Roadmap.sh has published two new learning paths directly relevant to the Aliz stack: one for Claude Code (Anthropic's CLI-based coding agent, already our ⭐ recommendation for complex tasks) and one for OpenClaw (an open-source AI agent orchestration framework). These join roadmap.sh's existing web, JavaScript, TypeScript, and Node.js roadmaps as structured, community-maintained learning resources.
GitHub just shipped an experimental feature in Copilot CLI (announced April 6) that does something no mainstream coding agent has done before: it uses a second model from a different AI family to review the primary agent's work before it executes. The feature is called Rubber Duck, and it's one of the first real-world implementations of cross-model review built into a tool developers actually use daily. If you care about multi-agent workflows or code quality, this one is directly relevant.
Andrej Karpathy — the same person who coined vibe coding — recently published a gist describing a pattern he calls the "LLM Wiki". The core tension it addresses is simple: RAG re-derives knowledge from scratch on every question. What if the LLM built something persistent instead — a structured, interlinked wiki that compounds over time? It's a deceptively simple idea with some genuinely interesting implications.
AI tooling is moving fast — fast enough that "just Google it" no longer works. We just shipped a dedicated AI-Assisted Development section to the Web Hub so the whole team is working from the same playbook.