The art of simplicity

  I think that everyone who uses AI recognizes the following pattern; you ask an LLM a simple question and it answers like it's writing a blog post: introduction, context, three examples, a closing summary. Fine for a first read, expensive when you're chaining calls or running an agent loop all day. The trick to avoid this is called "caveman prompting". You tell the model to drop articles, pleasantries and filler, and answer in short, blunt fragments. It sounds silly. But it works up to a point. A first attempt: just say "be concise" Most people's first instinct is a one-line system prompt: Be concise. No fluff. This already gets you a good chunk of the savings. In benchmarks I've seen floating around, a plain "be concise, return structured output" instruction accounts can already give you a nice reduction. It's the cheapest fix and most people stop here, which is reasonable. The caveman approach The caveman skill takes...

While investigating some performance issues, we ran into an ASP.NET Core API that cached a fairly expensive aggregation query for 60 seconds. Under normal load, that was fine: one request rebuilds the cache, everyone else reads from it. Under peak load, dozens of requests would arrive in that same expiry window, all see a cache miss, and all fire the same expensive query in parallel. The database didn't like that. That was the moment when our caching layer stopped helping and started hurting. A burst of requests comes in at the same time, all miss the cache, and all go hammer the database or the downstream API at once. That's a cache stampede . The cache was supposed to protect our backend, and for a few hundred milliseconds it did the opposite. Why this happens IMemoryCache.GetOrCreate (and its async sibling) looks like it protects you, but it doesn't add any locking on its own. Look at the naive version: public async Task<Report> GetReportAsync(string key) ...

A few years ago, I worked as an architect on a big mainframe rewrite. I still count it as one of my failures. Not because the technology was wrong, but because I couldn't convince the management team to simplify the approach. Years later, the organization is still struggling to get the new system up and running. I left the project at the time, because I couldn't put my name behind an approach that would take very long and cost a lot of money without a working system to show for it along the way. Gall’s Law That memory keeps coming back to me, because it's a textbook case of Gall's Law playing out in real life. Gall's Law , from John Gall's Systemantics , states it plainly: A complex system that works is invariably found to have evolved from a simple system that worked. A complex system designed from scratch never works, and it cannot be patched to make it work. You have to start over with a simple system that works. What does that mean in practice,...

There's a moment when you clone or pull a repository on Windows and Git throws an error like this: error: unable to create file some/very/deeply/nested/path/to/a/file.ts: Filename too long Nothing wrong with your code, nothing wrong with the repo. It's Windows. Why does this happen? Windows has a default path length limitation of 260 characters (the infamous MAX_PATH ). Git operations that create files with a full path longer than that — cloning, checking out, pulling — will fail with this error. Repositories with deeply nested folder structures (think node_modules, or generated code) hit this constantly. The fix: enable long paths in Git Git has a config setting for exactly this: core.longpaths . You have two ways to set it, depending on your rights on the machine. System-wide (requires Administrator privileges): git config --system core.longpaths true User-level (no Administrator required): git config --global core.longpaths true If y...

Recently I was wiring up a YARP reverse proxy in front of a couple of Aspire-managed services: an API and an Angular frontend. Aspire gives you service discovery for free, so the obvious move is to point your YARP clusters at the logical service names instead of hardcoded URLs. My first attempt looked like this: "Clusters": { "api-cluster": { "Destinations": { "api-destination": { "Address": "https+http://api" } } }, "frontend-cluster": { "Destinations": { "frontend-destination": { "Address": "https+http://angular-frontend" } } } } The https+http:// scheme is the standard Aspire service discovery convention: try HTTPS first, fall back to HTTP. It works fine when you're resolving endpoints through HttpClient . Unfortunately YARP doesn’t like this configuration. After setting it up with these values ...

While doing some pair programming to integrate OpenTelemetry tracing to a .NET application, we had a discussion on how to use the ActivitySource . It looks simple. You new one up, give it a name, start an activity, done. The discussion started when we added a second ActivitySource with the exact same name in a different class. This made us wonder: "Are we duplicating traces now? Is this a memory leak? Do we need a singleton?" So we decided to dig deeper. This post is what we learned… What ActivitySource actually is ActivitySource is part of System.Diagnostics , not part of the OpenTelemetry NuGet packages. Microsoft built tracing primitives directly into the BCL, and OpenTelemetry's .NET SDK simply listens to them. This is why you can add distributed tracing to a library without taking a dependency on OpenTelemetry at all. An ActivitySource is a factory for Activity objects, and an Activity is .NET's name for what OpenTelemetry calls a span.(don’t ask m...