AI at Goodnotes: how we work, learn, and build together
We are building a future in which AI doesn’t replace people but helps us reach new heights in both ambition and polish. If this sounds exciting to you too, you’d fit right in.
What do we actually do?
Many companies talk about AI adoption but gate access behind approvals and rate limits. We've taken a different path.
Generous access by design
Every employee — engineer or not — has access to hundreds of models through our internal LLM Router and our “GoodGPT” portal. Fill the context window with every prompt and leave rate limits behind.
Multi-tool culture
We encourage "multi-wielding" — using Goodnotes AI, ChatGPT, Claude, Perplexity, Cursor, Notion AI, and more, depending on the task. This builds two cultural assets we prize:
Model Sense: Knowing which model suits which job. You'll hear our people say, "I used Gemini 3 Pro to do the analysis but switched to 4.5 Opus to write the output" — not just "I asked AI."
Product Taste: By using cutting-edge tools daily, we develop sharp intuition for what great AI experiences feel like — insight that feeds directly into the products we build.
Governance that accelerates
Our Legal, Cybersecurity, and Procurement teams don't exist to slow things down. We created clear policies and formed AI review committees so teams can experiment safely and move fast.
Learning and Support
We don't expect anyone to figure this out alone. Succeeding at AI transformation will require teamwork and continuous learning, and we learn best together:
AI Champions
Every function has designated AI Champions whose job is to experiment, discover what works, and support their teammates’ use of AI. They're listeners as much as teachers — tuned in to real problems and ready to help solve them.
Continuous upskilling
We run regular training sessions — from prompt engineering to building custom agents — and curate a shared toolkit so everyone has access to the right resources. There’s also a L&D budget you can use for courses and certifications from outside the company.
A culture of experimentation
Trying something new is encouraged; waiting for permission is not. We learn by doing, and we share our wins (and failures) with radical candor.
AI in Action
Engineering
Automated code-review agents are embedded in our pull-request workflows, catching routine issues so senior engineers can focus on architecture and design.
IT & Operations
We've deployed agents that autonomously resolve internal help-desk tickets and keep knowledge bases up to date.
Procurement
Deep Research agents handle preliminary due diligence. What once meant slogging through vendors’ privacy policies and security reports now takes minutes, letting humans focus on negotiation and strategy.
Meetings
Many teams follow a simple rule: "If a meeting wasn't transcribed, it didn't happen." AI captures and summarises our conversations so participants can be fully present.
Transparency
We practise what we call one-liners — a short note at the end of any deliverable explaining how AI was used.
