Martin Alderson

I used to be a TDD sceptic - too much time writing tests for features that might get deleted. Then coding agents completely changed the economics of software testing.

Permission systems, Docker sandboxing, and log file secrets - why current approaches to securing coding agents fall short and what we might need instead.

Why DRAM shortages, not capital, will define AI infrastructure growth through 2027

Comparing token efficiency across 19 popular programming languages using RosettaCode data - from Clojure to C, there's a 2.6x difference.

Using Claude Code to port 120k lines of Pascal and 68k assembly to modern C# - and what this means for cross-platform development

MCP tools eat thousands of tokens. A simple CLI with instructions in your CLAUDE.md file uses 71 tokens and works brilliantly.

Travel agents are the classic example of an industry killed by the internet. Software engineering is facing the same disruption, but the timeline is compressed.

Critics are judging models trained on last-gen hardware. There's a 6x wave of compute already allocated - and it's just starting to produce results.

Using ASTs and AI agents to reverse engineer minified JavaScript in minutes instead of weeks

Software ate the world. Agents are going to eat SaaS.

Agentic coding tools are dramatically reducing software development costs. Here's why 2026 is going to catch a lot of people off guard.

Gemini 3 Pro's design capabilities and Opus 4.5's reduced babysitting needs represent a subtle but significant leap that traditional benchmarks completely miss.

Using IPv6 with Cloudflare to run multiple services on a single server without a reverse proxy

A practical approach to managing production infrastructure using git-tracked markdown files and Claude Code for small teams

Software engineers underestimate the scale of Excel usage. With agents now able to work directly in spreadsheets, we're looking at transforming how billions of dollars in business processes are managed.

Looking at actual token demand growth, infrastructure utilization, and capacity constraints - the economics don't match the 2000s playbook like people assume

A non-technical CFO built a production operations dashboard with Claude Code that had failed with low-code tools and agencies. This shift in who can build software is going to change everything.

I built a tracker to monitor the growth of MCP servers in the wild - turns out the ecosystem is growing faster than I expected

Insights from MCP Dev Summit Europe on agentic discovery, client compatibility challenges, and the emerging field of agentic experience design

Why GitHub Actions runners are slow and how bare metal servers can make your CI/CD 2-10x faster while costing 10x less

Google's Gemini AI Studio API has been suffering from severe reliability issues with little transparency about the problems on their status page.

From magical to frustrating in months. Why AI coding agents feel like dial-up internet and what ultra-fast inference could unlock for developer productivity.

How to give AI coding assistants complete visibility into APIs and third-party libraries using static analysis instead of basic text search.

Deconstructing the real costs of running AI inference at scale. My napkin math suggests the economics might be far more profitable than commonly claimed.

Testing Claude Code beyond software engineering - using it as a tax agent to analyze documents and navigate complex tax scenarios in real-time.

Testing Model Context Protocol support across OpenAI, Anthropic, and others. The reality of cross-platform MCP implementation in 2025.

Starting a blog about AI-assisted development, MCP integrations, and building production software with modern tooling like Claude Code and Cursor.