How Google Labs Evaluates and Selects AI Ideas Worth Building

How Enterprises Build and Manage AI Experimental Teams

Google Labs serves as Google's frontline for exploring new AI-driven products such as NotebookLM and Flow. The team runs small-scale experiments across software and related hardware to test novel product experiences. Josh Woodward, a Google veteran of over ten years, currently leads Google Labs, the Gemini app, and AI Studio, spanning early exploration to scaled product growth.

Woodward argues that because AI model capabilities advance faster than most companies' strategic planning cycles, every organization needs a dedicated "frontier exploration" team. He describes this team as "people with eight $200-per-month subscription accounts" whose job is to stay constantly sensitive to the latest trends by actively using the newest models.

Three Product Lifecycle Stages and Their Distinct Priorities

Woodward outlines three internal stages for a product's life:

Zero to One : Focus on capturing user attention and detecting early signals.

One to Ten : Shift to user growth and feature refinement.

Ten to One Hundred : Optimize conversion funnels and customer acquisition costs, entering a scaling game.

The critical challenge is keeping innovative energy alive at each stage while preventing mature products from crowding out the attention and resources needed for frontier exploration.

Three Principles to Avoid the "Three-Year Decay" of Corporate Labs

History shows corporate labs often lose effectiveness or disappear within three to four years, or fail to commercialize their outputs. Woodward offers three guidelines:

Create organizational independence : The lab must be a space where "weird things" can grow, not placed under an existing business unit.

Define clear goals and success metrics : Decide whether the lab feeds incubated projects into existing products or invents entirely new product lines and categories. Google Labs began as a "graduation lab" and expanded as AI blurred category boundaries.

Use the lab to challenge the company's ways of working : Beyond product or tech exploration, the lab should "manufacture good trouble" that forces the broader organization to improve its processes.

Sourcing and Filtering "Good Ideas"

Woodward details how the Labs team discovers promising concepts, evaluates whether an idea merits investment, and decides when to abandon a pursuit. A key mechanism is tracking "Almost Possible" product concepts — ideas that are nearly feasible with current model capabilities — and revisiting them as models improve.

Future Directions for Consumer AI Products

The discussion highlights emerging opportunities for consumer AI in entertainment, communication, and daily life services, suggesting these domains will see significant innovation as model capabilities expand.