A mature technology isn’t the finish line for product work — it’s the starting line. Through the lens of voice input products like Typeless and PLAUD, this piece explores how AI transforms a long-solved technical problem into a new frontier of product design, where the real challenge shifts from “can we build this” to “how deep can the experience go.”

Edwin Chen built Surge AI into a $1B company training ChatGPT, Claude, and Gemini — with fewer than 100 people, zero VC funding, and a scientist’s obsession with doing things right. Here’s what his unconventional path reveals about building in the age of AI.

A designer and PM turned a small workplace frustration into a fully deployed web product — with AI as the co-builder. This is the story of shipping something real for the first time and what it taught about the future of making things.

AI can generate illustrations, but can it arrange them on a slide like a designer would? We built a full pipeline to explore how AI can learn spatial layout — and turned the findings into a research paper.

Google went from fumbling the AI race to topping the App Store with Gemini. A product leader inside Google reveals how the company reframed an existential threat into its biggest advantage — and the lessons that apply to any team navigating disruption.

While the spotlight stays on ever-larger AI models, the smart money is moving in the opposite direction. Insights from Microsoft, NVIDIA, and academia reveal why small, specialized models are quietly becoming the real future of AI deployment.

The old model of rigid roles and sequential handoffs is giving way to something more dynamic. As AI handles more execution, teams are shifting toward fluid collaboration where humans focus on strategy and creative problem-solving.

You don’t need billions of dollars to build a winning AI product. Here are three strategic paths — riding existing models, fine-tuning your own, or orchestrating multiple models — that let small teams compete without training the next GPT.

Reforge CEO Brian Balfour predicted the rise of Facebook and Google Ads before most marketers caught on. Now he’s calling ChatGPT the next dominant growth channel — and the pattern behind his prediction applies to every platform shift of the past two decades.

Most people treat AI like a search engine and get generic results. The real breakthrough comes from collaborating with AI — bringing your own ideas, iterating together, and challenging its outputs. Here are 8 practical ways to level up.

How an AI product handles its loading screen reveals whether it sees itself as a tool or a collaborator. This design choice quietly shapes user trust, engagement, and the entire relationship between humans and AI.

As tech giants race to build ever-larger AI models, the real opportunity for small teams lies in the application layer. The key isn’t building the biggest model — it’s identifying the perfect transformation that turns AI capabilities into real user value.

The creator of the first prompt engineering guide reveals that much of what we believe about AI prompting is outdated. Backed by the largest study ever conducted with OpenAI, Microsoft, and Google, here’s what actually works now.

OpenAI’s Chief Product Officer shares a mind-bending perspective: today’s AI is the worst you’ll ever use. From the AI paradox to the future of human-AI collaboration, here are the key insights that changed how I think about where AI is headed.

Manual image review couldn’t keep up with real-time AI generation. So I built a Custom GPT reviewer using our existing style guides — no model training, no dataset, just clear rules. It matched human reviewers on 19 out of 20 test images, all in under 30 minutes.