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Implementing a JA4H-Equivalent Fingerprint with Amazon CloudFront Functions to Mitigate Bot Traffic

JA3 and JA4 fingerprints have been showing up more and more often in discussions about bot mitigation and client identification. Amazon CloudFront exposes TLS-based JA4 as a CloudFront-generated header, but it does not provide the HTTP-request-based JA4H fingerprint. That made me wonder: “Why not implement it ourselves with CloudFront Functions?” So I did. There are a few gotchas and design considerations you need to be aware of, and I’ll cover those as well. In this article, I’ll first demonstr

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ExternalSoftware Engineering
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Check any website's AI readiness from your toolbar

Shipped a small Chrome extension: click the icon on any site and get its AI Readiness Score out of 100, its tier, and what an AI agent can and cannot do on it. Free, private, one click. Part of the open AI2Web project. https://chromewebstore.google.com/detail/ai2web-ai-readiness-check/dgfgbjlpmhahoafdcfandobbncfjhlle

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ExternalSoftware Engineering
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The zero-egress trick that lets me give away a media tool for free

I run a small free tool called imgi. You drop in two images, drag a slider to compare them, and get a permanent link to paste anywhere. Before and after shots, mostly: a photo edit against the untouched shot, a game mod next to vanilla, an AI upscale against the source file. Here's what nobody warns you about when you build one of these. The hard part isn't the slider. It's the bandwidth bill. Every viewer who opens a comparison pulls down two full-resolution images. One link that catches on, a

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Why Federal Reform Picks AI‑Native Outcome Integrators

Executive summary Federal procurement is shifting from labor-based buys toward fixed-price, outcome-focused contracts—and that change alters who wins work. This article summarizes the third piece in a six-part Orange Slices series arguing that AI-native Outcome Integrators are structurally advantaged by recent acquisition reform, prototype-driven RFIs, and managed-service delivery enabled by Zero Trust and cloud-native architecture. Read the original article. Recent executive direction and the

aidatascienceleadership
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ExternalSoftware Engineering
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We Audited an E-Commerce Support Bot, Fixed the Bugs, Then Re-Tested It. The Score Jumped 86 to 91.

Most chatbot audits stop at "here's what's broken." We wanted to know if the suggested fixes actually work — so we applied them and re-tested. Here's the before-and-after, with transcript evidence. We ran an e-commerce customer support bot through BotCritic — order tracking, returns, refunds, sizing, general product questions — against 4 customer personas: Curious, Frustrated, Confused, and Technical. First run: 86/100 — Grade B. Solid, but with specific, fixable gaps. We applied BotCritic's sug

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