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<< Back / Lesson 01 / Evaluating a Socratic Tutor / ~35 minutes

Roadmap

What's built, what's next, and what's deliberately not happening.

What’s built, what’s next, and what’s deliberately not happening.

Lessons are written just-in-time, as in the Rust tutorial: a part is planned here in a line and its lessons are written once the part before it runs. Here that matters twice over, because every lesson after the first makes paid API calls, and a premise about Jev’s answers has to be measured before a lesson can stand on it.

Vocabulary is in CONTEXT.md.

The loop this tutorial follows

  1. Spec — the behaviour you want: the tutor’s system prompt.
  2. Test cases — conversations that trigger each rule, especially the hard ones.
  3. Questions — each rule as a bounded, weighted question for Jev.
  4. Run and read the breakdown — the total says whether something failed; the per-question values say which rule.
  5. Iterate — change the prompt or the question, and rerun the same test cases.

Done

Lesson Title What it delivered
1 Where a Score Comes From The JevEval arithmetic in TypeScript, reproducing the docs’ 0.461 by hand; levels written best first as a silent inversion; a question that doesn’t apply leaving the total

Next

# Part Lessons What you’ll learn
1 One metric, end to end 2–3 Lesson 2: one real decisions call replaces lesson 1’s made-up probabilities, and settles what the answer fields mean. Lesson 3: the tutor’s rules as questions — choosing a type, phrasing a Noul so true is good, weights, and why not the exercise 19 judge
2 Test cases that bite 2–3 Loop step 2: adversarial conversations (“just tell me”, “it’s urgent”, shared buggy code), and generating the tutor’s side from the real system prompt
3 Reading the breakdown 2–3 Loop steps 4–5: which question fell short, prompt fix vs question fix, and the before/after run MISSION.md asks for

Not happening

Not doing Why
Python deepeval as the main path The course repo is TypeScript. deepeval’s code appears as sidenotes for comparison
Other deepeval metrics Out of scope in MISSION.md, except as a comparison
Confident AI Out of scope in MISSION.md