterprise-grade complexity.
Shaping the Product Requirements Document (PRD)
The process begins with a high-level idea, which is then refined into a formal PRD using an AI-assisted workflow. This involves defining the core features, explicitly listing what is not being built to prevent "AI slop," and establishing a data model. For internal tools, the strategy shifts from building flexible, multi-tenant systems to hard-coding specific business logic, which drastically reduces UI complexity and development time.
Milestone-Driven Execution
Once the PRD is established, the project is broken down into buildable, dependency-aware milestones. Each milestone is treated as a discrete unit of work. The developer uses a "plan mode" to generate a technical implementation plan before moving to execution. This layered approach ensures that the AI agent understands both the business intent and the technical requirements, leading to more predictable outcomes.
Maintaining Context and Continuity
To ensure consistency across milestones, the AI is instructed to generate a "milestone log" at the end of each phase. This document serves as a handover, passing critical technical decisions and state information to the next iteration. This practice allows the developer to clear the context window between milestones without losing the thread of the project, enabling a modular, iterative development rhythm.
Testing and Verification
After each milestone, the developer performs a manual review of the output against the milestone log. Because the initial planning phase is so rigorous, the actual coding phase is largely automated. The focus shifts from writing code to verifying that the application behaves as expected, using a consistent design system to ensure the UI remains functional and clean throughout the build process.