The missing design vocabulary for agents.

Impeccable: Design skills for AI harnesses

1 skill, 23 commands, and curated anti-patterns for impeccable frontend design. Works with Cursor, Claude Code, GitHub Copilot, Gemini CLI, and Codex CLI.

A tale of two Agent Builders

What two competing solutions to the same design problem tell about the future of designing AI interfaces.

Impeccable: Design skills for AI harnesses

1 skill, 18 commands, and curated anti-patterns for impeccable frontend design.

It's Time To Start Preparing APIs for the AI Agent Era

With agentic AI, integrations are no longer static and immutable concepts.

Introducing AX: Why Agent Experience Matters

As builders, we need to start focusing on AX or “agent experience” — the holistic experience AI Agents will have as the user of a product or platform.

Writing effective tools for AI agents—using AI agents

Writing effective tools for AI agents—using AI agents

Agent Plugins

A portable package format for reusable components that extend AI agents.

Agentic Engineering Management

To what extent AI is OK to use in software development might be debated, but in general, the idea is not a controversial one anymore. The debate rather moved on from code completion and simple PR summarizations to Agentic Engineering, where an execution loop allows an AI Agent to function

LukeW | Agent Management Interface Patterns

As an increasing number of AI applications evolve to agents doing work for people, agent management becomes a critical part of these product's design. How can p...

Agent Design Is Still Hard

My Agent abstractions keep breaking somewhere I don’t expect.

Beyond agentic coding

AI dev tooling can do better than chat interfaces

Agent Skills

AI coding agents take the shortest path to done, which usually means skipping the specs, tests, and reviews that make software reliable at scale. Agent Skill...

Popmelt — Design copilots for AI agents

Our Taste models encode design expertise and philosophy, giving AI agents instant access to a curated catalog of aesthetic knowledge. Unlike traditional templates and design systems, our imprints are AI-native and guided by universal principles. This means agents can apply them to any interface scenario, not just predefined layouts and elements. They're also customizable and extensible, letting you build quickly without falling into the cookie-cutter UI library trap.

The Landscape of Emerging AI Agent Architectures for Reasoning, Planning, and Tool Calling: A Survey

This survey paper examines the recent advancements in AI agent implementations, with a focus on their ability to achieve complex goals that require enhanced reasoning, planning, and tool execution capabilities. The primary objectives of this work are to a) communicate the current capabilities and limitations of existing AI agent implementations, b) share insights gained from our observations of these systems in action, and c) suggest important considerations for future developments in AI agent design. We achieve this by providing overviews of single-agent and multi-agent architectures, identifying key patterns and divergences in design choices, and evaluating their overall impact on accomplishing a provided goal. Our contribution outlines key themes when selecting an agentic architecture, the impact of leadership on agent systems, agent communication styles, and key phases for planning, execution, and reflection that enable robust AI agent systems.