Claude Code, Copilot, Codex and Cursor accelerate delivery — but without domain context and architectural guardrails they ship technical debt at the same speed. Premium Faber helps backend-heavy teams (fintech, SaaS, ERP) adopt AI coding agents without losing control of their architecture.
A focused offer built for teams already shipping with AI coding agents — or about to.
We analyse your repository, current AI tooling and PR process. You get an AI readiness assessment, a map of architectural risks, a recommended AGENTS.md / CLAUDE.md, an initial ARCHITECTURE.md, a Mermaid context map, review checklists and a governance proposal.
Hands-on sessions for your engineering team: how to delegate tasks to AI coding agents, how to review their output, how to write context packs, and how to use bounded contexts as natural boundaries for agent work.
Supporting capabilities
DDD bounded contexts and Mermaid diagrams turned into machine-readable context for your agents.
Guardrails, ADR templates and review workflows so AI-generated code stays inside your architecture.
Senior backend modeling for fintech, SaaS and ERP — the foundation agents need to behave well.
Every engagement ships a concrete, version-controlled context pack — the practical artifact that lets AI coding agents work inside your architecture instead of around it.
A short, structured map of the repo agents can actually use — not a 1,000-page manual.
High-level architecture, conventions and key decisions, written for both humans and agents.
DDD as a practical tool to define boundaries, responsibilities and a shared vocabulary.
Diagrams-as-code so context is versioned, reviewed and consumable by LLMs.
Lightweight decision records and machine-checkable rules agents are expected to respect.
Concrete contracts for delegating work to an agent and reviewing what comes back.
We come from backend engineering and software architecture, not from the prompt-influencer side of AI. That's why our work focuses on what actually breaks: domain boundaries, review quality, hidden coupling, and the long-term cost of code that ships without context.
Four focused phases — designed to deliver value within weeks while building durable foundations for agentic engineering.
Review repo, PR process and current usage of AI coding agents.
Surface bounded contexts, draw a context map, identify architectural risks.
Ship the context pack: AGENTS.md, ARCHITECTURE.md, ADRs, review checklist.
Workshop the team on the new workflow and follow up on real PRs.
The recurring situations where architecture control around AI coding agents pays for itself.
Agents break domain boundaries in your monorepo
Copilot PRs are fast — but review takes longer than before
No AGENTS.md / CLAUDE.md / Cursor rules for your repo
Legacy backend where agents lose context fast
Fintech or regulated domain — guardrails and audit trail required
Onboarding a team onto AI coding agents
No metrics for the quality of AI-generated PRs
Moving from ad-hoc 'vibe coding' to a controlled workflow
Premium Faber Limited helps engineering teams adopt AI coding agents — Claude Code, Copilot, Codex, Cursor — without losing control of their architecture, domain or code quality. We work with backend-heavy organisations in fintech, SaaS and complex B2B platforms, where architectural decisions compound and the cost of getting them wrong with AI is the highest.
Tell us a bit about your goals or current challenges. We'll get back to you within one business day.
marek@premiumfaber.co.uk