Architecture

I have spent the last eighteen months either building, reviewing, or operating systems that some marketing department somewhere has called “agents”. The definition has been so thoroughly stretched that it now means anything from a chatbot with a calculator tool to a long-running autonomous workflow that touches production infrastructure. Underneath the noise there is a real engineering discipline emerging, and the patterns that separate the systems that survive contact with real users from the ones that demo well and fall over are starting to be legible. ...

The question I get asked most often by engineers starting to build with language models is some variation of: “should we fine-tune or should we do RAG?” It is almost always the wrong question, but it is the wrong question in an instructive way. The reason it gets asked so much is that the choice feels architectural, and architectural choices feel like the kind of thing you commit to once and live with. In practice, the choice is closer to “should I use a database or a cache” - the answer is usually some of both, applied to different problems, and the ratio shifts as the system matures. ...

This is a “thinking out loud” post, not a report from the front lines. I have no evidence any of this is happening at scale, and it is not how my current day job looks. These are just ideas I keep turning over, and I wanted to write them down to see if they hold together. The question I keep coming back to is simple. If AI agents continue to improve at the rate they seem to be, what does engineering work look like five or ten years from now? Not tomorrow. Not next quarter. Further out, where the shape of the job might actually be different. ...

Platform engineering used to be the title on a few job adverts at Spotify and Netflix. In 2026 it is the default shape of any infrastructure team larger than a dozen people. The shift is worth understanding, because it is not just a rebrand of DevOps - it is a different operating model, with different tools, different incentives, and a different relationship to the developers it serves. This post is a plain-language walk through what platform engineering actually is, why the industry has converged on it, and how the arrival of AI agents is reshaping the discipline mid-flight. ...

What the Amiga Got Right (That We’re Still Copying) The Commodore Amiga was not the most successful computer. It was not the fastest. It was not the cheapest. It was introduced in 1985, bought by Commodore in a panic, and discontinued by 1994 as the company collapsed. By most commercial metrics, it was a failure. Yet almost every good idea in modern computing traces back to the Amiga. Preemptive multitasking. Graphics layers and compositing. Named pipes. Memory protection. Hardware acceleration. Plug-and-play peripherals. Scripting languages. Digital audio and video editing. Networking. The Amiga did these things in 1985 when IBM PCs were still running in 8-bit mode. ...

The views in this post are my own personal reflections on the industry, written in my own time. They are not about any specific employer, team, or colleague, past or present, and do not draw on any non-public information. “Best practice” is a phrase that should be treated with suspicion. What works for a fintech running 500 engineers rarely works for a five-person startup. The notes below are generic patterns drawn from public talks, books, and industry write-ups - always weighed against context, team size, and what the system is actually trying to do. ...

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