The Domain-Grounded AIDLC Methodology

Targeted Domain Extraction: Isolating the Bounded Context

Principle: "Map the Business Reality, Not the Database."

Rather than attempting to boil the ocean by modeling your entire platform, we isolate a single, high-value domain slice to establish an immediate, localized ground truth.

• Interactive Domain Extraction: I conduct a highly-focused, interactive remote session with your cross-functional engineering and product leads.
• Resolving Domain Ambiguity: We extract and formalize the core rules, state transitions, and business logic around your use case, deliberately resolving semantic conflicts and aligning on a unified vocabulary.
• The Bounded Context: We document explicit domain boundaries, core entities, and permitted behaviors, establishing a strict, targeted baseline that isolates pure business knowledge from messy application-layer infrastructure.

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Harness Engineering: Compiling the Executable Domain Model

Principle: "Domain Rules Must Be Machine-Enforceable."

Once the core concepts are extracted, I translate them into an executable ground truth for your coding agents.

• The Executable Domain Model Baseline: I write and compile a formal, machine-readable domain model (as a Domain-Specific Language (DSL)) defining your operational entities, permitted state changes, and strict business rules.
• The AI Harness Package: I engineer a customized asset package (integrating natively with environments like Cursor, Claude Code, or GitHub Copilot). I deliver drop-in configuration files (e.g., repository-level .cursorrules or Claude prompt configurations) that natively anchor your existing AI tools in the domain model.
• Executable Single Source of Truth: The centralized domain model acts as the authoritative reference point, ensuring developers and AI agents operate within identical, unambiguous boundaries.

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Air-Gapped Delivery: Zero-access integration

Principle: "Maximum Governance, Minimum Friction."

Enterprise security shouldn't bottleneck architectural velocity. This engagement is designed to completely bypass traditional vendor risk assessments.

• Zero-Access Architecture: I do not require access to your live CI/CD pipelines, internal networks, or sensitive source code.
• Self-Contained Artifacts: The compiled domain model baseline, execution hooks, skills and tools for your harness are delivered entirely as self-contained, machine-readable artifacts. Not as fluffy documentation or abstract guidelines.
• Drop-In Extension: The deliverables act as a localized, drop-in extension for your existing AI-accelerated workflows, allowing your team to activate the guardrails instantly without introducing external dependencies or exposing proprietary IP.
• Capability Transfer: I provide comprehensive knowledge transfer sessions to ensure your engineering team fully understands the domain model, the harness configuration, and the integration process, enabling them to independently maintain and extend the system without external assistance.

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Capability Transfer: Handover via the Integration Runbook.

Principle: "Empower the Developers, Constrain the AI."

We take the deterministic foundation and wire it quietly into your developers' day-to-day workflow.

• The Zero-Friction Integration Runbook: Alongside a live handover deep-dive, I deliver definitive, step-by-step IDE instructions your engineers need to wire the air-gapped constraints into their local Copilots within minutes.
• Local Pre-Flight Interceptors: We activate the hooks, tools and skills built directly for your environment. When an agent attempts a plan or code block that contradicts your domain rules, the harness automatically intercepts execution and forces a self-correction before a human ever reviews the PR.
• The Architectural Evolution Runbook: A static baseline is a dead baseline. Instead of relying on probabilistic AI to manage its own rules, I deliver a definitive maintenance runbook for your senior engineers. Built on Model-Driven Engineering principles, your team retains 100% independent authority to update, recompile, and extend the domain model baseline as your platform scales.