Build & submit taskBetabeginner

Ship Your First Change with Claude Code

Drive one real change end to end in Claude Code: pull a tiny journal app with a stubbed search feature and two failing tests, hand the agent the goal, and watch it gather, act, and verify until the suite is green. A local self-check proves the run happened for real, and you submit the code, the machine-generated evidence, and a short trace of the loop for instant, rubric-based feedback.

45 min

Est. time

3

Outcomes

5

Rubric criteria

55%

Pass score

What you'll learn

Skills you'll have real reps in after shipping this.

The agent loop is three literal phases you can point to in a transcript: gather (reading store.py and the failing tests), act (the edit), verify (the test run).
Red tests are the cleanest goal you can hand an agent: they define done, and the agent can check itself against them without asking you.
A job that ends in a change something must execute belongs in Claude Code, and a job that ends in words belongs in Chat, whatever the difficulty of either.

The scenario

You just installed Claude Code and you want to feel the loop for yourself instead of reading about it. The fastest way to internalize an agent is to hand it a small, self-contained goal that ends in a verifiable change, then watch it gather context, act, and check its own work.

This kit is that goal, prepared for you. tinylog is a tiny journal CLI where add and list work and search is a stub that raises NotImplementedError; two red tests describe exactly what search should do. You open Claude Code in the folder, give it the goal, and let it drive. You write none of the implementation yourself: your job is to steer, watch the loop close, and capture where each phase happened. A local self-check re-runs the suite and writes your proof-of-work evidence only when the feature genuinely works.

Your role

You are a developer running Claude Code for the first time. Your deliverable is the feature it built under your direction (a working search plus six green tests), machine-generated evidence of the passing run, and a short trace showing the gather, act, and verify phases in your own session, packaged as a single submission.

Start the task to unlock the full brief

You'll get the step-by-step requirements, setup commands, the 5-criterion grading rubric, tips, and the ability to submit your solution for instant AI grading.

Free to start · submit when you're ready

Run your first real Claude Code session, hands-on

This is the fastest way to feel how Claude Code actually works: pull a tiny journal CLI with a stubbed-out search feature and two failing tests, open Claude Code in the folder, and hand it the goal. You watch the agent gather context, edit the code, and run the test suite, then you trace the gather, act, and verify phases in your own transcript, so the agent loop stops being a diagram and becomes something you have driven. A local self-check keeps the whole thing honest: it re-runs the suite, confirms the spec tests are untouched, and writes your proof-of-work evidence only when the feature genuinely works. It is the first boss project in Preporato's hands-on Claude Code course.

Frequently asked questions

Do I need to be an experienced developer to do this?

No. The kit is a small, readable Python app, the goal fits in one sentence, and Claude Code writes the implementation while you set the goal and steer. You need Claude Code installed and Python 3 to run the tests and the self-check; everything is standard library, so there is nothing to install.

What exactly do I submit?

One zip the CLI builds for you: the tinylog app with search implemented, the kit's unmodified test file, the evidence file check.py generates when all six tests pass, and session.md, your short trace of the session with three moments labeled GATHER, ACT, and VERIFY plus two sentences on why this was a Claude Code job.

Can I fake the evidence or just write the code myself?

The evidence is generated by check.py re-running the real test suite, and the grader cross-checks it against your submitted code: the canary token, the verbose unittest output, and a hash check that the spec tests are untouched. Hand-written evidence over a still-stubbed search will not hold up, and the rubric also grades your session trace, which is where driving the agent shows.