What's the hard marketing / data / website problem you can't solve?
Richard Baxter, marketing engineer.
From complex site migrations and replatforming to data collection, price monitoring and app builds. I'm a Senior Consultant who builds, delivers and upskills your in-house team.
What I do
Site migrations & replatforming
Five legacy domains folded into one Shopify Plus trade store, wired to SAP Business One, without losing the search equity.
The case study →Application & platform builds
An AI-ready jobs board platform with its own API and MCP support, and the custom apps that do what the platform can't.
The case study →Data collection & price monitoring
Competitor prices and product data collected overnight, served as a dashboard the commercial team checks each morning.
The case study →Technical SEO, audits & scoping
Twenty years of technical SEO, now run through an audit console I built and use on my own sites every day.
The case study →Content marketing & automation
Research, drafting and fact-checking at production scale, ready for your editor before publish.
The case study →AI training & team enablement
I work with your people until the penny drops and they're building their own small connectors and MCPs to speed up the whole team.
Work with me →What I've built lately.
Content that keeps itself current
Publishing pages that carry numbers - prices, benchmarks, "updated for 2026" posts - and dreading the refresh backlog? I built a statistics site where every figure recomputes from its source, and a Claude routine reads the prose against the data each morning. The patterns transfer to any site.
How it works →
The parts Shopify Plus B2B doesn't do
Running trade pricing through an ERP and wondering whether Shopify Plus can hold it - the negotiated specials, the volume breaks, the carton rules? I moved the price lists across natively and built the one piece the platform can't do, so every customer sees the price their rep agreed.
Read the case study →
Eight content ideas, from the model you choose
Type a topic or paste your URL, then pick which model does the thinking - Llama, Qwen, DeepSeek and a few more, most of them free - and get eight commissioning-editor pitches: safe bets, bold swings and contrarian takes, each scored for freshness.
Read the comparison →
The world's first AI-ready job board and data platform
Jobs pulled from 19 ATS platforms, AI-enriched on the edge, and served four ways from one store - web page, XML, JSON and live agent tools.
The case study →
Shopify Plus - Industrial B2B commerce, wired to SAP B1
Five legacy brand sites folded into one Shopify Plus trade store, priced live from SAP - and organic search up 35% year on year.
The case study →
Retail competitor price monitoring
Five competitors' prices across a 1,250-product portfolio, checked overnight instead of by hand.
The case study →
Compliance monitoring software for FCA-regulated networks
Three hours of manual checking per broker site, down to minutes - with the evidence attached to every decision.
The case study →
Technical SEO audits, inside Claude
Search Console and a full crawl of your site, merged into one ranked audit you can talk to.
The case study →
Retail price and product data collection, with n8n
Product catalogues from 20+ suppliers, re-scraped, enriched and served to publishers daily.
The case study →
Private AI on my own hardware
The volume work moved onto my own GPUs, and sensitive data never leaves the building.
The case study →
Content automation with a system behind it
Research, drafting and fact-checking at production scale, ready for your editor before publish.
The case study →Which side of this do you want to be on?
Do you want to ignore the fact that AI is present, or shall we learn to execute with it in a way that is safe, reliable, and enhances your team's abilities? This type of thing is already happening at your competitors. The moat, if you like, is for you to see what's possible, take that away, and think about what can be done with it to improve the speed at which your business operates.
Tools I publish, free.
Open-source MCP servers that solve specific problems marketers and digital people face, built because I needed them and run on my own sites every day. Install them into the AI assistant your team already uses.
Gemini MCP
Grounded search, image analysis, diagrams and video from inside Claude, with my Gemini MCP.
SEO Audit
The complete technical SEO audit at conversation speed. Search Console and a first-party crawl merged, findings ranked by expected clicks per developer-hour.
FMP MCP
Company fundamentals, statements and ratios from inside an agent. Built for finance and investor-research workflows.
Writing.
What is a Marketing Engineer (and do you need one)?
In today's post we're taking a closer look at the marketing engineer, the role Greg Isenberg reckons becomes tech's next big hire. The title may or may not stick, but the job is certainly real: I've been running the systems it describes for a year. Here's what it involves, what to build first, and what the sceptics get right.
Dynamically updating infographics and content (so you don't have to)
I built a statistics site where every number updates itself. The harder half turned out to be the prose - so a Claude routine now reads the site against its data every morning. Here's how the whole thing works, and the patterns you can take for your own site.
The parts Shopify Plus B2B doesn't do (and how we built them)
Shopify Plus does more B2B than most people think - right up until a customer sits on two catalogues and their negotiated volume pricing disappears. I put an industrial hardware distributor's ERP pricing live on it, with one first-party app and nothing extra to host. Here's what native covers, and what I had to build.
vLLM settings for a pair of RTX 4090s: the flags I run for twelve local models, and why
The flag-by-flag vLLM settings page for a dual-4090 rig: the baseline every preset shares, the six flags that change per model, the rig discipline you set once, and one verified launch block for each of twelve open-weight models with the reason attached.
The 26%: what the companies actually making money from AI do differently
Google Cloud surveyed 2,403 executives and found a 26% cohort whose AI returns are accelerating year on year - and BCG independently landed on the same number. Meanwhile MIT says 95% of pilots die. Both are true, and the difference between the two groups is where they aim the technology, not how much they spend on it.
Which AI model pitches the best content ideas?
Content Marketing Ideas lets you choose which AI does the thinking. I ran the same brief through all eight models: how the pitches differ, which are worth the wait, and why the free ones are slow.
The VRAM traps: why a 16GB model wouldn't load on a 48GB card
A 16GB model would not load on my 48GB card, and the reason was a shortfall of one kilobyte in a memory no spec sheet mentions. These are the fit traps a VRAM figure will never warn you about.
The Dual-4090 96GB vLLM Benchmark & Runbook
Can a £6,200 modified Ada rig match enterprise MoE throughput? The living measurement record for a dual RTX 4090 48GB vLLM rig - every number measured here.
What is the hard problem you can't solve for a reasonable budget?
We've come out of a world where you needed to invest in quite specific SaaS tools to do things that were fundamental to the operation of your business. This new world lets us build that intellectual property into the core of your company.