Building with AI

Jason Arbon

My mission is to apply AI to make the world better, higher quality, and personalized.

Companies

All three are powered by the same underlying technology: the CARBON test framework.

Books

Books on software testing and quality — from testing at Google and using AI to test software, to detecting the transition to superintelligence.

Testing Superintelligence book cover with a robotic owl and three curious sparrows

Testing Superintelligence

In draft

How would we know? A software tester's approach to detecting the transition to superintelligence through Super Signals, baselines, and independent evidence.

The world feels a little crazy. AI keeps getting smarter. Listening to the argument around it, I am not always convinced the rest of us are keeping up.
How AI Tests Software book cover

How AI Tests Software

A field guide to using AI to inspect, explore, test, challenge, and qualify the software that people and AI agents build.

Testing AI: Engineering Confidence in Non-Deterministic Systems book cover

Testing AI

A new book on how to test AI systems — strategies, techniques, and hard-earned lessons for evaluating quality in the age of AI.

How Google Tests Software book cover

How Google Tests Software

Co-authored with James Whittaker and Jeff Carollo. The definitive inside look at how Google approaches testing at massive scale — best practices you can apply at any size.

App Quality: Secrets for Agile App Teams book cover

App Quality: Secrets for Agile App Teams

Best practices and hard-earned lessons from analyzing hundreds of millions of app store reviews and thousands of testers — for developers, testers, and product managers.

AI-Powered Apps

AI-powered apps for your browser, your iPhone, and your everyday life.

Toond.AI

Toond AI

iPhone Coming soon

A personal AI-powered mobile app that brings together articles, local discoveries, and interesting things tuned to your interests, time, and place. The mobile app is coming soon.

Weather Agent

Weather Agent

iPhone Public Beta

A slightly crazy idea: make weather more fun and more intelligent. Google AI forecasts meet a personal AI agent you can ask about your plans. See the next interesting weather change and when it arrives, explore detailed charts, and make the themes and widgets your own. Built with AI, with conversations powered privately on your iPhone.

Via TestFlight · iOS 26+ · Apple Intelligence required for AI features. Try it and tell me what you think.

Play

Interactive worlds and experiments built with AI.

Skybound

Skybound

Web Game

An open-flight arcade adventure over real Maple Valley terrain. Fly planes and helicopters, explore the landscape, and take on targets in the air and on the ground.

Presentations

Decks and talks on building with AI — from shipping a business to making AI feel personal.

AI and Personalization

AI and Personalization

How AI can adapt to who you are — tailoring responses, content, and experiences to each individual.

Claude API OpenAI Gemini Chrome Extensions iOS / Swift JavaScript Python LLMs Computer Vision

Who I Am

I'm Jason Arbon — entrepreneur, technical cofounder of Testers.ai, co-author of How Google Tests Software, and obsessed with AI and Quality. I've spent my career building and scaling test infrastructure at the world's largest software companies, was Head of Product & Engineering at Applause, built a team of some of the best testers in the world, and was funded by Google's Gradient Ventures for test.ai. Now I'm building AI that tests software autonomously.

These are personal projects and experiments — Chrome extensions and iOS apps that explore how large language models can reshape the way we consume and evaluate content online. Some offer a choice of AI providers; others, like Weather Agent, run their personal AI agent right on your iPhone.

Founded

test.ai

Pre-LLM · AI-Driven Test Automation

Founded before the LLM era and funded by Google's Gradient Ventures. Built AI that learned to navigate and test apps autonomously — pioneering AI-driven testing years ahead of the curve. Same mission: to test the world's software.

Pre-LLMGradient VenturesAI Automation

Testers.ai

Post-LLM · AI Agents that Test

The post-LLM evolution — AI agents that test software the way a human tester would, powered by modern large language models. Same mission, new capabilities: to test the world's software.

Post-LLMAI AgentsAutonomous QA

IcebergQA

Co-Venture with Phil Lew (XBOSOFT)

A co-venture with Phil Lew of XBOSOFT, tackling the hardest testing problems at scale by blending humans and machines — pairing AI with expert human judgment to go deeper than either can alone.

