Practical notes on automation, AI systems, internal apps and the decisions behind software that people actually use.
Selected articles
Useful ideas, tested in practice.
SEO
Why "keywords that describe my service" is the wrong starting point
Starting keyword research from your own service vocabulary only surfaces demand you already expected. A problem-first approach — Problem → Solution → Use case → Outcome — finds the searches that actually lead to the same project.
Running Your Own LLM Is Cheap in Dollars, Expensive in Time
We rented a GPU and self-hosted an open-weight model instead of calling a third-party API. Here's what actually broke, and what we'd tell anyone trying this.
How to Actually Compare Coding Models: What BridgeBench Measures That Older Benchmarks Don't
HumanEval and MBPP are saturated — frontier models clear 90%+ and the score stops telling you anything. BridgeBench evaluates across seven production-relevant categories instead of one isolated task type.
What Is Claude Fable 5.1? A Business Guide to Anthropic's New Flagship
Fable 5.1 is Anthropic's new flagship, released September 2026 — matching or beating Opus 5 on most benchmarks while using fewer tokens. What that means for a project you're planning.
The AI Automation Projects That Fail After the Demo — and Why
The demo always works. The failures we get called in to fix all happen after that, in the gap between a clean example and messy real usage. Three patterns show up over and over.
When a Custom App Beats a No-Code Stack (And When It Doesn't)
No-code tools win for the first three months. Then usage grows, and the same shortcuts that made you fast start making you slow. Here's how to tell which side of that line you're on.
Your Data Isn't Ready for AI — Here's the Five-Step Cleanup That Comes First
Most automation projects stall the first time they meet real records. The cleanup that unblocks them takes days, not quarters, you can run it yourself, and it pays back even if you never build the automation.
What an AI Pilot Should Cost — and the Three Numbers That Decide If It's Worth It
Real budget ranges for a first automation project, the two costs every budget forgets, and the three numbers you can work out yourself to know whether a project is worth doing at all.
What Google's Policy Actually Says About Scaled AI Content — and What the Data Shows
The spike-then-collapse pattern in AI content sites is real and documented. The viral case studies illustrating it usually are not. We separated the verified policy text and published datasets from the marketing anecdotes.
yt-dlp: The Boring Tool Behind Most Media Pipelines (And What It Costs You Legally)
A 184,000-star command-line downloader is the ingestion layer under most AI content workflows. What it actually does, why the licence is unusual, where it breaks, and the compliance questions to settle before it touches a client project.
What an AI Automation Agency Actually Does (And What to Ask Before You Hire One)
The category is two years old and already full of people selling the same three workflows at consulting prices. Here's what the work really involves, where it fails, and the questions that separate a partner from a demo.
Do You Need a Customer Portal? What It Costs, What It Saves, and When Not to Build One
A client portal removes the status-update loop between you and your customers. Here is how to work out whether it pays for itself, what belongs in version one, and the three reasons portals fail after launch.
What Is an AI Agent? A Business Definition — and Why 89% of Pilots Never Ship
A plain definition of an AI agent, the four levels of autonomy worth distinguishing, and an honest look at why most enterprise agent pilots die before production. Written for the person who has to approve the budget.
What Is an MCP Server? A Business Guide to the Model Context Protocol
An MCP server is the layer that lets an AI assistant reach your actual systems. What it contains, what it costs, where it goes wrong, and how to decide whether your company needs one — from a team running four of them.
Find the Ten Hours: A Process Audit You Can Run Without Us
The whole method we use to find where a company is losing time, written out so you can run it yourself on a Thursday afternoon. No tools to buy, no consultant required.
The n8n Workflow That Saves Our Clients 10 Hours a Week
One repeated pattern shows up again and again in client inquiries: information trapped in one tool, needed in three others. Here's the workflow we build to fix it.
AI Agents Are Ready for Your Internal Tools Sooner Than You Think
Computer-use AI agents can already operate real, undocumented internal software. That changes what "automatable" means for legacy tools and admin panels.