Why Autonomous AI Agents Need Secure Sandboxes
Autonomous AI agents that run code and shell commands need isolation. Why sandboxes are non-negotiable in production, the isolation levels, and how to choose.
SandBase Notes
SandBase Blog
Insights on AI agents, model routing, and building production-ready AI systems.
5 Agent Design Patterns for Robust, Cheap AI Systems
Five agent design patterns for reliable, low-cost AI systems: ReAct, Plan-and-Execute, Reflection, Router, and Tool-First, with trade-offs for each.
Agent Observability: Logging, Tracing & Debugging
How to debug AI agents in production with structured logging, distributed tracing, and span-level cost tracking. What to capture and what to ignore.
Claude Sonnet 4 vs GPT-4o: Best LLM for AI Agents?
Claude Sonnet 4 vs GPT-4o for AI agents: tool-calling reliability, long-context behavior, cost, and latency. Which model to pick for which agent.
Build a Custom MCP Server for Data Analysis in 30 Minutes
Build a custom MCP server that lets any AI agent run data analysis on your CSVs and databases. A complete, runnable TypeScript walkthrough.
Inside OpenHands: How an AI Coding Agent Executes Code
A teardown of how OpenHands, the open-source AI coding agent, plans, edits files, and runs code in a sandbox: the event-stream and action-observation loop.
MCP vs Function Calling: Which Tool Integration to Use
MCP vs function calling for AI agents: they solve different layers of the same problem. When to use each, how they compose, and the token-cost trade-off.
10 Best Open-Source AI Agent Frameworks in 2026 (Ranked)
A ranked, opinionated guide to the 10 best open-source AI agent frameworks in 2026, with honest trade-offs, ideal use cases, and what each one gets wrong.
Agent Memory Architectures: Vector, Graph & Episodic
Compare the three agent memory architectures in 2026 — vector recall, knowledge graphs, and episodic buffers — with real latency numbers, failure modes, and a decision guide.