Cloudflare - Tag - Shengxu · Cloud Architecture & DevOps

Hands-On: From AI Semantic Search to AI Content Pipeline – How Static Blogs Continuously Evolve (Continued)

Sat, 06 Jun 2026 10:30:00 +0800

A few months ago, I wrote an article titled “Hands-on: Building Fully Automated AI Semantic Search with Cloudflare Vectorize and Gemini”. The problem it solved was clear: enabling semantic search for a static blog and capturing user queries that failed to find results as Content Gaps.

Once that architecture was running, I quickly realized: Search is just the last mile of the content lifecycle.

From the moment a Markdown article is written to when it’s actually discovered by readers, it must pass through summaries, translations, related recommendations, internal links, image optimization, search indexing, SEO, deployment, and quality checks. If these steps still rely on manual processing, even the smartest AI search is just a new entry point bolted onto a traditional publishing workflow.

Practical Guide · Building a Memory-Powered AI Writing Partner (Part 1): Multi-Agent Architecture Evolution

Sun, 25 Jan 2026 10:00:00 +0800

When writing a long novel, the most painful part isn’t “not being able to write”—it’s “forgetting what you’ve already written.” Did I set up that foreshadowing properly? Was that character already injured in the last chapter? When exactly was that world-building rule established? Once your manuscript crosses the hundreds-of-thousands-of-words mark, relying solely on your brain and scattered notes quickly becomes unmanageable.

FantasyNovelAgent grew out of this exact need. It started as a simple Python script, then evolved to include dynamic memory and auto-archiving, later added multi-device sync, and is now taking its first steps toward a front-end/back-end separation with cloud-native storage. This article retraces that evolution path and explains the key trade-offs, offering a reference for similar projects.

Hands-On: Building an Automated AI Semantic Search with Cloudflare Vectorize and Gemini

Fri, 23 Jan 2026 15:30:00 +0800

In 2026, adding AI search to a personal blog is nothing new. But achieving it with zero cost, full automation, and high performance remains a technical topic worth exploring.

This article breaks down the technical architecture behind this site’s AI Search feature, showing how to combine Cloudflare Workers, Vectorize, D1, and Google Gemini to build a closed-loop RAG (Retrieval-Augmented Generation) system.

1. Core Architecture Design

Our goal is a fully automated workflow: write and deploy. The author only needs to push Markdown articles; everything else—vector generation, index updates, frontend deployment—is automated.