Myles MellorCommercial, digital & marketing operator

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.

LevelsAwarenessUnderstandingAppliedProficientExpert

Building with AI

The hands-on AI engineering — built, not read about.

  • Prompt engineering

    Proficient

    30 custom skills, each with its own prompt scaffolding; a shared voice guide and intake-brief pattern across them.

  • AI APIs & models

    Proficient

    Two RAG implementations shipped end-to-end across two providers (Anthropic + OpenAI) — embeddings, vector store, hybrid retrieval, cost tracking.

  • Data pipelines

    Proficient

    Two distinct production pipelines — directory enrichment and document/email ingestion — sharing a reusable verification stage.

  • Evaluation & testing

    Proficient

    Two AI-system eval harnesses with measured baselines, on top of 25 years of marketing measurement discipline.

  • Agent architecture

    Applied · advancing

    An 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

    Proficient

    30 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

    Applied

    Built RAG from scratch — chunking trade-offs, similarity metrics, metadata schema. The maths of attention/embeddings stays surface-level (honest, non-developer).

  • AI security & safety

    Proficient

    Code-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

    Proficient

    A full governance operating system in daily use; an enterprise CRM transformation across hundreds of users; reusable measurement frameworks.

  • Web development

    Proficient

    20 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

    Proficient

    Launched 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

    Proficient

    CI/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

    Proficient

    A 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 · advancing

    First 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

    Applied

    A 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

    Applied

    Authored 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 · advancing

    A 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.