Executable Domain Grounding for Your AI-Accelerated SDLC

I deliver a single, highly opinionated service for software development organizations operating in B2B SaaS and regulated industries: The Domain-Grounded AIDLC Sprint.

Instead of open-ended advisory retainers or generic prompt engineering, I deliver a fixed-scope, 2-week architectural intervention. I establish the deterministic domain vocabulary required to safely govern your internal AI coding tools (like Cursor, Claude Code, GitHub Copilot, or SpecKit). This shifts your architecture from post-generation testing to pre-generation deterministic constraint—eliminating "rogue domain logic" and massively reducing PR review bottlenecks.

My focus is exclusively on software engineering leadership (CPTOs & VPs of Engineering) at mid-market and enterprise B2B SaaS and regulated industries who are scaling AI-accelerated software development across their organization.

The core bottleneck: Your product squads are leveraging AI coding agents without centralized domain boundaries. These agents are confident but statistically probabilistic—they invent parallel business rules, unauthorized state transitions, and unapproved data models. This instantly compounds technical debt and shifts a massive cognitive load onto your senior engineers during code review.

This sprint does not replace your internal harness; it deterministically grounds it in your actual domain knowledge.

Most internal AI harnesses rely on post-generation testing or spreading business rules across dozens of disparate system prompts and context files. As you scale across multiple squads, managing that "prompt drift" becomes an impossible maintenance burden.

The Domain-Grounded AIDLC Sprint introduces an executable single source of truth. By centralizing your domain rules into a formal, machine-readable domain model, you create a strict baseline. We wire this directly into your workflow and harness with AI skills, tools and hooks that intercept AI hallucinations at the specification level. It complements your existing setup, making it exponentially more manageable, scalable, and deterministic.

It doesn't just integrate with SDD; it mathematically grounds it.

SDD is a massive leap forward because it captures developer intent before generating code. However, if your specifications are written purely in ambiguous natural language, your platform is still exposed to domain drift. AI agents can and will misinterpret natural language specs to invent rogue domain logic.

The Domain-Grounded AIDLC Sprint wires a machine-readable domain model directly into your SDD framework (e.g., GitHub SpecKit). When your developers or agents write specifications, the local linters intercept and validate them against your core business rules. If a specification violates your domain boundaries, it fails immediately, stopping the hallucination during the specification phase, before a single line of code is ever drafted.

Absolutely not. Attempting to map an entire enterprise architecture is a multi-year trap that usually dies in committee. I do not boil the ocean.

Instead, I apply the Bounded Context principle from Domain-Driven Design (DDD). We do not map the universe; we isolate a single, high-risk or high-value feature or platform slice where AI hallucinations are currently clogging your pull requests.

During the sprint, we extract 8 to 12 core operational rules for that specific boundary. We let the LLMs guess the generic boilerplate and standard CRUD functions. But for the critical state transitions, constraints and semantics, the 20% of your domain logic that carries 80% of the risk, we lock those down in the Executable domain model baseline. It is about protecting your highest-liability workflows, not modeling the whole system.

Agencies sell "Labor" (billable hours); I deliver "Systems" (Executable IP).

• ✅ No "Junior" Hand-offs: You work directly with a Ph.D. in Computer Science with 15+ years of experience in enterprise systems architecture, Model-Driven Engineering, and domain-specific languages.
• ✅ Architectural Insurance: I don't give you a slide deck of theories. I provide the deterministic, machine-readable ground truth (the domain model baseline) and the automated execution hooks that physically prevent domain drift from fracturing your platform.
• ✅ Air-Gapped & Zero-Access: Because I deliver self-contained configuration packages and drop-in Integration Runbooks, I do not need access to your live CI/CD pipelines or sensitive source code. This entirely air-gapped approach bypasses the 3-to-6 month Enterprise Procurement and InfoSec nightmare typical of agency engagements.

To ensure rapid value delivery and bypass bloated consulting overhead, the engagement follows a strict 4-step Delivery Mechanic over two weeks:

1. Targeted Domain Extraction: Applying Domain-Driven Design, we isolate a single, high-value Bounded Context and extract just the 8 to 12 core business rules into a formal domain model baseline.
2. Domain Model Compilation & Harness Engineering: I compile the core schema and configure the customized AI asset package, using the domain model as an executable single source of truth for your agentic workflows.
3. Air-Gapped Delivery: The compiled domain model baseline, execution hooks, and local linters are delivered as self-contained, machine-readable artifacts.
4. Handover & Implementation Alignment: Alongside a live handover, I deliver a definitive Zero-Friction Integration Runbook, a set of step-by-step instructions to wire the air-gapped grounding into your local workflows within minutes.

I deliver Deterministic Validation against Domain Drift:

• Optimized DORA Metrics: By eliminating the rework cycles caused by hallucinated business logic, this executable domain baseline directly accelerates your Lead Time for Changes and minimizes your Change Failure Rate.
• Pre-Flight Domain Interceptors: Unauthorized data structures or conflicting business rules trigger immediate, deterministic compilation and linting failures during local specification evaluation. Your AI agents are forced to self-correct before any code is committed.
• Optimized Unit Economics & Latency: Coding models no longer waste massive context windows trying to deduce application logic. This drastically reduces your token burn per agentic loop and safely routes execution to highly efficient models.
• Independent Architectural Authority: Alongside the harness, I deliver the Architectural Evolution Runbook. Built on robust Model-Driven Engineering principles, your senior engineers receive the exact workflow required to independently update, recompile, and extend the domain model as your platform scales.

The argument is Senior Engineering ROI and Technical Debt Mitigation:

1. The Senior Engineer Tax (ROI): Every hour a senior engineer spends debugging AI-hallucinated business logic in a Pull Request is an hour stolen from shipping high-value roadmap features.
2. The Runtime Risk (Mitigation): AI-generated code often looks structurally perfect while being semantically wrong. If a subtle, AI-generated business logic error slips past manual review and reaches production, the implications—corrupted core logic, cross-tenant leaks, or broken compliance—are catastrophic.

You are making a discrete, one-time Operational Velocity Investment to systematically prevent unauthorized domain logic from ever reaching code review.

I use a transparent, fixed-fee model to eliminate procurement friction.

• The Domain-Grounded AIDLC Sprint: €19,500 (Excl. VAT).
• Billing Schedule: 50% billed upon mutual execution of the Statement of Work (SOW) to secure your sprint dates on the calendar. The remaining 50% is billed upon final delivery of the Integration Runbook.
• Operational Assumptions: Maintaining the fixed-scope 2-week delivery timeline requires a maximum 48-hour turnaround on intermediate schema reviews from your team. Any review cycles exceeding this 48-hour SLA automatically extend the final sprint delivery date by an equal duration to protect the integrity of the architecture.

There are no hidden overages or ongoing software subscription fees. You retain 100% ownership of the localized deliverables.