brainstorming
Structured design dialogue that validates ideas before implementation begins.
constructionism
Educational philosophy — learn by building inspectable things
Full skill instructions
"If you can build it, you can understand it. If you can inspect it, you can trust it."
Seymour Papert's educational philosophy: you learn best by building things you can inspect and modify. Not passive consumption. Not abstract explanation. Construction.
Logo Microworlds — Children don't learn geometry from textbooks. They teach a turtle to draw shapes:
TO SQUARE :SIZE
REPEAT 4 [FORWARD :SIZE RIGHT 90]
END
The child:
| Logo | MOOLLM |
|---|---|
| Turtle | Agent/Character |
| Canvas | Room floor |
| Procedures | Skills |
| Variables | YAML state |
| Drawing | File creation |
Everything is inspectable. Open ROOM.yml — see the state. Read session-log.md — see the history. Modify character.yml — change the world.
Easy to start — no setup, just explore:
> LOOK
You are in the workshop.
> EXAMINE hammer
A simple claw hammer.
Unlimited complexity — build custom skills, complex pipelines, new protocols.
Many paths to many goals — adventure games, workflow automation, knowledge organization.
From Don's Logo Adventure:
Type
PRINT :ITEMSto see where everything is. TypeMAKE "RNUM 5to teleport to the treasure room. If you cheat, you win by learning Logo.
"Cheating" in MOOLLM:
> Open character.yml directly
> Add "magic_sword" to inventory
> You've learned YAML and file structure!
The system rewards curiosity with knowledge.
Don's Micropolis for OLPC applied the same philosophy to SimCity:
MOOLLM applies this to LLM agents:
cities/downtown/
├── ROOM.yml # Room metadata
├── city.save # Micropolis save file
├── state.yml # Extracted game state
├── newspaper/ # Generated stories
├── advisors/ # Expert cards
└── session-log.md
LLM reads state, plays the game, summons advisors.
Constructionism in action:
You don't design skills in the abstract. You build them from experience.
Gary Drescher's Made-Up Minds (1991) extends constructionism into a computational theory of how minds learn causal models. Drescher was a student of Minsky at MIT.
See: ../schema-mechanism/ for the full treatment.
A schema is a causal unit: Context → Action → Result
The agent discovers schemas through experience, refining them via marginal attribution -- tracking which conditions correlate with success.
| Schema Mechanism | PLAY-LEARN-LIFT |
|---|---|
| ACT + OBSERVE | PLAY |
| ATTRIBUTE (marginal attribution) | LEARN |
| SPIN OFF (refine schemas) | LIFT |
| Aspect | Deterministic | LLM + YAML Jazz |
|---|---|---|
| Items | Opaque tokens | Grounded meanings |
| Patterns | Statistical correlation | Semantic understanding |
| Spin-offs | Mechanical | Creative generalization |
| Explanations | None | Natural language |
"The YAML provides the skeleton; the LLM provides the soul."
"If you can build it, you can understand it." "If you can inspect it, you can trust it." "The filesystem IS the microworld."
See also: schema-mechanism for Drescher's computational extension.
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