Insights
Everything we've published, newest first.
Prompt Testing — A Practical Guide for Production Systems
How to test prompts like production code — versioning, regression suites, scoring non-deterministic output, and the failure modes that only appear at scale.
AI for Business: What It Can Do, What It Can't, and How to Tell
A jargon-free guide for people deciding whether to spend money on AI — what the technology is actually good at, where it reliably fails, and the questions that separate a real opportunity from an expensive demo.
AI Agents: What Changes When Software Can Act
A practical guide to AI agents for people deciding whether to build one — what an agent actually is, where the value is, the failure modes that only appear once software can take actions, and how to keep one under control.
Software Architecture: Designing for the Changes You Cannot Predict
A guide to architectural decision-making — what actually counts as architecture, the trade-offs behind common patterns, when to split a system apart, and how to record decisions so they survive the people who made them.
AWS in Practice: What to Learn First and What the Bill Will Say
A practical orientation to Amazon Web Services — the handful of services that cover most needs, the cost mechanics that surprise people, and the account decisions that are painful to change later.
Azure in Practice: Where It Fits and What to Get Right Early
A practical orientation to Microsoft Azure — the services that cover most needs, why identity is the centre of gravity, licensing advantages that are real, and the decisions that are painful to change later.
Business Analysis: Turning a Vague Request Into Something Buildable
A practical guide to business analysis — how to find the real requirement behind a feature request, writing requirements that can be tested, the document types explained, and the traps that produce shelfware.
Cloud: What Gets Cheaper, What Gets More Expensive
A vendor-neutral guide to cloud computing — the economics that actually apply, which decisions to keep portable, when repatriation makes sense, and how to avoid the bill nobody predicted.
Cyber Security for Businesses That Aren't Banks
A practical security guide for organisations without a security team — the handful of controls that stop most real attacks, how attackers actually get in, what AI changes, and how to decide what is worth spending on.
Data Engineering: Getting the Numbers to the Decision, Correctly
A practical guide to moving data from where it is created to where decisions are made — pipeline design, the quality checks that catch real problems, and why two reports disagree.
DevOps: Shortening the Distance Between Merge and Live
A practical guide to DevOps — the four measures that actually indicate whether it is working, the practices that move them, and why buying tools rarely helps.
Docker: Packaging Software So It Runs the Same Everywhere
A practical guide to containers — what problem they actually solve, the handful of concepts that matter, how to build images that are small and secure, and the mistakes that cause production incidents.
Enterprise Architecture: Making the Whole Estate Coherent
A practical guide to enterprise architecture — what it is for, why most EA functions fail, the frameworks in plain terms, and how to run one that teams actually value.
FinTech: The Constraints That Make Financial Software Different
A practical guide to building financial technology — why money must never be a floating-point number, what idempotency really means when payments are involved, the regulatory shape of the field, and how fraud and risk systems actually work.
Kubernetes: What It Solves, and When You Don't Need It
An honest guide to Kubernetes — the problems it genuinely solves, the concepts that matter, what it costs to run, and the clear signs you should use something simpler.
Linux: The Practical Administration That Actually Matters
A working guide to Linux for people who run systems on it — the filesystem logic, permissions, services, diagnosing a slow or full server, and the security defaults worth setting on day one.
Machine Learning: When It Beats Simple Rules, and When It Doesn't
A practical guide to machine learning for business — what problems it genuinely suits, what it needs to work, how models fail in production, and why the baseline matters more than the algorithm.
MCP Explained: One Way to Connect AI to Your Systems
A clear introduction to the Model Context Protocol — the integration problem it solves, how it works, what it means for security and vendor lock-in, and whether you should adopt it yet.
Oracle: Performance, Licensing and Knowing When to Move
A practical guide to Oracle Database and applications — where it genuinely earns its cost, the licensing traps that produce audit bills, performance basics, and how to assess a migration honestly.
Project Management: Delivering Without Pretending You Knew Everything Upfront
A practical guide to running software projects — why estimates fail, what actually causes delay, choosing between predictive and adaptive approaches, and the small set of controls that genuinely help.
Prompt Engineering: Getting Reliable Output From a Language Model
A practical guide to prompting for business systems — the techniques that measurably work, why prompts belong in version control, and how to tell improvement from luck.
RAG Explained: How to Make AI Answer From Your Own Documents
A plain-language guide to Retrieval-Augmented Generation — what it is, why it beats fine-tuning for most business problems, how to build one that works, and the four reasons they usually fail.
Software Engineering: Writing Code Other People Can Change
A guide to the practices that keep software changeable — why readability beats cleverness, what code review is actually for, how to test without a test obsession, and how technical debt really accumulates.
Software Testing: Proving It Works Before Customers Find Out It Doesn't
A practical guide to testing — how to decide what deserves testing, the levels and what each is for, why coverage is a poor target, and how to test systems whose output is not deterministic.
How to Write a BRD That Actually Gets Used
A Business Requirements Document that survives contact with delivery — structure, the sections that matter, how it differs from an FRD and SRS, and the failure patterns that make BRDs shelfware.