How We Engage

An IFD engagement is structured to deliver immediate value while building your team's capacity to sustain the practice independently. The engagement follows four phases, each building on the previous.

Phase 1: Discovery

We begin by understanding your current state — not just your technology stack, but how your team works with it.

Discovery covers:

• Architecture review — How is your system organized? Where are the boundaries, integration points, and areas of complexity?
• Development workflow assessment — How does your team plan, build, review, and deploy? Where do AI tools fit in the current workflow?
• Pain point identification — Where does architectural knowledge get lost? Where does AI-generated code create friction? Where does onboarding take too long?
• Collaborative design sessions — We conduct initial altitude-gated design sessions on a representative piece of your system, demonstrating the IFD approach and surfacing intent that may not be captured anywhere today.

Discovery typically takes one to two weeks depending on the complexity of the systems involved.

Phase 2: Methodology Adoption

With discovery complete, we establish the IFD foundation in your development environment.

This phase produces:

• A Diataxis-structured documentation directory integrated into your repository, with initial explanations and reference materials for your key systems
• Design Decision Documents for the architectural choices surfaced during discovery — creating an immediate governance baseline
• A CLAUDE.md entry point that orients AI tools to your full documentation corpus
• Practice-level Skills configured for your team's IFD practice

Methodology adoption focuses on your most critical systems first. The goal is a working IFD practice on a meaningful slice of your architecture — not a comprehensive documentation project that delays value delivery.

Phase 3: Skill Development

With the methodology foundation in place, we develop the project-level Skills that make IFD operational for your specific codebase.

Skill development involves:

• Convention extraction — Identifying the patterns, naming conventions, component structures, and architectural rules your team follows (or should follow)
• Skill authoring — Encoding those conventions as Skills that AI tools can consume during implementation
• Validation — Testing Skills against real implementation tasks to verify they produce code that aligns with your team's intent
• Iteration — Refining Skills based on implementation results, adding edge cases, and adjusting constraints

This phase is inherently collaborative. Your senior developers and architects work alongside XTIVIA to ensure Skills reflect your team's actual practices and standards, not generic best practices.

Phase 4: Enablement

The final phase transfers ownership of the IFD practice to your team.

Enablement includes:

• Design session facilitation training — Your team members learn to conduct altitude-gated design sessions independently, including when to ascend (return to a higher abstraction level) and how to produce documentation artifacts from design conversations
• Skill authoring training — Your team learns to create, update, and maintain Skills as your project evolves and conventions change
• DDD authoring practice — Team members practice writing Design Decision Documents for real architectural decisions, with feedback on structure and completeness
• Sustainability review — We assess whether the IFD practice is self-sustaining, identify any gaps, and provide recommendations for continued maturation

After enablement, your team has the methodology, the artifacts, and the skills to maintain and extend the IFD practice without ongoing external support.

Ready to explore how IFD can work for your team? Get started with a conversation.