Human skills in anticipatory design and user flows are crucial to combat the ‘uncanny valley’ of AI UX.

Any LLM can put together plausible docs with some context and a simple prompt.

AI doesn’t just add intelligence — it redistributes it. Here’s how that shift can make or break a product.

AI-native startups are doing more with less — 40% smaller teams, 6x higher revenue per employee — and the data confirms it’s not just hype.

The next $1T company will be a software company masquerading as a services firm.

Accessibility was designed for humans, but the surface it exposes in your apps can benefit your agents and save you money — if you populate it.

Generate editable Figma designs from AI — GPT, Claude, Gemini, you name it — without leaving Figma. Real layers. Real auto-layout. Not a screenshot.

Report by Anthropic reveals how AI has been narrowing the "front door" for new talent.

The chat interface is fine for users. The flat message model behind it is a bad fit for agentic systems. Here’s what it erases.

A mental model for thinking about all the big changes that are happening as a single transition.

Removing the context-gathering bottleneck for most support work.

When someone says "AI", ask: "Which category?" Force specificity.

LLMs drift, fabricate tokens, and start every session from scratch. Here’s how to feed your design system to AI coding agents so they stop guessing.

Systematic analysis of how AI systems make decisions — from product recommendations to developer tool choices.

Before writing code, dialog with progressive levels of design alignment.

How pressure to deliver fast erodes the deep thinking necessary for truly functional products.

Anthropic’s new Academy transitions from tool-specific tutorials to a mental model of AI fluency.

Four categories of task that you should consider before turning to AI.

Our current neoliberal version of capitalism has built a rent-extraction layer on top of human limitations that agents don't have.

Simply throwing a massive spec at an AI agent doesn’t work—context window limits and the model’s “attention budget” get in the way.