A craft-by-craft guide to building financial services software with AI — from product intake through handoff, implementation, and QA. Structure your work once and watch it cascade through every tool in the pipeline.
Each craft section is a self-contained module. Start at Product if you're building something new. Jump into Design, Handoff, or Development if you're picking up mid-process.
Six phases from UX discovery through validation reporting, with AI agents, human gates, and traceability baked in at every step.
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A well-structured requirement cascades through your entire AI toolchain. The 15 minutes you spend structuring it up front saves hours of rework when AI tools need to guess at intent.
These apply at every craft. The tools are capable — the quality of your input is the constraint.
Your tools are powerful — Claude, Copilot, Figma Make. The gap isn't capability, it's the quality of what you feed them. Structure once, consume everywhere.
Requirements don't get structured until migration into Helix near the end of development — by that point, AI tools can't help. Capture structure at the point of the stakeholder call.
Name the user, the moment, the data. "A Loan Officer reviewing 6 commercial loan applications with overdue credit decisions" gets a better screen than "a monitoring dashboard" every time.
Stakeholders give vague feedback on Lorem Ipsum. They give specific, actionable feedback on LOAN-0042 — Credit Risk Flag, 38 days pending, Chicago Branch Office.
If a requirement describes a quality ("user-friendly") without observable behavior, AI can't generate code from it. Describe what happens — what loads, validates, submits.
AI tools generating tests rely entirely on what you've written. No edge cases in your acceptance criteria means no edge case tests — the gap becomes a compliance risk in SOC 2 Type II and PCI-DSS contexts.