A deep dive into OpenSEO
Explore OpenSEO's architecture: SEO data APIs, Cloudflare Workers, its audit crawler, MCP tools, AI agents, storage, and self-hosting trade-offs.
Topic
#architecture
29 篇笔记
构建你的 AI FDE 能力入门篇： 0x01 Palantir 架构中心·中文全解
本系列编译自 Palantir Architecture Center 官方文档，共 7 篇，从整体架构到各核心层逐层拆解 Palantir 的技术体系。建议阅读顺序总览：Palantir 架构中心导读 —— 全局地图，先读这篇 AIP、Foundry 与 Apollo：一体化平...
An Accidental Blackboard
Notes from my Thoughtworks colleagues on AI-assisted software delivery
AI Chip Architectures
A look at AI Chip Architectures. NVIDIA, AMD, TPUs, Trainium, Groq, Cerebras.
Agent 的 Sandbox 到底是怎么实现的？
从 Codex、Claude Code、Gemini CLI 到 OpenHands很多人讨论 AI Agent 安全时，关注的是：“模型会不会执行危险命令？”但真正重要的问题其实是：即使 Agent 决定执行危险命令，底层系统是否允许它成功？这就是 Sandbox（沙箱）存在的...
io_uring：Linux 的高效异步 I/O 框架
iouring：Linux 的高效异步 I/O 框架 原文: Efficient IO with iouring — Jens Axboe, 2019 作者: Jens Axboe（Linux 块设备层与 I/O 子系统核心维护者） 说明: 本文翻译并梳理了 iouring 的设计思想、核心机制与使用方式。 📝 摘要 iouring 是 Jens Axboe 于 2019 年提出的 Linux…
The Audit Log Page
An audit log has two readers. Most logs are designed for the wrong one. Five theses on product audit logs.
Building the last WAL on S3
Nearly two years ago, we started Archil with a simple realization: it was clear that people were spending immense effort to build new, serve...
wal3: A Write-Ahead Log for Chroma, Build on Object Storage
wal3, Chroma's write-ahead log, combining a 30-year-old lock-free algorithm with S3's newest conditional writes feature.
From context to dreams: architecting memory for AI agents
Have you ever felt that every conversation you have with an LLM across sessions feels like starting over from scratch? LLMs have a problem: ...
Kyverno is a platform primitive, not a security tool
Where does Kyverno live in your organization? I don’t mean which cluster! On which team’s slide deck does it show up? Whose budget line? For most companies I’ve…
PaddleOCR-VL 服务问题排查与部署汇总
📝 摘要 本文汇总了 PaddleOCR-VL 服务在 vLLM 部署下的效果问题排查结论及完整部署方案。客户反馈 PaddleOCR-VL 丢失版面分析能力，根本原因是直接用 OpenAI SDK 裸调 vLLM 的 接口，只调用了 VLM 识别模型而绕过了版面分析模型 PP-DocLayoutV3。PaddleOCR-VL 的正确用法是两阶段 pipeline：版面分析 + VLM 识别。文…
所有想做 FDE 的人，都该读懂 Palantir 这套方法
大模型进入企业以后，最难的一步是把一家公司的数据、规则和权力关系，变成 AI 能够理解并安全执行的系统。2026 年 5 月，OpenAI 成立了一家专门负责企业部署的新公司。它准备投入超过 40 亿美元，并计划通过收购 Tomoro，一次带入约 150 名 Forward De...
LLM Inference: Past, Now, and Future — Where Does the Value Move?
LLM Inference — Past, Now, and Future: Where Does the Value Move?For the past two years, LLM inference has been one of the most contested la...
What is WAL backpressure, and why does ClickHouse Managed Postgres need it?
How ClickHouse Managed Postgres uses WAL-aware backpressure to slow client writes, protect disk space, and let the archiver recover.
YC 开源 QM：当每个员工都有 Agent，公司需要怎样的协作系统？
未来一家公司里，可能每个员工都有自己的 Agent。它们能读文件、查数据库、写代码、回复邮件，也能在后台持续运行任务。问题随之而来：这些 Agent 应该看到什么？记住什么？使用谁的账号？哪些能力可以共享？危险动作由谁批准？7 月 31 日，Y Combinator 开源的 QM...
Agency: Secure, scalable sandboxes for agents
This is part of our series on how we're AI-pilling Sierra.In our last few posts, we talked about what happens when every employee has a sing...
We rewrote our agent to run entirely in a Durable Object with Pi, Agents SDK and Code Mode
We recently finished moving the camelAI agent off of virtual machines. The agent now runs inside a Cloudflare Durable Object, its filesystem...
A Swarm of Agents for Multi-Angle Analysis: Building a Team of Experts from LLMs
Not about speed. About making several agents with different viewpoints argue over one decision and reach a conclusion better than any of the...
Trust Doesn't Live in Code Review
The gate you becameAgents write code faster than anyone can read it. This is not a forecast; it is the baseline now. A single agent, in an a...
Optimizing distributed AI inference: Advanced deployment patterns
Learn about the three optimization levers for distributed AI inference: prefill/decode disaggregation, KV cache strategy, and speculative decoding.
Migrating LiteLLM to Rust - Building the Fastest and Litest AI Gateway
LiteLLM is moving its AI gateway to Rust: 15x throughput, 11x less memory, and sub-1ms per-request overhead. No v2, no migration, your config stays the same.
The 7 Types of Agent Memory: A Technical Guide for AI Engineers
Agent memory explained: the 7 types — working, semantic, episodic, procedural, retrieval, parametric, prospective — and when to build each.
The Agent Loop Architecture
Everyone's asking "WTF is a loop?" Here's the question nobody's asking: what runs the loop?The AI discourse has converged on loops as a core...
Complete Map of Graph Technology 2026: 128 Products, 7 Categories
The complete guide to graph databases, knowledge graphs, GraphAI, and more. 7 categories, 128 graph technology products, 113 vendors
knowledge-catalog/okf/SPEC.md at main
Google Cloud Knowledge Catalog Tools and Samples. Contribute to GoogleCloudPlatform/knowledge-catalog development by creating an account on GitHub.
Launching a million sandboxes per second in constant time
They say that in the future, everyone will have their own sandbox company for 15 minutes. Let's make that simpler, here's exactly how I buil...
Faking a Filesystem For your Agent: PostgresFS
Faking a filesystem for your agent: why PostgresFS lost to a skillCo written by @SufjanFana Working with agent harnesses, it is hard not to ...
DuckDB Internals: Why is DuckDB Fast?
Walk through DuckDB's internals: how it skips serialization overhead, parses and optimizes SQL, and stores data in columnar row groups with zone maps.