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Signal Shingle: a novel architecture for high-performance ASP.NET multi-widget sites

Part of the Stylo.Bot release series. Behaviour-Aware ASP.NET UI covers the server-rendered dashboard surface; Finding and Fixing Unbounded Growth covers the reliability discipline behind bounded state; Learning to Get Faster covers the earlier adaptive-cache…

StyloBot Release Series: StyloExtract - a local learning HTML to Markdown converter

StyloBot v8 lets a site give AI crawlers a controlled Markdown view of its pages at its own local edge, without ceding the gateway to a CDN. This piece is about the extractor that does the conversion (StyloExtract): the walker bug lucidVIEW caught, and the…

StyloBot Release Series: Behaviour-Aware ASP.NET UI

Bot detection should not stop at allow/block. This post shows how StyloBot's classification result becomes application logic in ASP.NET: tag helpers in Razor, action filters and policies in controllers, signal-level gating, so your UI can shape the experience…

StyloBot Release Series: Behaviour-Aware TypeScript UI

Bot detection should not stop at allow/block. This post shows how StyloBot's classification result becomes application logic in TypeScript: server middleware for Express and Fastify, template helpers for Handlebars, Nunjucks, and EJS, and browser web…

StyloBot Release Series: Testing the Thing That Won't Sit Still

How do you test a detector whose answer is supposed to change as it learns? This post is about BDF, the Behavioural Definition Format that makes StyloBot testable: one file defines a class of traffic, then drives regression replay, load generation, and a…

StyloBot Release Series: The Sidecar Architecture

StyloBot's detection engine is ASP.NET Core. This post explains how that engine connects to Go gateways, Node.js applications, and any other stack via a gRPC sidecar, a typed Go SDK, and a Caddy plugin, without any of those consumers needing to know anything…

StyloBot Release Series: Finding and Fixing Unbounded Growth in Long-Running .NET Services

Long-running services tend to slowly drift toward unbounded memory. Here's how I find that drift, how I think about fixing it without papering over it, and a worked example from StyloBot's vector similarity layer that took it from 13 GB on the Large Object…

StyloBot Release Series: Learning to Get Faster

Heads up: this one is for the nerds. It's a deep technical dive into StyloBot's adaptive learning system (EWMA updates, hysteresis thresholds, verdict caching, variance watchdogs), with real code from Mostlylucid.BotDetection and pointers to the equivalent…

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