My $182 ARM SBC draws 7 watts and runs a full AI agent with browser automation. Here’s every stupid problem I hit getting there. So I had this Rock 5B (RK3588, 16GB RAM, 1TB NVMe) sitting around running headless Ubuntu 22.04. Thought it’d be fun to turn it into a self-hosted OpenClaw box with WhatsApp integration and remote desktop. The Good Part Installed XFCE4 + xrdp + Chromium in parallel via SSH.

Context Management Is the Real Bottleneck for AI Agents Ever since Anthropic released MCP (Model Context Protocol), I’ve felt that this company has a uniquely sharp perspective on the model-to-user relationship. MCP gave agents a standardized way to access external tools and data. Then came Skills — reusable bundles of instructions and workflows that promised to make agents more “capable.” Together, they represent two sides of the same coin: MCP expands what the agent can do; Skills shape how the agent thinks.

How business-logic-aware MCP implementations can transform user experiences beyond simple database management The Current State of MCP in Databases MCP (Model Context Protocol) has been gaining significant attention lately, but I believe its potential in database applications is still largely underestimated. Most current database MCP implementations focus primarily on database administration tasks—exposing capabilities like SHOW TABLES, SHOW DATABASES, and basic DDL operations like ALTER TABLE. While these implementations often include natural language to SQL capabilities, they operate at a very generic level, similar to early database administration tools like PHPMyAdmin.

Vector Databases: A Traditional Database Developer’s Perspective As a traditional database developer with machine learning platform experience from my time at Shopee, I’ve recently been exploring vector databases, particularly Pinecone. Rather than providing a comprehensive technical evaluation, I want to share my thoughts on why vector databases are gaining significant attention and substantial valuations in the funding market. Demystifying Vector Databases At its core, a vector database primarily solves similarity search problems.

ClickHouse on DataFrame To be the Fastest SQL Engine on Any Format The story begins with the undeniable fact that ClickHouse is the fastest open-source OLAP engine on the planet. Even when your data outgrows your memory capacity, it can still process it at lightning speed with incredible memory efficiency. Every challenger in this field tries to prove they are faster and easier to use than ClickHouse. However, the unique nature of databases means that five years might just be a warm-up, and it takes a decade to truly master the craft.

The Start During the Lunar New Year in February last year, in order to solve the efficiency problem of the machine learning model sample data I was facing at the time, I created chDB. Of course, compared to everything that the creators of ClickHouse have done so far, chDB is just a tiny hack on ClickHouse local. Running Everywhere Despite many imperfections, chDB quickly gained a lot of fans in a way that surprised me.