Different problems, same method: find what's actually driving the cost, then build the thing that fixes it. Not everything here was a paid engagement, and every entry says which it was.
Scoping a build normally happens in a document nobody reads and a proposal that hides its assumptions. By the time a disagreement about scope surfaces, someone is already building the wrong thing.
A living specification the client logs into. The scope is a navigable tree of programs and modules, each carrying its requirements, open questions, documents, and the flows connecting it to everything else. Password and two-factor login, and every engagement runs on its own physically separate instance and database.
Clients watch the scope take shape instead of receiving a proposal, and open questions are visible to both sides while they are still cheap to answer. This is the instrument I scope with. It isn't a product for sale.
Growth depended entirely on existing relationships. The owner knew the market segments but had no system to find prospects, qualify them, track them, or hand them off to sales. Business development was a person's memory, not an operation.
A custom CRM built around how their sales motion actually works, with pipeline intelligence feeding it: prospect discovery, enrichment, company research, dashboard, and analytics, segmented by the company's actual service lines. Delivered as a working system, not a report.
Their new sales hire received a research-grade pipeline on day one. Instead of cold-starting from scratch, they had qualified prospects with context and a plan for reaching them. Business development became a repeatable operation instead of a founder dependency.
A custom social app for a pet-services business, designed and built end to end rather than adapted from a template.
Phase one, deployed and working.
It was never adopted, and the work stopped there. It's on this page because the build was real, not because it became a business.
Rough-order estimates for utility installs come out of judgment and a spreadsheet. Months later, when the number is questioned, nobody can reconstruct how it was reached or which assumptions moved it.
An estimating engine where the rules live in configuration files a client can read, and the engine itself is deterministic code: intake, takeoff, pricing, then a rough-order range. The AI is fenced to one job, reading documents to pre-fill the intake form, and it never prices anything. Every output carries a stamp recording exactly which rules produced the number.
Built and demonstrated live in July 2026. It's a demonstration of method rather than a client system, and its design is the diagram on the Ownership and Continuity page.