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Martin Fowler

The Archaeologist’s Copilot DSLs Enable Reliable Use of LLMs Fragments: July 13 Experiences with local models for coding Viability of local models for coding Fragments: July 6 Building Reliable Agentic AI Systems Fragments: June 16 Fragments: June 2 Fragments: May 27 The VibeSec Reckoning bliki: Vibe Coding Maintainability sensors for coding agents Fragments: May 14 bliki: Interrogatory LLM What Is Code? Fragments: May 5 bliki: Mythical Man Month Fragments: April 29 Structured-Prompt-Driven Development (SPDD) Fragments: April 21 Fragments: April 14 Alan Turing play in Cambridge MA Fragments: April 9 Feedback Flywheel Principles of Mechanical Sympathy Harness engineering for coding agent users Fragments: April 2 Encoding Team Standards bliki: Architecture Decision Record Fragments: March 19 Context Anchoring Fragments: March 16 Fragments: March 10 Ideological Resistance to Patents, Followed by Reluctant Pragmatism Ideological Resistance to Patents, Followed by Reluctant Pragmatism Humans and Agents in Software Engineering Loops Design-First Collaboration Fragments: February 25 Knowledge Priming Fragments: February 23 Fragments: February 19 bliki: Host Leadership Fragments: February 18 bliki: Agentic Email bliki: Future Of Software Development bliki: Excessive Bold My favorite musical discoveries of 2025
Fragments: March 26
Martin Fowler: 26 Mar 2026 · 2026-03-26 · via Martin Fowler

Anthropic carried a study, done by getting its model to interview some 80,000 users to understand their opinions about AI, what they hope from it, and what they fear. Two things stood out to me.

It’s easy to assume there are AI optimists and AI pessimists, divided into separate camps. But what we actually found were people organized around what they value—financial security, learning, human connection— watching advancing AI capabilities while managing both hope and fear at once.

That makes sense, if asked whether I’m a an AI booster or an AI doomer, I answer “yes”. I am both fascinated by its impact on my profession, expectant of the benefits it will bring to our world, and worried by the harms that will come from it. Powerful technologies rarely yield simple consequences.

The other thing that struck me was that, despite most people mixing the two, there was an overall variance between optimism and pessimism with AI by geography. In general, the less developed the country, the more optimism about AI.

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Julias Shaw describes how to fix a gap in many people’s use of specs to drive LLMs:

Here’s what I keep seeing: the specification-driven development (SDD) conversation has exploded. The internet is overflowing with people saying you should write a spec before prompting. Describe the behavior you want. Define the constraints. Give the agent guardrails. Good advice. I often follow it myself.

But almost nobody takes the next step. Encoding those specifications into automated tests that actually enforce the contract.

And the strange part is, most developers outside the extreme programming crowd don’t realize they need to. They genuinely believe the spec document is the safety net. It isn’t. The spec document is the blueprint. The safety net is the test suite that catches the moment your code drifts away from it.

As well as explaining why it’s important to have such a test suite, he provides an astute five-step checklist to turn spec documents into executable tests.

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Lawfare has a long article on potential problems countering covert action by Iran. It’s a long article, and I confess I only skip-read it. It begins by outlining a bunch of plots hatched in the last few years. Then it says:

If these examples seem repetitive, it’s because they are. Iran has proved itself relentless in its efforts to carry out attacks on U.S. soil—and the U.S., for its part, has demonstrated that it is capable of countering those efforts. The above examples show how robustly the U.S. national security apparatus was able to respond, largely through the FBI and the Justice Department….

That is, potentially, until now. The current administration has decimated the national security elements of both agencies through firings and forced resignations. People with decades of experience in building interagency and critical source relationships around the world, handling high-pressure, complicated investigations straddling classified and unclassified spaces, and acting in time to prevent violence and preserve evidence have been pushed out the door. Those who remain not only have to stretch to make up for the personnel deficit but also are being pulled away by White House priorities not tied to the increasing threat of an Iranian response.

The article goes into detail about these cuts, and the threats that may exploit the resulting gaps.

It’s the nature of national security people to highlight potential threats and call for more resources and power. But it’s also the nature of enemies to find weak spots and look to cause havoc. I wonder what we’ll think should we read this article again in a few years time