jensen-way

Jensen Way

A physics-of-reality decision framework for AI coding assistants. Tests whether a product, feature, or spec obeys reality before you commit engineering time — and produces a defensible Build / Pivot / Kill verdict backed by evidence.

"The next wave requires us to understand things like the laws of physics — friction, inertia, cause and effect. The fact that I tip that thing over, it's going to fall. When I set the bottle down, it's not going to go through the table. All of these common sense physical reasoning abilities that children have, that our pets have — most AIs don't have."

— Jensen Huang, Hill & Valley Forum 2025, interviewed by Jacob Helberg, May 3, 2025

Jensen was describing Physical AI — the next wave after perception, generative, and agentic AI. We noticed the same observation applies to most product plans: they operate in a frictionless vacuum where users adopt because you ship, teams align because you scheduled a meeting, and systems scale because the architecture diagram says so.

Jensen Way ports that insight to product decisions. A child shouldn't need equations to follow your causal chain — if they can't, the physics are probably against you.

Install

/plugin marketplace add agentoptics/jensen-way

Or drop the single-file skill into your project:

mkdir -p .claude/skills/jensen-way
curl -o .claude/skills/jensen-way/SKILL.md \
  https://raw.githubusercontent.com/agentoptics/jensen-way/main/skills/jensen-way/SKILL.md

Then:

/jensen-way Should we add real-time collaboration to our docs product?

What you get back

1. A framed decision (what, why, time horizon)
2. A causal chain from "we build it" to "it matters" — with weak links marked
3. Evidence-backed evaluation against 6 laws of reality
4. A friction budget — force available vs. friction total
5. A verdict: BUILD / PIVOT / KILL with the single biggest risk named

See EXAMPLES.md for two worked evaluations — one PIVOT, one KILL.

The 6 laws

#	Law	The toddler version
1	Gravity of demand	"Do people actually want this, or do you just wish they did?"
2	Friction of adoption	"Is this solving something that hurts, or just something slightly annoying?"
3	Competitive gravity	"If someone bigger takes your toy, can you get it back?"
4	Hard constraints (the table test)	"What's the thing that absolutely cannot happen no matter how hard you try?"
5	Organizational inertia (Conway's Law)	"Do the people who need to work together actually talk to each other?"
6	Entropy & economics	"If you stop paying attention to this, does it break? Is it worth the effort?"

Each law scores Aligned / Fighting / Broken.

• BUILD — no Broken, at most 2 Fighting with named mitigations, friction budget positive
• PIVOT — 1-2 Broken that dissolve if scope / approach / timeline changes
• KILL — 3+ Broken, OR Broken on Demand Gravity, OR friction budget deeply negative

Example prompts

/jensen-way Should we add AI-powered search to our documentation platform?

/jensen-way We're deciding between building our own auth vs. using Auth0. Evaluate both.

/jensen-way Our PM wants to ship a mobile app in 6 weeks. 3-person team, no mobile experience. We all have a 100$ budget per month for AI assistance. Feasible?

/jensen-way Fork an open-source project and maintain our own version, or contribute upstream?

Philosophy

Most product failures aren't caused by bad engineering — they're caused by ignoring physics:

• Building something nobody wants (ignoring demand gravity)
• Underestimating how hard it is to change user behavior (ignoring friction)
• Assuming teams will coordinate perfectly (ignoring organizational inertia)
• Planning for the happy path only (ignoring entropy)
• Not knowing what can't be done (ignoring hard constraints)

A child wouldn't make these mistakes. They have an intuitive understanding of cause and effect, friction, and hard limits. Jensen Way brings that intuition to product decisions — with evidence attached.

Works with any AI assistant

The framework is in a single Markdown file: skills/jensen-way/SKILL.md. Model-agnostic. Copy it into your system prompt, paste it into a conversation, or reference it as a project file. It works with any assistant that can follow a structured workflow.

Contributing

Issues and PRs welcome. If you've used Jensen Way to make a decision (build or kill), open an issue — real-world runs make the framework better.

License

MIT

Credits

Built by Agent Optics. The physics framing is drawn directly from Jensen Huang's Hill & Valley Forum 2025 remarks on Physical AI. The extension from Physical AI to product decisions is ours.