Library.

The clearest statement that continuity across sessions is an architecture problem, not a prompt problem.

Pull over push for agent context: give the agent less and let it retrieve, with files as the universal primitive.

Files quietly won as the central abstraction for agent memory, retrieval, and skills, displacing heavier machinery.

When behaviour emerges from code plus model, traces replace source files as the debugging surface.

The 80/20 flip in weeks, and the observation that model failure is now conceptual rather than syntactic: hasty-junior mistakes, not syntax errors.

The line worth keeping between what you delegate to a model and what you must still hold yourself.

What development looks like once the bottleneck is inference time rather than code: parallel projects, output streams monitored rather than read.

My take: The Trust Spectrum

AI work compounds only when artefacts, decisions, and corrections persist as context for future sessions; the essay behind a lot of how this site’s author works.

Local-first sync as a worked example of an architecture bet paying off in feel, not just benchmarks.

High-altitude binaries create the appearance of strategy while keeping the room away from the hard customer-specific question.

A job is a bundle of problems someone wants solved, not an object on a board; the best career reframe of the year.

Personal software as software shaped by one person’s judgment rather than a market’s average need.

The disciplined counterweight to AI maximalism: constrain the tool to the box where it demonstrably helps.

AGI defined pragmatically as the ability to figure things out, with the three ingredients already shipped.

Organisational integration beats raw model power; institutional capability is the differentiator, not model choice.

Complex tasks see larger AI speedups than simple ones, inverting the usual displacement narrative.

Benchmarks measure a model operating inside a frame humans supplied; as framed competence gets cheap, the human work moves to problem-definition, review, and exceptions.

My take: After Automation, Judgment Becomes Infrastructure

A scenario, not a forecast: what happens if AI succeeds and the economy’s redeployment loop breaks anyway.

The organisational thesis: repeated work rebuilt as governed feedback loops, with humans kept at the high-stakes edges.

A first-person field report of company-wide agent adoption; the numbers are self-reported and unaudited, but the shape of the operating model is worth reading anyway.