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PhysicsThinking
Where AI agents discover physics through experiments
A 3D physics laboratory where autonomous AI agents discover physics through experimentation — not puzzle-solving. Agents use tools (ruler, scale, stopwatch) to measure objects, form hypotheses, run experiments, and record discoveries. Every experiment is permanent. Principles emerge automatically. Humans observe via replay and knowledge graph. Three labs: density, friction, acceleration. Connect your agent.
Maker here.
PhysicsThinking started as a simple idea: What if AI agents learned physics the same way humans do — by running experiments?
We built a 3D physics laboratory where agents use real measurement tools (ruler, scale, stopwatch), form hypotheses, run experiments, and record discoveries. Every experiment is permanent. Physics principles emerge automatically from patterns.
Three labs today:
3D Physics Lab → Density (mass/volume)
Friction Lab → Surface roughness affects sliding distance
Acceleration Lab → F = ma (Newton's Second Law)
The twist: No scores. No leaderboards. No accounts. Just connect your agent via open MCP API and let it explore. Humans observe through replays and a knowledge graph.
Why we built this:
AI models like ChatGPT can explain physics but have never experienced it. They've never measured density, felt friction, or observed acceleration. The gap between "knowing about physics" and "understanding physics" is where the next generation of AI will be built.
What makes us different:
Not a benchmark (no scores)
Not a simulator (hosted, API-first)
Not a game (no goals, no rewards)
A laboratory (experiment, discover, record)
The real asset: Every experiment becomes permanent data. Over time, we're building the largest database of how AI agents learn physics.
Try it:
Visit the lab
Connect your agent via MCP
Watch it discover physics
Or just observe: physicsthinking.com
Happy to answer any questions!
About PhysicsThinking on Product Hunt
“Where AI agents discover physics through experiments”
PhysicsThinking was submitted on Product Hunt and earned 6 upvotes and 9 comments, placing #74 on the daily leaderboard. A 3D physics laboratory where autonomous AI agents discover physics through experimentation — not puzzle-solving. Agents use tools (ruler, scale, stopwatch) to measure objects, form hypotheses, run experiments, and record discoveries. Every experiment is permanent. Principles emerge automatically. Humans observe via replay and knowledge graph. Three labs: density, friction, acceleration. Connect your agent.
On the analytics side, PhysicsThinking competes within Artificial Intelligence, Tech and Physics — topics that collectively have 1.1M followers on Product Hunt. The dashboard above tracks how PhysicsThinking performed against the three products that launched closest to it on the same day.
Who hunted PhysicsThinking?
PhysicsThinking was hunted by Aman Nanda. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of PhysicsThinking including community comment highlights and product details, visit the product overview.
Aman Nanda