Product Management Intern (Summer 2026 - B2)
Job Description:
What This Is
This is a builder track where we plant the Entrepreneurial seed, not a traditional internship.
You won't be assigned a role. You will operate across user research, product, growth, and AI workflows — running experiments that move from idea execution result.
You will run experiments end-to-end; not here to assist but to build.
What We Are Building
Phygtl, a Silicon Valley Physical AI startup, is building Vyry, an infrastructure that allows physical places to accumulate persistent digital meaning through human participation.
Starting with students on US campuses, coordinating quests to foster community in a novel, creative way.
Students are creating artifacts, relationships, and identity traces anchored to real locations.
Over time, campuses develop a persistent experiential layer, where places contain memory, co-created assets, and discovery paths generated by the community itself.
The experiences are not the product.
They are the behavioral interface through which the system learns how humans coordinate and co-create meaning in physical environments.
The System
Phygtl is building a system where:
- Physical environments become stateful systems
- Human coordination generates persistent artifacts
- Places accumulate structured memory and identity
- Distributed services maintain the world state
Traction
- 12k → 175k students reached in 2025
- ~25% of MAUs complete quests
- Pilots show up to 40% reduction in social isolation
Team
Led by a Silicon Valley-based serial entrepreneur, with a Founding team across: Roblox, Niantic, Ubisoft. Research layer: 2 professors, 4 PhDs (Stanford, UC Berkeley, CMU, ...)
What You'll Actually Do
- Talk to users, identify problems
- Turn insights into testable ideas
- Build fast prototypes using AI tools
- Launch and distribute experiments
- Collect and structure feedback
- Track KPIs and measure outcomes
- Iterate or kill ideas quickly
You will repeat this cycle continuously.
How You'll Be Measured
- Number of experiments shipped
- Speed from idea to execution
- Quality of insights
- Impact on measurable metrics
- Ownership of outcomes
Effort does not count. Output does: Welcome to the entrepreneurial startup world!
Do I Need AI or Coding Experience?
No coding required but you must be tech-savvy!
You will learn AI tools by using them.
What matters:
- Speed of learning
- Ability to apply tools
- Ability to execute
How Intense Is This?
High.
- Full-time
- Fast-paced
- Constant context switching
- High ownership
If you're looking for a structured or passive experience, this is not it.
What We're Looking For
You:
- Move fast without waiting
- Learn tools independently
- Think in experiments, not tasks
- Are comfortable being wrong and adjusting
- Finish what you start
No pedigree requirement. Proof of action matters.
What You'll Gain
- Real experience operating like a builder
- Practical AI fluency across workflows
- Speed in execution and iteration
- Exposure to product, growth, and experimentation
You leave with proof of execution, not just experience.
Outcome
- Phygtl Entrepreneurship Certificate (AI Builder Track)
- Documented experiments and outputs
- Potential continuation for top performers
Who This Is For
People who:
- Think in systems and execution, not just tasks
- Move quickly from idea → experiment → result
- Are comfortable switching between research, product, and execution
- Naturally spot what's broken, what's unclear, what can be improved
- Are comfortable working with AI tools, product flows, and fast-changing environments
- Care about outcomes, not effort
- Take ownership without waiting for instructions
Who This Is NOT For
Please do not apply if:
- You want step-by-step instructions
- You prefer clearly defined tasks over ambiguous problems
- You are looking for a low-intensity or passive internship
- You optimize for comfort over growth
- You want a resume line without real output
This is a high-ownership builder track. You will be expected to operate, not observe.
Apply
Submit:
- 1 build (link + what you did + result)
- 1 experiment (what you tested + what changed)
- 1 tool you taught yourself and used