Building with Claude since April 2026 · Claude Corps Fellowship

I fell for AI in a chemistry lab. I make systems run more efficiently.

I'm Vanessa — a PhD chemist who taught myself to build with Claude. I can't look at a process without wondering how to make it more efficient — the ideas start flowing and I have to build them. Apps families use, a free Google Slides add-on anyone can grab (more to come!), tools for industry and research, and an operating system that makes Claude govern, verify and improve itself.

Explore the work → See the system I built

Projects shipped

Live & testable

Automation hooks I built

Operating-system modules

PhD, Green Chemistry · Ogden, Utah · 🇬🇧 🇪🇸 🇫🇷 trilingual+

About me

From the lab bench to shipping software

I spent years as a chemist — a PhD in Green Chemistry, published in mass spectrometry, building machine-learning classification models for cannabis samples long before "AI" was a headline. Some of it was in QC labs under GMP/GLP/FDA rules, where I learnt auditing, traceability and validation fast — the exact discipline my Claude system runs on today. I've also been a teacher and tutor to students all over the world.

Then I started building with AI — and eventually with Claude in particular — and I couldn't stop. With zero formal programming background, I taught myself to scope, ship and improve real products: apps my family actually uses, free tools lots of people can pick up — like a Google Slides add-on I built for my own projects — and the system that runs underneath it all, in only a few months, since April 2026.

What I care about is useful, honest work that helps people — which is why most of what I build is free. More than any single field, I'm drawn to making processes better and as efficient as possible. My interests run wide: science, research and industry, education, tools for families, accessibility. Right now, while I homeschool my daughter until she's old enough for public school, learning and family tools are simply where I'm focused — far from the limit of what I want to build.

🎓 Free online teaching 🧑‍🏫 Tools for teachers & homeschoolers ❤️ Charity work 🤍 HG patient peer support 🆓 Accessible resources

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Built with Claude

Things I scoped, shipped & keep improving

Every one of these is a real, working project — most you can open and test right now. My interest runs well beyond teaching, into industry and research too; right now there are more learning tools here simply because that's where my days go, homeschooling my toddler. They're honest first versions: all of them have pending tasks, because the work is ongoing.

projects shipped

Portfolio at a glance

15 built with Claude8 earlier, other tools9 live & testablemost of it free

The centerpiece

COS — the Claude Operating System I built

It isn't an app you can open — it's infrastructure. A system of rules, automatic checks and self-audits I engineered so Claude works like a careful, senior teammate: it plans, verifies, logs and improves itself every session — while I stay in the loop, watching, verifying, evaluating, correcting course and making the final call.

🎯

Your request

comes in plain language

✍️

Auto-rewrite

prompt-engineered internally

📚

Playbook loads

right rules, on demand

🔨

Build

with guardrails

🔍

Verify

render + measure, prove it

🔄

Log & retro

never forgets, self-improves

Knowledge modules

Runtime safety hooks

Scheduled automations

Self-audits / month

interactive

Click any step above to see how my system handles it →

Six stages run on every request — from a plain-language ask to a logged, self-improving result.

Self-taught

A system I built — and still supervise

This system is self-taught. Drawing on the discipline I built in regulated QC labs — auditing, traceability and validation — I put together my own Claude operating system, then kept refining it with ideas from the wider community. Anthropic's AI Fluency and Claude 101 courses gave precise names to habits I'd been forming on my own — and opened my eyes to how much further this can go. I'm well aware this system has plenty of room to grow. What excites me about this opportunity: to keep learning from the people who do it best, to put everything I learn into practice for a good cause, and to teach these skills to others.

The architecture, wired — the real graph

These 21 governing files reference each other — one-way (→) and two-way (↔). CLAUDE.md routes, but INDEX.md, REGISTRY.md and the playbooks cross-link too. Node size = how much is written in each file. Hover or tap any node to see its real connections.

21 files62 cross-references~23k words of contextINDEX.md = most connected (20)

← scroll the map sideways to explore · tap any node for its connections

Every edge is a real reference I can point to in the files — this is the map I use to keep the system a closed circuit (nothing orphaned). Through all of it, I stay in the loop: review, verify, decide.

Use it→Automate it→Govern it→Auto process-improvement·human input:ReviewFeedbackDecide

🧪 Lab auditing→my system's twice-monthly self-audits

🗂️ Lab traceability→a master index where nothing gets lost

✅ Validation before release→my verify-and-render-before-ship gate

That instinct came from regulated-lab work — picked up fast — and from teaching myself the rest.

⚙️ Automation

Hooks & scheduled audits run themselves — no reminders needed.

🤝 Augmentation

Claude and I build as thinking partners, every session.

🧭 Agency

The COS lets Claude act, verify and self-correct on my behalf.

🧠 Built ADHD-first — which makes it better for everyone

⛔ Perfectionism-loop guard→flags when I'm polishing past the point of real value

📦 Shippability score→tells me the moment a product is good enough to ship

✅ Ship first, refine later→further polish becomes a choice, never a blocker

I designed these guards around how an ADHD brain actually works — but they help anyone: best-quality output, shipped on time, without the hours lost to changes nobody needed.