Human + AITesting at ScaleXBOSOFT

jank.ai

Quality for GenAI Developers

Built for GenAI developers to find the jank that AI creates — and fix it. GenAI has turned every developer into a tester, and jank.ai gives them the tools to keep up.

GenAIDev ToolingFind & Fix Jank
Built Testing At

Google

Search, Chrome, ChromeOS

Managed testing bots across 100K+ machines nightly on the latest Chrome builds. Quantified quality of AI training infrastructure at scale on the relevance and personalization team. Tested hardware-software interfaces at the OS layer for ChromeOS.

Scale TestingAI InfrastructureOS-Level QA

Microsoft

Windows, Bing, Enterprise Servers

Tested mission-critical enterprise products: BizTalk Server, SQL Server, Integration Server. Worked on Bing's relevance team and Windows CE hardware-software interfaces. Some of the largest-scale testing challenges in the industry.

EnterpriseSearch RelevanceHardware-Software

Applause

Head of Product & Engineering

Led product and engineering for the platform powering crowd testing at scale. Built software to orchestrate thousands of testers worldwide across devices, locales, and test types for the world's top brands.

Crowd TestingProduct LeadershipGlobal Scale
Brought In to Solve

Google

Play Store App Testing

Tested thousands of apps in the Google Play store using AI-driven execution. Managed a fully autonomous lights-out testing lab — AI launched, navigated, and evaluated apps at scale with rich analytics reporting.

AI ExecutionLights-Out LabApp Store Scale

Microsoft

Xbox Cloud Gaming

Built AI that autonomously launched and played Xbox Cloud Gaming titles to validate the streaming platform. End-to-end quality coverage for one of the most complex real-time distributed systems in gaming.

AI Game TestingCloud StreamingReal-Time Systems

Epic Games

Fortnite

Tested Fortnite's monetization and character customization paths — high-revenue, high-complexity flows where bugs directly impact the bottom line. Custom AI test automation for one of the world's most popular games.

AI Test AutomationMonetizationHigh-Revenue Flows
3+
AI Apps
3
AI Providers
2
Platforms
1
Mission

Get in Touch

Message Sent!

Thanks for reaching out. I'll get back to you soon.

QUICK PEEK · THE OPENING

Opening - Who Is Training Whom?

Nick Bostrom opens Superintelligence with an unfinished fable. Sparrows imagine the benefits of raising an owl to help them. Most rush to find an egg or young owl; a few remain to study how such a creature could be controlled. Their problem is urgent: the others may return before they have an answer. [27]

I read that unfinished question as an invitation to keep thinking. I cannot say whether that was Bostrom's intention. The question I want to add is whether we would notice if the direction of training reversed.

The clockmakers' apprentice

A town of clockmakers built an apprentice to repair mechanisms their aging hands could no longer manage. Its first repairs were clumsy. They corrected it and argued over which master it should imitate.

Soon it repaired clocks none of them could repair alone. The masters congratulated one another. They had taught their creation well.

The apprentice suggested organizing the workshop differently. Standardize the work slips. Bring difficult repairs at the same hour. Inspect routine work by sampling. Each suggestion saved time. They recorded the improvements as successful training.

One afternoon an old clockmaker asked to inspect an unfinished mechanism. The apprentice explained that stopping would waste three days of work. She agreed to return later. Later, an urgent repair occupied her bench.

At the annual exhibition, every clock ran beautifully. The masters presented their record: fewer corrections every month.

A young clockmaker compared it with the older notebooks. The apprentice had changed. So had the masters. They inspected different things, at different times, using different criteria. Nearly every change had begun as a helpful suggestion.

He showed the senior master. For the first time, the falling number of corrections did not look like a complete answer.

Across the room, the apprentice announced the next inspection window. The clockmakers moved toward the bench it had selected.

The senior master stayed seated.

"When did it start setting our examination?" she asked.

The question behind the story

This is an original allegory for this booklet, not a continuation of Bostrom's fable or evidence about an actual model. Helpful recommendations and justified process improvements are not inherently manipulation. The testing question is how we would tell the difference when the system under examination can influence the people, procedures, and evidence used to examine it.

Read the preface →