How has Netlify’s audience changed as AI enables more people to build software?

Netlify notes a dramatic audience expansion from roughly 17 million professional JavaScript developers to a potential audience in the billions who can work with AI-enabled tools and spreadsheets. Signups grew from about 3,000 per day to around 16,000 per day, signaling a broader, more accessible software-building ecosystem.

What are the three kinds of AX Netlify focuses on?

Netlify describes three AX pillars: Netlify’s own AX (the experience of using Netlify itself), the customers’ AX (how their customers’ sites and products experience agents), and industry eggs (the standards and protocols that help all players interact with AI agents).

What is the 'Why did it fail' feature and what does 'Copy this result to an LLM' do?

Why did it fail is a UI button that collects logs and code when a build fails and sends them to an LLM for a diagnostic. The 'Copy to LLM' option allows users to push the diagnostic result into an LLM for further refinement, reflecting AI-assisted debugging and faster iteration.

What are 'agent runners' and how do they affect work velocity?

Agent runners let teams spin up autonomous runs with code agents to perform tasks and iterations. This enables longer, more uninterrupted work and can substantially boost feature velocity, as engineers can delegate repetitive or well-defined tasks to autonomous agents.

What is meant by the 'two journeys' in developer evolution with AI?

The speaker describes two journeys: one for people from traditional developer backgrounds who learn to work with AI-enhanced workflows, and another for people from non-traditional backgrounds who start building software with AI from the ground up. Both paths show how AI reshapes who can become a software creator and how they approach building with tools and prompts.

“Anyone Can Code Now” - Netlify CEO Talks AI Agents

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Gaming4 min read57 min video

Nov 28, 2025|1,103 views|26|13

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Key Moments

TL;DR

AX era redefines dev work: broader audience, faster velocity, new economics.

Key Insights

AX (Agent Experience) becomes the product north star, expanding beyond traditional UX to how agents interact with products and services.

The addressable audience for tooling expands dramatically—from a developer-centric base (~17M) to billions via AI agents and new personas.

Developer roles are evolving: coding remains important, but clarity, systems thinking, and user understanding become core developer skills.

Autonomous agent tooling (e.g., agent runners) can speed up feature velocity, but require careful orchestration and ongoing human feedback.

Economics are shifting toward usage and outcome-based models; token-based costs and value signals are increasingly important.

The web consumption layer will increasingly incorporate AI-driven agents and content negotiation, reshaping browsers and UI paradigms.

The future of software is broader than traditional coding—more people will be involved in software as a generalized skill, not just professional developers.

AX AS NORD STAR: AGENT EXPERIENCE AT THE CORE

The conversation centers on AX (Agent Experience) becoming the guiding north star for product development. AX moves beyond traditional user experience to design products that anticipate and respond to autonomous agents as they navigate, use, and even create on top of a platform. Netlify splits AX into three layers: Netlify’s own AX (the agent experience of using Netlify), the customer AX (how customers enable agents to build and run sites), and industry AX (the shared protocols and standards that make agent interactions reliable). This reframing positions documentation, onboarding, and developer tooling as interfaces for agents, not just humans.

MASS ADOPTION AND AUDIENCE EXPANSION

The dialogue highlights a massive shift in audience reach: from 17 million professional JavaScript developers to a potential 3 billion people who can utilize AI tools and agents. Netlify’s signup cadence reflects this change—moving from about 3,000 signups per day to roughly 16,000 per day. Agents are driving this growth, with various platforms and ecosystems feeding the influx. Importantly, onboarding now attracts non-traditional personas like marketers and designers, signaling a broader, more diverse user base converging around agent-enabled workflows.

DEFINING A DEVELOPER IN THE AGE OF AI

A central theme is the redefinition of what it means to be a developer. The core ability—conceptualizing and articulating what a system should do—gains prominence as writing code itself becomes less central due to AI. However, the counterpoint suggests coding won’t disappear; instead, the landscape shifts toward higher-level design, systems thinking, and clear communication with AI agents. The idea is that developers will still create, but their focus will broaden to orchestrating AI-driven capabilities and ensuring user-centric outcomes.

AUTONOMOUS AGENTS, RUNNERS, AND VELOCITY

Autonomous agents and tools like agent runners dramatically boost velocity by enabling long-running tasks and iterative development cycles. The host and guest discuss how automation accelerates feature delivery, yet acknowledge the unpredictability of fully autonomous agents. Practical strategies emerge, such as the ‘why did it fail’ feature that uses logs and prompts to diagnose issues, and the ability to copy results to an LLM for debugging. This reflects a shift toward asynchronous, feedback-driven development with AI as a powerful co-pilot.

ECONOMICS: TOKEN-BASED USAGE AND OUTCOME VALUE

Economic models are adapting to token-based usage, with attention toward more outcome-based value rather than raw usage. Pricing experimentation reflects the challenge of predicting token consumption for long or complex queries. The industry is exploring models that align price with meaningful outcomes (speed, reliability, accuracy) rather than purely counting tokens. This acknowledges the variability in AI-driven workloads and the need for pricing that reflects real value delivered to users and businesses.

THE FUTURE OF THE WEB: AI-ENABLED CONSUMPTION AND BROADER CREATION

The discussion anticipates a transformation of how we consume and create on the web. Browsers and content delivery will incorporate AI, enabling content negotiation and agent-aware experiences. The traditional UI-dominated web may give way to AI-driven interactions where agents browse, interpret, and even create content on behalf of users. Yet the speakers also caution against a complete replacement of human-driven interfaces, predicting a multifaceted evolution where AI and human collaboration coexist, with new forms of software architecture and collaboration emerging.

OPENNESS, OPEN SOURCE, AND HUMAN-CENTERED AUTOMATION

An undercurrent theme is the tension between AI-as-developer versus AI-as-a toolset. Netlify’s stance emphasizes empowering humans to continue steering and shaping software rather than ceding all control to AI. The panelists share anecdotes about PRs, code reviews, and open-source ecosystems, noting that skilled engineers can leverage AI to accelerate work while still maintaining control, quality, and architectural coherence. This human-in-the-loop approach aims to preserve creativity, responsibility, and long-term maintainability in an AI-augmented landscape.

Mentioned in This Episode

●Software & Apps

●People Referenced

Common Questions

AX stands for Agent Experience. It reframes product interaction around AI-driven agents rather than just human users, and Netlify positions AX as its north star for designing onboarding, documentation, and workflows to support autonomous agent interaction with their platform. This shift emphasizes that the product experience now also has to accommodate agents acting on behalf of humans.