🎯

Delegation

deciding whether, when & how to engage AI

"Setting goals and deciding whether, when and how to engage with AI." — AI Fluency

On-demand playbook router

The system loads only the rules a task needs, so Claude engages with the right context instead of everything at once.

Mechanism decision guideSELF-BUILT

A rulebook for choosing the right tool for each job — a skill, an agent, a hook or an automation — not just "ask the chatbot".

Cross-tool handoff briefSELF-BUILT

When my free Claude usage ran out, a guardrail let me delegate to a free model (e.g. z.ai) for debugging without it breaking my rules.

Acts autonomouslySELF-BUILT

It deploys and runs multi-step tasks end-to-end on its own — with a safety guard that forces a private GitHub backup before anything goes live.

Offload to free-running scriptsSELF-BUILT

Whenever possible, work runs as standalone scripts and automations that execute outside the AI's usage — saving cost and stretching every credit further.

✍️

Description

describing goals to get useful behavior

"Effectively describing goals to prompt useful AI behaviors and outputs." — AI Fluency

Auto prompt-engineering hookSELF-BUILT

A dedicated skill turns my everyday, conversational requests into structured, engineered prompts (who / what / context / format) before Claude acts — and when something is vague, it switches to interview mode, asking a couple of clarifying questions first so the brief is right from the start.

Standing rules + power-phrase library

A reusable description system — plain-language conventions, locked decisions — so I never re-explain the same things.

🔍

Discernment

judging whether the output is actually good

"Accurately assessing the usefulness of AI outputs and behaviors." — AI Fluency

Self-preview: render + measureSELF-BUILT

When Claude builds UI, it previews and measures its own work across screen sizes before showing me — so I don't test every little change. Fewer back-and-forths, fewer tokens, better results.

Facts, never assumptionsSELF-BUILT

It double-checks the real sources before speaking — our own files, live documentation for current info, whether a tool/connection is actually available — instead of guessing.

Adversarial critic + a 9-expert boardSELF-BUILT

An internal red-team and multi-perspective panel — each advisor grounded in real methods — review work before it ships.

🛡️

Diligence

taking responsibility for the outcome

"Taking responsibility for what we do with AI and how we do it." — AI Fluency

5 automatic safety hooksSELF-BUILT

Deploy-guard, log-keeper and an auto-retrospective that — at high context — saves my work, then nudges me to free up room. Diligence I can't forget.

A system that improves itselfSELF-BUILT

After each session it scans our conversation for friction and spots new skills, hooks or fixes worth building — then scheduled audits keep everything current, including a weekly agent that revisits every project's saved knowledge and refreshes anything that's gone out of date. Everything is registered, recoverable, and remembered across sessions.

Built-in review mode for human feedbackSELF-BUILT

Every site I build ships with a one-click review mode (this site has it too): I click anywhere to pin a note, then export the whole list for Claude to action — precise human feedback, no guesswork. It's now a standing rule for every website and page my system makes.

Some custom skills I engineered into my system

A few of the reusable skills I built so Claude works the way I need — ordered by how much they shaped this work.

improve-system ★

The self-improvement loop: after each session it scans our work for friction and turns recurring problems into permanent upgrades — the skill that makes the system improve itself.

process-optimization

Reviews the workflow I actually used in a session and finds what to streamline next time — so the way I work keeps getting faster and cleaner, not just the tools.

science-claim-verifier

My scientist's reflex, automated: it checks every health or science claim against peer-reviewed literature before a product ships — and I built it with its own evaluation tests.

ask-the-board

Convenes a panel of advisor personas — each grounded in a real methodology — to pressure-test strategic decisions from several angles before I commit.

I built this operating system on my own. Anthropic's courses put names to concepts I was already using.
I made Claude plan, verify and improve its own work, with me supervising every step.

None of it runs unsupervised. I stay in the loop on every build — reviewing the work, correcting it, and stopping to re-steer the direction when needed. The system does the heavy lifting; the judgement stays human.

Where I started

Early projects, other AI tools

Before the system existed, I was already building. These came first — made with other AI tools — and they're exactly why the COS exists now: as I revisit each one, I'm rebuilding it better, the right way.

Honest note: most of these were debugged with other tools — like z.ai — when my usage limits on the AI I was using at the time ran out. Building on a budget is part of the story, and stretching free tools is a skill of its own.

Credentials

Certified & always keen to learn

A few of my most recent certifications. During my years in industry at Cytiva and Teva I earned many more — GMP, quality and lab-systems training among them.

🎓

AI Fluency: Framework & Foundations

Anthropic · passed 10/10 ✦

⚡

Claude 101

Anthropic · passed 10/10 ✦

🧑‍🏫

Teaching skills

Teaching-strategies courses during the PhD

🛡️

Safeguarding (Prevent Duty)

UK Government

Let's talk

I'd love to build with the Claude Corps

What pulls me most is purpose. I've chosen most of my roles — including my last, in the QC lab of a medicines manufacturing plant at Teva — because the work reached every patient who needed those drugs to heal or manage their symptoms. That's the thread in everything I build: I want to put my skills to work for the right people, doing the right things — which is why a non-profit or mission-driven team is exactly where I want to be. If that resonates, I'd love to talk.

Email me → Connect on LinkedIn ↗