Capability
What I can do — and how I know
A living map of capability across seventeen AI areas. Every level is grounded in real, shipped workspace evidence — not self-assessment. I've deliberately left out percentile claims (“top X%”): they're directional at best, and over-claiming would undercut the point. Where something is still developing, or a genuine gap, it says so. The honest version is the credible one.
Building with AI
The hands-on AI engineering — built, not read about.
Prompt engineering
Proficient30 custom skills, each with its own prompt scaffolding; a shared voice guide and intake-brief pattern across them.
AI APIs & models
ProficientTwo RAG implementations shipped end-to-end across two providers (Anthropic + OpenAI) — embeddings, vector store, hybrid retrieval, cost tracking.
Data pipelines
ProficientTwo distinct production pipelines — directory enrichment and document/email ingestion — sharing a reusable verification stage.
Evaluation & testing
ProficientTwo AI-system eval harnesses with measured baselines, on top of 25 years of marketing measurement discipline.
Agent architecture
Applied · advancingAn autonomous diagnostic chain with file-based handoffs; read-only MCP integrations; two hand-wired API integrations. SDK-driven orchestration is the next step.
Human-AI interaction design
Proficient30 skills with deliberate conversational UX, progressive disclosure and surfaced uncertainty, now codified as authored agent-UX design principles and proven by redesigning a skill against them.
AI concepts & theory
AppliedBuilt RAG from scratch — chunking trade-offs, similarity metrics, metadata schema. The maths of attention/embeddings stays surface-level (honest, non-developer).
AI security & safety
ProficientCode-enforced local-only data governance and read-only credential scoping, plus a prompt-injection red-team across six external-input skills with documented defences. Honest gap: those defences are instruction-level, not yet structurally enforced (agent sandboxing and audit logging still to build).
Systems, product & web
The operator and builder craft the AI work sits inside.
Systems design
ProficientA full governance operating system in daily use; an enterprise CRM transformation across hundreds of users; reusable measurement frameworks.
Web development
Proficient20 years of websites; a live Next.js directory; a daily-use finance app. The modern typed-React stack is newer than the two-decade web foundation (honest).
Product thinking
ProficientLaunched a 16-unit complex at 22% net profit; a startup proposition to £1.2m in 18 months; scope decisions made and documented, not drifted into.
DevOps & infrastructure
ProficientCI/CD live across four repositories with auto-deploy on push, plus Vercel deployments and 20 years of domain/DNS/hosting. Honest caveat retained: no infrastructure-as-code or formal monitoring yet.
Creative & content AI
ProficientA reusable, themeable engine that renders on-brand explainer videos (authored HTML → headless render → MP4), now spanning two brands; plus generative-model work — an AI-built artist concept (Suno music + AI imagery). Honest caveat: the video path is code-rendered, not model-generated, and the generative work is one concept, not yet a standing operation.
Commercial & strategy
Where the 25-year career meets the AI work.
Commercial AI application
Applied · advancingFirst external consultancy deliverable shipped; 30 skills in daily use. Honest note: the repeatable consultancy pipeline past one client is still to be built.
Marketing & growth automation
AppliedA 25-year marketing career at scale (HSBC £50m+, Santander). The AI-automation layer specifically is still developing — the level reflects that, not the career depth.
AI ethics, policy & regulation
AppliedAuthored an IP & compliance position for the consultancy (what it does and doesn't do, client-owns-deliverables, UK-GDPR data discipline already practiced). Honest note: positional and applied, not a formal audited programme.
The honest gap
Shown deliberately — restraint is part of the credibility.
AI strategy (enterprise)
Understanding · advancingA strong enterprise commercial and transformation track record; the AI-specific enterprise overlay is pilot-stage, not yet org-scale (honest).
Maintained as a living record — levels move as the evidence does, in either direction.