I'm Liam. Six years writing copy that had to convert or get killed. Three years building the systems that scale that work to a $20M+ portfolio.
Every system on this site was built inside Claude Code. Frontends, backends, agents, skills, MCP integrations. One runtime, one builder, real receipts.
9 systems. Three continents. One builder.
Production platforms, internal tools, open-source templates, and the meta-tooling that ships them. Each one built on Claude Code. Tap any row to open the build.
The boring, expensive busywork, automated.
A growing library of real automations I built and ran in n8n (a tool for wiring apps together). Each one takes a painful, repetitive job a team does by hand and turns it into a system that runs on its own, using the tools a business already pays for. Filter by team, and open any one to see exactly how it works.
Every workflow runs on the same backbone, and the guardrail is in all of them: a confidence check with a human fallback, so nothing risky ever happens unattended.
Lead response and qualification
“Leads sit for hours before anyone replies. The hot ones go cold.”
A lead fills in the website form. In one second, AI reads it, decides how hot it is, and either texts them back instantly or starts a nurture email, then saves them to the CRM and pings the sales team. No lead ever waits.
Support triage assistant
“The support inbox overflows with the same questions, and replies are slow.”
Every incoming message gets sorted by topic and urgency, then AI drafts a reply using only your help-centre articles. If it's confident and simple, it sends and closes the ticket. If not, it hands the draft to a human to approve first, so nothing risky goes out alone.
Community moderation
“Your community needs watching around the clock for spam and rule-breakers.”
Every new post is checked against your community rules. Clean posts pass instantly; anything borderline (spam, self-promo, abuse) gets sent to a human with the reason attached. The bot flags, it never bans on its own, and every decision is logged.
Customer research engine
“Teams write copy and make decisions on gut feel instead of what customers actually say.”
Type in one brand, and it listens to what real customers are saying about it in nine different places: Reddit, Amazon reviews, TikTok, competitor Facebook ads, and more. Then it checks it gathered enough, and notes exactly where every quote came from, all before anyone writes a single word.
New-customer onboarding cascade
“A sale closes and six teams scramble to do their bit by hand.”
The moment a sale is marked “won,” six teams spring into action at the same time: the invoice goes out, onboarding tasks are created, the customer's account is set up, welcome emails start, and leadership gets a heads-up, all without anyone lifting a finger.
HR handbook assistant
“New hires flood HR with questions already answered in the handbook.”
A new hire asks a question in Slack. The bot looks it up in the employee handbook, answers only from what it actually found (and links the page), and if it isn't sure, it quietly hands the question to a real person. It never makes anything up.
Overdue invoice chaser
“Someone chases unpaid invoices by hand every single week.”
Every morning it pulls your overdue invoices, picks the right tone for each based on how late it is (a gentle nudge, a firm reminder, or a final notice), sends them all, and flags the worst offenders to a human. The money gets chased while you sleep.
Receipt bookkeeping
“Receipts pile up and get typed into the books one by one.”
A receipt lands in the inbox. AI reads the photo or PDF (vendor, amount, category), checks it isn't a duplicate and fits policy, then posts it straight to the books. Anything odd gets flagged to a human. The shoebox of receipts disappears.
Meeting notes to tasks
“Meeting decisions get made, then never turn into tracked tasks.”
When a meeting ends, AI reads the transcript, pulls out every action item with its owner and due date, creates the tasks, messages each person their part, and posts a clean recap. Nothing said in the room gets forgotten.
Content repurposing
“One blog post should become ten pieces of content, but never does.”
Publish a blog post and it instantly becomes a LinkedIn post, an X thread, a newsletter blurb, an Instagram caption and a short-video script, all in your brand voice, then gets scheduled and saved to your content calendar. One piece of work, a week of content.
Pre-call prep briefs
“Reps walk into calls cold, with no idea who they're talking to.”
Thirty minutes before a meeting, it looks up who you're talking to (their role, their company, recent news), pulls your past history with them from the CRM, and writes a one-page brief with talking points and smart questions. You walk in knowing exactly what to say.
Employee offboarding
“Someone leaves and nobody's sure every account actually got shut off.”
On an employee's last day, it revokes every login at once (email, Slack, single sign-on across all apps), reassigns their open tasks, stops payroll, then posts a confirmed audit checklist to IT and the manager. No forgotten account left open.
