AI-Native Thinking: Lessons from the Tech & Society Conference
Reflections on API readiness, evals, experimentation, and psychological safety from a UCLA Anderson Easton Technology Management Center session on AI-native organizations.
A session hosted by the UCLA Anderson Easton Technology Management Center featuring Raghvender Arni, Arun Rao, and Deborah Liu explored how AI-native thinking is reshaping leadership, product management, and organizational culture.
Key takeaways
1. API-first mindset
Digital readiness isn’t optional anymore. If your business isn’t built for AI integration or doesn’t have the necessary APIs for agents to consume, it will increasingly fall behind.
2. Evals are the new KPIs for data PMs
Knowing how to measure model reliability and when a job is truly done is becoming a critical product skill.
3. Jump into the pool
Don’t just use AI for queries. Experiment with agentic tools, automate workflows, and prototype with intention.
4. Psychological safety fuels innovation
When teams feel safe voicing half-formed ideas, critique turns into creativity. Great cultures make curiosity safe.
As someone exploring the intersection of AI and product strategy, sessions like these are a reminder that transformation isn’t about replacing people. It’s about retraining how we think, lead, and build as we augment ourselves with AI.
