Model Online / On-Site
Duration
Modules 5 modules

Course Objective & Scope

A coding agent can generate a 1,500-line pull request in under an hour, leaving senior engineers with an impossible choice: spend half a day untangling the diff or rubber-stamp it with 'LGTM' and risk a production outage. This course redesigns code review and human sign-off for high-velocity AI engineering teams.

Splitting work into small stacked PRs, running author-side AI self-review and evidence packaging, tuning automated PR review bots (Copilot Code Review, CodeRabbit, custom PR agents) for high signal and zero nitpick noise, reviewing large diffs systematically, and enforcing risk-tiered human approval gates are practised hands-on.

Who Should Attend?

  • Senior software engineers and pull-request reviewers
  • Tech leads and software architects
  • Engineering managers and DevEx/platform teams
  • Prerequisite: experience with Git pull-request workflows and team code reviews

Key Takeaways

  • Replace massive AI code dumps with small, logically sequenced stacked pull requests
  • Package PRs with architectural rationale, highlighted risk zones and verification evidence before requesting review
  • Configure AI PR review bots to suppress style nitpicks and focus on logic, concurrency and edge-case defects
  • Review AI-assisted diffs efficiently by following data flow and invariant boundaries rather than alphabetical file order
  • Implement risk-tiered human approval policies using CODEOWNERS and path/complexity rules

Curriculum

The Asymmetry Problem: Reviewing in Hours What AI Wrote in Minutes
  • Reviewer fatigue, rubber-stamping risks and cognitive load limits on diff size
  • Shifting the burden of proof from the reviewer back to the PR author
Author Discipline: Stacked PRs and Verification Evidence
  • Separating formatting, structural refactoring and behaviour changes into distinct PRs
  • Running local AI self-critique and attaching test, trace or screenshot evidence before requesting review
Tuning Automated AI PR Review Bots for High Signal
  • Writing repository-specific review instructions for Copilot Code Review, CodeRabbit or custom PR agents
  • Suppressing style nitpicks so automated comments only flag real logic, security or architectural bugs
AI-Assisted Review Techniques for Human Reviewers
  • Using an IDE agent to generate a call-flow walkthrough and interrogate implicit assumptions in a diff
  • Spotting silent behaviour shifts, breaking schema migrations and swallowed errors
Risk Tiering and Human-in-the-Loop Approval Gates
  • Differentiating approval rules for docs/tests, standard features and high-risk paths (auth, billing, DB migrations)
  • Configuring CODEOWNERS, branch protection gates and review-turnaround SLAs

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