Daily KPI brief
“Nobody knows the real numbers without half a day of stitching spreadsheets.”
At 7am it pulls yesterday's sales, ad spend, website traffic and pipeline from four different tools, compares them to the day before, and writes a plain-English brief (revenue, ROAS, what changed, what to watch), then posts it to leadership. No more half-day of stitching.
Built, wired and tested end-to-end on my own n8n. The plain-English names are what you see; the real APIs and models sit one layer down in each step. More being added.
What the systems actually produce.
Real static ads my systems generated, each routed through a different expert framework and composed around the brand's real product. Tap any one to enlarge.
Generated by my creative systems, not hand-designed. Every product is composed around the brand's real packaging, accurate to the SKU.
Real numbers from production systems.
Every number below ties to a system I shipped. No vanity metrics, no rounding tricks.
From copy to code, across three continents.
Six years of direct response craft. Three years of production AI systems. The line between writing and shipping got thinner every year.
DR copywriter → Head of AI Copy
Started here. Daily emails, push notifications, UX writing, and ad copy for a crypto gaming platform with 1.5M+ players. Grew from daily direct response into Senior Copywriter, then Head of AI Copy, building Claude Code agents for the Affiliate and VIP teams. Five years of copy that had to convert or get killed.
AI Copywriter → Head of AI Copy
Joined as the first AI-focused copywriter across the Foxelli portfolio, with Hooks & Needles and Mindful Souls as my primary brands. Six months in I was running Claude in production, not as a drafting tool but as the actual output. Promoted to lead a 5-person copy team through the AI transition, then to take AI across the whole company.
Head of AI Automation/Strategy
Owned AI strategy across 7 DTC brands and a $20M+ combined portfolio. Built Foxelli Studio, an end-to-end AI ad production platform. Built copy agents deployed company-wide and research systems that turned customer surveys into AI-ready brand context. Architected for 100 concurrent users.
Founder
Custom AI marketing systems for DTC and CPG brands at $10M–$100M. Five-layer architecture: Context, Data, Intelligence, Agents, Commands. The team stays in the chair. Every output gets reviewed. The system gets smarter with every correction.
Five principles that decide what gets built and what doesn't.
Claude Code is the build environment, not the assistant.
Every system in this portfolio shipped through Claude Code. Frontends, backends, agents, skills, MCP integrations, CLIs. One runtime. Most people use AI to write code. I use it to ship systems.
Humans where it counts. Autonomous everywhere else.
Anything that touches a customer gets a human's approval, and brand voice and creative instinct stay human. Back-office systems run fully autonomous, no approval loop. The real skill is knowing which is which.
Every system gets a learning loop.
If it can't get smarter from the work, I haven't finished building it. Editor feedback, customer corrections, failed campaigns. All of it feeds back into the next pass.
Build the meta-tool.
Don't write a script when you can write the skill that writes the script. Don't write the skill when you can write the agent that picks the right skill. The leverage compounds.
Run AI economically.
All media generation routed through Kie.ai at ~60% under retail. Token discipline upstream: prompt caching, tight context windows, reuse over re-fetching. Cost-engineering an AI stack is engineering. I do both halves.
The runtime, the surfaces, and what's wired in.
Most portfolios list AI alongside React. Mine doesn't. AI is the layer everything else runs through.
The runtime, the surfaces, and what's wired in. Most portfolios list AI alongside React. Mine doesn't. AI is the layer everything runs through.
Runtime
- ▎Claude Code (primary)
- ▎Claude Agent SDK
- ▎60+ custom skills authored
- ▎Custom hooks + settings.json automation
Surfaces
- ▎VS Code (daily driver)
- ▎Google Antigravity
- ▎Terminal CLI
MCP servers wired
- ▎Supabase
- ▎n8n
- ▎Notion
- ▎GitHub
- ▎Firecrawl
- ▎Figma
- ▎Stitch
CLIs addressable
- ▎Codex
- ▎Gemini
- ▎NotebookLM
Verified by the people who built the tools.
Anthropic certifications, English fluency, and the receipts behind the work. The certs come from the lab whose tools I build on every day.
Let's build something that compounds.
Open to senior AI engineering, AI strategy, and advisory roles. Remote · US & EU only. Available now.