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14 posts tagged with "agents"

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AG-UI: The Missing Protocol Between AI Agents and Your Frontend

· 4 min read
Gergely Sipos
Frontend Architect

AG-UI (Agent User Interaction Protocol) is an open, event-based protocol that standardizes how AI agents communicate with user-facing applications. Created by CopilotKit and adopted by Microsoft, Google, AWS, LangChain, and CrewAI, it fills the gap between MCP (agent↔tools) and A2A (agent↔agent) by defining the agent↔UI layer. It's MIT licensed with 14.4k GitHub stars and 50+ framework integrations.

The LLM Wiki Now Has a Formal Spec — OKF v0.1 📐

· 5 min read
Gergely Sipos
Frontend Architect

The LLM Wiki pattern — previously just a gist from Karpathy and a growing community convention — now has a formal, versioned specification. On June 12, Google Cloud's Data Cloud team published OKF (Open Knowledge Format) v0.1, a vendor-neutral spec for representing curated knowledge for AI systems. This is the fourth post in our LLM Wiki series (previous posts: the pattern, our wiki mapping, local models), and arguably the most significant development since the idea first gained traction.

Copilot Automations: Your AI Team Member That Never Sleeps 🤖⏰

· 7 min read
Gergely Sipos
Frontend Architect

GitHub Copilot started as autocomplete for code. Then it became a chat assistant. Then a coding agent you could assign issues to. Now it's crossing the final threshold: an autonomous agent that runs on a schedule, without anyone prompting it. Copilot Automations turn your AI assistant into a background team member — one that shows up at 9am every day, does useful work, and opens a PR for review.

chronicle:cost-tips — Copilot Billing Is Live, Here's Your Spend Analyzer 💸

· 4 min read
Gergely Sipos
Frontend Architect

Usage-based billing went live on June 1. Two days in, most developers have zero visibility into what's actually burning their premium requests. Chronicle just shipped a new cost-focused command — /chronicle:cost-tips — that surfaces exactly that. Think of it as the spending companion to the workflow-quality /chronicle:tips command we covered in April. It builds on the same session insights infrastructure in VS Code but points the lens squarely at your wallet. This post is commentary on why it matters right now.

VS Code Chronicle — Your Agent History Is Now Queryable 🗂️

· 6 min read
Gergely Sipos
Frontend Architect

VS Code 1.118 shipped an experimental feature called Chronicle on April 29, 2026, and it solves a problem most of us have been working around for months: your Copilot Chat history is now a queryable artifact, not a scroll-to-find afterthought. If you've ever prepped for a standup by scrolling through yesterday's agent sessions, or tried to remember what you did across three branches last Thursday, Chronicle targets exactly that pain. The full details are in the VS Code 1.118 release notes — this post is commentary on why it matters, not a restatement of the feature spec.

awesome-copilot: The Community Collection Your Copilot Setup Is Missing

· 4 min read
Gergely Sipos
Frontend Architect

If you've set up GitHub Copilot, written a .github/copilot-instructions.md, maybe defined a custom agent or two — and then wondered "what now?" — the answer is awesome-copilot. It's the single most useful community resource for anyone pushing Copilot beyond defaults. Maintained under the github org, it has built a large community of users and contributors. It covers agents, instructions, skills, plugins, hooks, and agentic workflows — basically every customization surface Copilot exposes. If your setup ends at a .github/copilot-instructions.md, this repo is where you go next.

Inside Nemetschek's Multi-Agent Copilot Setup 🤖🧩

· 12 min read
Gergely Sipos
Frontend Architect

When your product is an AI assistant, using AI to build it feels natural — but doing it well is harder than it sounds. The AI-Assisted Development section describes these patterns in the abstract. This post is what they look like after a year in production on a real Aliz frontend: a React + TypeScript chat-based AI assistant with theming, 18-language internationalization, MCP integrations, and multi-environment deploys. The codebase is large enough that no single prompt can reason about it coherently, which is the whole reason the team stopped reaching for a tool and started building a system — the same shape described in Multi-Agent Orchestration. Three layers of AI setup, a team of specialist agents, and a workflow called QRSPI hold it together.

We Accidentally Built an LLM Wiki 📚

· 9 min read
Gergely Sipos
Frontend Architect

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.