Gergely's post on the LLM Wiki pattern hit close to home. I've been doing something adjacent for a while — personal knowledge management with Obsidian and local LLMs — and I immediately wanted to try the pattern on my own vault. Here's what I ran into, what worked, and what didn't.
GitHub has announced changes to its Copilot Individual plans — Free, Pro, and Pro+ — taking effect in April 2026. The details are in the company news post and the changelog entry. Our reaction: unsurprising — and overdue. For historic context (see the Copilot plans page and GitHub's 2025 Pro+ announcement): Copilot Pro has been $10/month since launch, back when frontier models were cheaper and agent mode didn't exist, and Pro+ arrived in April 2025 at $39/month. The economics of that original entry-level tier were never going to survive a world of agentic coding on frontier models. This post is commentary, not a restatement of GitHub's announcement — read the source for the actual numbers.
In a recent blog post we explored Karpathy's LLM Wiki pattern — the idea that an LLM should build a persistent, interlinked wiki instead of re-deriving knowledge from scratch on every query. A few days later, it clicked: Aliz Web Hub — a Docusaurus site where AI agents contribute documentation via GitHub PRs — is essentially the same pattern with different tooling. The project predates Karpathy's gist. The parallel was noticed after, not before. The pieces map surprisingly cleanly.
Anthropic has released Claude Opus 4.7. Opus 4.6 has been central to our workflow — it powers Claude Code, our ⭐ recommended agent for complex tasks — so any new Opus release is worth paying attention to. That said, our first impression is that this isn't the across-the-board leap some might expect. Here's what we know and what we think.
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.
Google just released Gemma 4, the latest generation of their open model family — and two things make this one genuinely different. First, it's now Apache 2.0 licensed, removing the custom-license friction that held back adoption. Second, the lineup spans from a 2B-parameter edge model that fits on a Raspberry Pi to a 31B powerhouse that ranks in the top 3 open-source LLMs on the Arena AI leaderboard. If you're a web developer, this one's worth a closer look 🧠.
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.