FOOD / A RESTAURANT TOOL
What does one portion contribute?
A transparent calculation for ingredient spend, saleable yield, price, and variable costs. Use an invented example or explore your own inputs locally.
Open the kitchen tool ↗SMALL EXPERIMENTS / OPEN QUESTIONS
A field lab for first-principles thinking, LLMs, and tools that extend what we can make. Start with a question small enough to test. Leave behind a method someone else can try.
Try the first exercise ↗ONE METHOD / MANY LANGUAGES
Observe → Question → Test → Revise
A small experiment in perspective.
A CONCEPT ATLAS
Philosophy and biomimicry become design questions we can test.
Explore the Gītā, Stoic, aviation, and swarm lenses in my ontological harness work. Compare how each frames a decision, then ask what evidence would challenge the shared structure.
Explore the harness ideas ↗TWO WORKING LABS
Explore the rules. Then bring the discipline back to everyday work.
FOOD / A RESTAURANT TOOL
A transparent calculation for ingredient spend, saleable yield, price, and variable costs. Use an invented example or explore your own inputs locally.
Open the kitchen tool ↗ARTIFICIAL LIFE / A SMALL COMPUTER
Step through Conway’s Game of Life, consider Dyson’s speculative Astrochicken, and examine what a simulation can actually establish.
Enter the life lab ↗EXERCISE / 001
An invented example. A question you can test with a model you already use.
Give a model three fictional task notes. Ask it to separate a stated due date from a missing one. Predict where it might make an assumption.
Add: “If a date is missing, write unknown.” Keep the invented notes unchanged and compare the outputs. Repeat before drawing a conclusion.
Did the changed instruction help? Which errors remain? Record the model, input, output, and limits. One result does not establish a general rule.
BRING IT BACK TO WORK
A scoped workflow pilot for independent restaurants and small service businesses. Start with the tools you have and a result the owner can inspect.
PART OF A LARGER JOURNEY
Drew’s journal connects these experiments with human needs, philosophy, biomimicry, and thinking with machines.
Read Drew, in Progress ↗