AI Code Review Agent

6 Interactive Sessions

Short, interactive sessions: watch it work, try it, then build it yourself. You can go deeper at any time in the written chapters.

1. 1

   Reading a code change the way a reviewer does

   Before an agent can review a change, it has to turn the change from plain text into structure: which files, which lines were added or removed, which functions, and what kind of change it is.

2. 2

   Finding the problems without crying wolf

   Five detectors read the parsed code, each looking for one kind of problem. A good detector catches the real problems first, then cuts the false alarms that train people to ignore it.

3. 3

   Turning findings into a score you can act on

   Turn a pile of findings into four scores and a verdict. One overall number hides where a change is weak, so the verdict follows the weakest dimension.

4. 4

   Writing a review people can act on

   Turn findings into a review: a short summary, comments ranked by priority, and a suggested fix where one is safe. The agent comments and suggests. A person checks the fixes, decides and merges.

5. 5

   Putting the review where people will see it

   Give the review a home: a small web app with a dashboard of every PR, a review page with the comments, and a panel that shows which part of the pipeline produced each number.

6. 6

   Running the review on every pull request

   Make the review automatic. GitHub tells the agent each time a PR opens or changes, the agent reviews it, and posts a check that can stop the merge. Then measure whether the agent is right, so it keeps people's trust.

How this certificate is scored

Your certificate shows how many of your written answers met the rubric below, checked by an AI grader. Anyone who checks your certificate sees it.

• You answer 6 short questions, one for each module, in your own words (at least 40 words each).
• An AI grader checks each answer against what its module asks for: it must answer the question, use the course's practice case specifically, and be correct.
• To pass, at least 5 of the 6 answers must meet that bar. The certificate says the answers were graded by AI.

The rubric

1. Module 1, Code Parsing: Diff parsing + AST + symbol resolution.
2. Module 2, Issue Detection: Bug, security, anti-pattern detectors.
3. Module 3, Quality Scoring: Multi-dimensional scoring + trends.
4. Module 4, Review Generation: Inline comments + fix suggestions.
5. Module 5, Review App: Dashboard + diff viewer + quality gauge.
6. Module 6, Production Pipeline: GitHub webhook + CI/CD + feedback.

What you walk away with