For Enterprise Teams
What You Get from an IFD Engagement
An IFD engagement produces a governed intent corpus — a coherent body of documented architectural decisions, AI-consumable Skills, and the templates your team uses to extend both. The corpus is tangible, durable, and owned by your team after the engagement concludes. These are not slide decks — they are working assets embedded in your repository from day one.
A Living Documentation Corpus
Your codebase receives a Diataxis-structured documentation system: explanations capturing architectural reasoning, how-to guides for implementation patterns, reference materials defining API contracts and specifications, and tutorials providing onboarding paths. The documentation is designed to be maintained as the system evolves — not produced once and abandoned.
Structure ensures it remains navigable at scale. Diataxis prevents documentation rot by keeping different content types in predictable, separately maintained locations.
Design Decision Documents
Every significant architectural choice made during the engagement is recorded in a DDD: the scenario, options evaluated with trade-offs, the recommendation, and the actual decision with its driver. The separation between recommendation and decision preserves the analytical process — including cases where a business constraint overrode the technically preferred option.
When requirements change, DDDs tell you not only what was decided but why — so you can assess whether the original reasoning still holds.
AI-Consumable Skills
Your project receives practice-level Skills encoding the IFD methodology itself, and project-level Skills tailored to your specific technology stack, naming conventions, and architectural patterns. Skills are not documentation summaries — they are actionable constraints AI assistants consume directly during code generation. Skills ship in the Claude Agent SDK format by default, loaded by Claude Code in CLI and IDE contexts. When an engagement's toolchain requires it, equivalent Skill packages are authored for other AI assistants — for example, Cursor or GitHub Copilot.
AI-generated code reflects your team's deliberate choices rather than generic patterns, and that remains true across sessions, developers, and tool changes.
Templates and Methodology Transfer
The engagement includes everything your team needs to sustain IFD independently: DDD templates for recording future architectural decisions, documentation templates aligned with the Diataxis framework, Skill authoring guidance for creating new Skills as your project evolves, facilitation patterns for running altitude-gated design sessions, and a CLAUDE.md index file that orients any AI assistant to the full corpus on session start.
The goal is self-sufficiency. After the engagement concludes, your team has the tools and practices to continue capturing intent without ongoing external support.
Working Assets, Not Deliverables
These artifacts are embedded in your repository from day one. They are not delivered in a slide deck — they are operational.
Most consulting engagements produce a strategy document. IFD engagements produce a working documentation system, a set of active Skills, and a team that knows how to maintain both. The artifacts do not age on a shelf because they are used daily — by developers writing code, by AI agents consuming context, and by team leads reviewing architectural alignment.
Ready to build this into your team's practice?
Talk to XTIVIA →