| --- |
| license: mit |
| language: |
| - en |
| tags: |
| - 3d-printing |
| - additive-manufacturing |
| - llm |
| - retrieval |
| - build-small-hackathon |
| pretty_name: "Microfactory Node: Lesson Ledger" |
| size_categories: |
| - n<1K |
| --- |
| |
| # Microfactory Node: 3D Printer (Lesson Ledger) |
|
|
| The compounding memory of **Microfactory Node: 3D Printer**, a small local Gemma that learns 3D |
| printing job by job. Each row is one durable lesson keyed to the conditions it was learned in. |
| The node retrieves from this ledger before every print, so job N+1 starts smarter than job N. |
| This is the knowledge that usually lives in one maker's head and dies with the shop. Here it |
| persists, and anyone can read it. |
|
|
| Project: [Live](https://node.microfactory.space) · |
| [Code](https://github.com/kylebrodeur/microfactory-node). |
|
|
| ## Schema (one JSON object per line) |
|
|
| ```json |
| {"job_id": "seed-004", "material": "PLA", "geometry_type": "overhang", |
| "env_temp": 28.0, "env_humidity": 50.0, "outcome": "failed_sag", |
| "lesson": "PLA overhang sagged at 28C with the fan low; raise cooling, drop nozzle ~10C.", |
| "source": "seed", "timestamp": "2026-05-20T09:00:00Z"} |
| ``` |
|
|
| | Field | Meaning | |
| |---|---| |
| | `material` | PLA, PETG, ABS, TPU | |
| | `geometry_type` | overhang, bridge, stringing, adhesion, vase (the failure-mode class) | |
| | `env_temp` / `env_humidity` | room conditions the lesson was learned in | |
| | `outcome` | success, failed_sag, failed_stringing | |
| | `lesson` | one durable, directional sentence (the transferable craft) | |
| | `source` | `seed` (curated start), `ingested` (from real configs/prints), `earned` (a real reported outcome), `sim` (the deterministic world) | |
|
|
| ## How the knowledge is sourced |
|
|
| Lessons are grounded, never invented. Seed lessons are hand-curated starters. Ingested lessons |
| come from real slicer/firmware profiles and real print history. Earned and simulated lessons come |
| from outcomes reported outside the model: the model proposes, a deterministic world or a human |
| reports what happened, and only then is a lesson written. The model never grades its own work. |
|
|
| ## Honest limits |
|
|
| Small and deliberately so. The simulated outcomes are a physics-lite stand-in for a printer, used |
| to run the closed loop on camera; they are labeled as such. Treat the lessons as a maker's |
| notebook: directionally true, condition-keyed, and meant to be checked against your own machine. |
|
|
