Go 1.24 has no revolutionary changes—mostly incremental improvements that show up in daily coding. range-over-func graduated from experimental and is safe for production. Performance percentages in the notes follow the official write-up and were not reproduced here.

OWASP is watching this: AI Agents are expanding their capability boundaries rapidly — writing code, executing commands, calling external APIs, querying databases. The more capable they become, the larger their attack surface.

In 2024, Anthropic research demonstrated that LLMs can retain backdoor behaviors even after standard safety training. OWASP listed prompt injection as the #1 threat to LLM applications. Deploying AI Agents in production means security is not optional.

AI Agents have a persistent problem: every Agent needs its own custom tool integration code. Switch to a different Agent? All tool integrations need to be rewritten from scratch. MCP (Model Context Protocol) solves exactly this.

Pick OpenSpec for mid-size features: write proposal / spec / design / tasks as Markdown before any edit. Skip it for a typo or a one-file patch.

TypeScript types hold the boundary: HTTP, database, and third-party SDK input start as unknown. Turn strict on. Compile-time contracts and runtime checks must match; tsc does not validate production traffic.

pi-mono exists because the dominant AI agent tooling is Python: LangChain, LlamaIndex, Dify, CrewAI. In the TypeScript / Node.js ecosystem, options for adding AI capabilities are limited. pi-mono tries to solve this. It’s a TypeScript monorepo offering a complete toolkit from low-level LLM API to high-level coding agent.