Course · 8 lessons · personal, Jarvis, and company
Cultivated AI: stop repeating the same correction and make your agent get better every week
The model arrives ready-made, and it's the same one your competitor has. What improves is the garden around it: role, context, rules, examples, memory, evaluation, and feedback. In eight lessons you build the five files that cultivate, close the loop with the failure log, and decide the agent's autonomy by the numbers.
- 8elements of cultivation
- 5text files that cultivate
- 4levels of autonomy, raised by evidence
- 20 minper weekly review
The lessons
Concept, the files, three gardens (personal life, Jarvis, and company), the evaluation cycle, and autonomy by evidence. Each lesson has a practice with "done when" and a commented test.
Lesson 1 · 14 minThe seed and the garden: why AI is cultivatedNobody writes, line by line, a model's ability to code or plan. The labs create the conditions and the abilities emerge. You do the same on a different scale: the model arrives ready-made, and what you cultivate is the environment around it.
Lesson 2 · 18 minThe eight elements and the five files that cultivateEvery agent, whether it's your personal assistant or a sales agent, is cultivated with the same eight ingredients. And all cultivation fits into five text files that you copy, fill in, and review every week.
Lesson 3 · 15 minThe maturity ladder: what is and isn't cultivated AINot every AI with memory is cultivated, and not every agent is cultivated. Most of what is called AI today operates on the first two steps. The difference between the steps is not the model: it's what exists around it.
Lesson 4 · 15 minFirst garden: personal lifeMost people use AI as a question machine: open it, ask, copy, close. It's like hiring a brilliant consultant and wiping their memory every morning. In personal life, cultivation is cheap: three or four text files and twenty minutes a week.
Lesson 5 · 18 minSecond garden: your JarvisJarvis is the popular name for the agentic personal assistant: an AI that acts in your environment, reads and writes files, manages your calendar, runs commands. People install the tool and expect it to come ready. The model comes ready. Jarvis is cultivated.
Lesson 6 · 17 minClosing the loop: failure log and observabilityWhat isn't observed isn't cultivated. This lesson follows a clinic front-desk agent from its first error to supervised autonomy, and shows the minimum you need to record to replace "I think it got better" with "it improved from 88% to 95%".
Lesson 7 · 16 minAutonomy by evidence, not by trustThe temptation is to grant autonomy early: the answers look good and someone says "just let it run on its own." It's like promoting the intern on day two because they asked a good question. This lesson gives you the four levels, the numbers to move up, and the way back.
Lesson 8 · 18 minThe third garden: the company, and your planIn a company, to cultivate is to stop treating AI as software you program and start treating it as a capability the organization develops. When projects fail, the reason is rarely the model: it's a lack of context, process, and feedback. This lesson closes the course with a dated plan.
Who it's for
- 1People who use AI every day and are tired of explaining the same thing every week.
- 2People who built (or want to build) a personal assistant, a Jarvis, and expect it to improve.
- 3Managers who are about to put the first agent into a company process.
What you'll be able to do
- 1Describe any agent through the eight elements and write its agent profile.
- 2Keep a failure log and a weekly review: the correction goes into the file, not into the chat.
- 3Measure accuracy by sampling and decide whether to raise or lower autonomy using numbers.
- 4Leave with a dated plan for 30 days (personal) or 90 days (company).