Chris (Links) (@links.chris.blue) Bsky - nopzon.com

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Posts by Chris (Links)

Agentic Annotated Bibliography

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Introducing FastMCP 3.0 🚀 Move fast and make things.

2 months ago 1 0 0 0

Scaling PostgreSQL to power 800 million ChatGPT users | OpenAI By Bohan Zhang, Member of the Technical Staff

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Clouded Judgement 12.12.25 - Long Live Systems of Record Every week I’ll provide updates on the latest trends in cloud software companies.

3 months ago 0 0 0 0

AI’s trillion-dollar opportunity: Context graphs - Foundation Capital By building context graphs from decision traces, AI agent startups are capturing the “why” behind the “what” - and gaining a structural advantage in shaping what comes next. Continue reading

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The State Of LLMs 2025: Progress, Progress, and Predictions A 2025 review of large language models, from DeepSeek R1 and RLVR to inference-time scaling, benchmarks, architectures, and predictions for 2026.

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Building internal agents A few weeks ago in Facilitating AI adoption at Imprint, I mentioned our internal agent workflows that we are developing. This is not the core of Imprint–our core is powering co-branded credit card programs–and I wanted to document how a company like ours is developing these internal capabilities. Building on that post’s ideas like a company-public prompt library for the prompts powering internal workflows, I wanted to write up some of the interesting problems and approaches we’ve taken as we’ve evolved our workflows, split into a series of shorter posts:

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octopii/docs/ARCHITECTURE.md at master · octopii-rs/octopii 🦑 Distributed Systems Kernel written in rust

3 months ago 0 0 0 0

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sorted string tables (SST) from first principles why sorted string tables are the swiss army knife for data systems and how they are implemented

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S3 Express One, Value-Less LSM Trees, ShardStore Amazon S3 Express One Zone Storage Class is the "fastest cloud object storage for performance-critical application." How does it work?

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frameworks for understanding databases building mental models for tradeoffs in performance, availability and durability in data systems

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Can LLMs give us AGI if they are bad at arithmetic? – Wes McKinney <img src="https://wesmckinney.com/images/llm_counting_degradation.png" /><br/>

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Build Your Own Database A step-by-step guide to building a key-value database from scratch.

5 months ago 7 1 0 0

Concurrent Local Coding Agents · xxchan's blog AgentDev, toolset and UI for Git Worktrees and agent sessions - My opinionated, more flexible version of Cursor 2.0

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Event Streaming is Topping Out There's no money left in real-time event streaming. A major consolidation wave is beginning.

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Mike Waud - Problems for Future Me From NervesConf US 2024

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A Friendly Tour of Process Memory on Linux A deep dive into how Linux manages process memory, page tables, and virtual address spaces

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AI's Dial-Up Era It is 1995.

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Inside the race to build agent-native databases Subscribe • Previous Issues

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Current New Orleans 2025 Conference highlights.

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Inside NVIDIA GPUs: Anatomy of high performance matmul kernels - Aleksa Gordić From GPU architecture and PTX/SASS to warp-tiling and deep asynchronous tensor core pipelines.

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Iceberg CDC: Stream a Little Dream of Me Iceberg v3 gave CDC identity and precision, v4 makes change detection light and metadata compact. Streaming icy edges finally start to…

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Corrosion · The Fly Blog Corrosion is distributed service discovery based on Rust, SQLite, and CRDTs.

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Inside Husky’s query engine: Real-time access to 100 trillion events | Datadog See how Husky enables interactive querying across 100 trillion events daily by combining caching, smart indexing, and query pruning.

6 months ago 1 0 0 0

Event-Hidden Architectures | Skip Interactive features without events

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https://arxiv.org/pdf/2509.00997

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R2 SQL: a deep dive into our new distributed query engine R2 SQL provides a built-in, serverless way to run ad-hoc analytic queries against your R2 Data Catalog. This post dives deep under the Iceberg into how we built this distributed engine, from its metadata-driven planner to its parallel execution model.

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This Send/Sync Secret Separates Professional From Amateur Rust Developers 2 Months of Banging My Head Against Send/Sync, Explained in One Coffee Break

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[2504.16736] A Survey of AI Agent Protocols The rapid development of large language models (LLMs) has led to the widespread deployment of LLM agents across diverse industries, including customer service, content generation, data analysis, and even healthcare. However, as more LLM agents are deployed, a major issue has emerged: there is no standard way for these agents to communicate with external tools or data sources. This lack of standardized protocols makes it difficult for agents to work together or scale effectively, and it limits their ability to tackle complex, real-world tasks. A unified communication protocol for LLM agents could change this. It would allow agents and tools to interact more smoothly, encourage collaboration, and triggering the formation of collective intelligence. In this paper, we provide the first comprehensive analysis of existing agent protocols, proposing a systematic two-dimensional classification that differentiates context-oriented versus inter-agent protocols and general-purpose versus domain-specific protocols. Additionally, we conduct a comparative performance analysis of these protocols across key dimensions such as security, scalability, and latency. Finally, we explore the future landscape of agent protocols by identifying critical research directions and characteristics necessary for next-generation protocols. These characteristics include adaptability, privacy preservation, and group-based interaction, as well as trends toward layered architectures and collective intelligence infrastructures. We expect this work to serve as a practical reference for both researchers and engineers seeking to design, evaluate, or integrate robust communication infrastructures for intelligent agents.

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Supporting our AI overlords: Redesigning data systems to be Agent-first This Berkeley systems group paper opens with the thesis that LLM agents will soon dominate data system workloads. These agents, acting on b...

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