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zuzu.codes uses a structured 30-day track format with dialogue-based teaching, an in-browser code editor, and gamification (XP, streaks, progress tracking). The format builds genuine understanding through daily practice.

Day 30 · ~11 min●

Thirty days ago you rated yourself on six AI skills. Today you rate yourself again — same six, same scale. Then you see the gap.

I ran the capstone this morning. Gave it a research question. It pulled 5 recent papers via Perplexity, extracted a structured finding from each — claim, authors, year, journal — and returned a markdown mini-review grouped by year. That's a methods section, automatically.

That agent used search, structured extraction, and formatting in one chain. Three weeks ago you were reading 40 abstracts manually over a weekend. Today that same coverage takes two minutes.

I want to see the Day 1 delta.

Same six rows. Rate honestly where you are today. The chart shows both ratings side by side — the gap between Day 1 and now is yours to defend in a methods section: "AI-assisted literature triage using a structured extraction pipeline."

A reviewer asked how I found the non-English papers I cited. I sent them the script.

A reproducible AI pipeline is a citation in itself. That's the point of the whole track.

What you built

30 days, 20 AI lessons, 1 literature summariser agent.

From first agent to full research pipeline

Week 1 — First agent, system prompts, classification — summarising one abstract in two sentences
Week 2 — Structured output, Pydantic extraction — extracting claim, authors, year, journal from a paragraph
Week 3 — Pipelines, batch processing — classifying 50 open-text survey responses in one loop
Week 4 — Web search, tools, capstone — the full AI mini-review agent on a live research question

What the chart shows

Column	Meaning
Left bar	Day 1 self-rating
Right bar	Today's rating
Gap	Real, measurable growth

You've completed the researchers trio. Python gave you reproducible analysis. Automation gave you pipelines that run themselves. AI gives you literature at the speed of the field.

Sign up to practice

Create a free account to get started. Paid plans unlock all tracks.

Day 30 · ~11 min●

Thirty days ago you rated yourself on six AI skills. Today you rate yourself again — same six, same scale. Then you see the gap.

That agent used search, structured extraction, and formatting in one chain. Three weeks ago you were reading 40 abstracts manually over a weekend. Today that same coverage takes two minutes.

I want to see the Day 1 delta.

A reviewer asked how I found the non-English papers I cited. I sent them the script.

A reproducible AI pipeline is a citation in itself. That's the point of the whole track.

What you built

30 days, 20 AI lessons, 1 literature summariser agent.

From first agent to full research pipeline

Week 1 — First agent, system prompts, classification — summarising one abstract in two sentences
Week 2 — Structured output, Pydantic extraction — extracting claim, authors, year, journal from a paragraph
Week 3 — Pipelines, batch processing — classifying 50 open-text survey responses in one loop
Week 4 — Web search, tools, capstone — the full AI mini-review agent on a live research question

What the chart shows

Column	Meaning
Left bar	Day 1 self-rating
Right bar	Today's rating
Gap	Real, measurable growth

You've completed the researchers trio. Python gave you reproducible analysis. Automation gave you pipelines that run themselves. AI gives you literature at the speed of the field.

What you built

30 days, 20 AI lessons, 1 literature summariser agent.

From first agent to full research pipeline

Week 1 — First agent, system prompts, classification — summarising one abstract in two sentences

Week 2 — Structured output, Pydantic extraction — extracting claim, authors, year, journal from a paragraph

Week 3 — Pipelines, batch processing — classifying 50 open-text survey responses in one loop

Week 4 — Web search, tools, capstone — the full AI mini-review agent on a live research question

What the chart shows

Column	Meaning
Left bar	Day 1 self-rating
Right bar	Today's rating
Gap	Real, measurable growth

You've completed the researchers trio. Python gave you reproducible analysis. Automation gave you pipelines that run themselves. AI gives you literature at the speed of the field.

What you built

30 days, 20 AI lessons, 1 literature summariser agent.

From first agent to full research pipeline

Week 1 — First agent, system prompts, classification — summarising one abstract in two sentences

Week 2 — Structured output, Pydantic extraction — extracting claim, authors, year, journal from a paragraph

Week 3 — Pipelines, batch processing — classifying 50 open-text survey responses in one loop

Week 4 — Web search, tools, capstone — the full AI mini-review agent on a live research question

What the chart shows

Column	Meaning
Left bar	Day 1 self-rating
Right bar	Today's rating
Gap	Real, measurable growth

You've completed the researchers trio. Python gave you reproducible analysis. Automation gave you pipelines that run themselves. AI gives you literature at the speed of the field.