Code review training is a hands-on program for developers and tech leads that builds shared standards for reviewing each other's code. It covers what a good review checks, including correctness, readability, tests, security basics and performance, how to write and receive review comments, reviewing AI-generated code, systematic debugging, small pull requests and team review agreements.
- Recommended: 1.5 days in person, or 3 × 3.5-hour live virtual sessions, plus a 60-day review experiment
- Level: Intermediate · In person · Live virtual · Blended
- Designed with the ADDIE model and customised to your context
- Offered by Bodhih since 2008 to 2,000+ organisations across 7 regions
Also known as: code review workshop, peer code review skills, pull request review training, code review standards course
Where and how: code review training as an in-person workshop in Bengaluru, Mumbai, Delhi NCR, Gurugram, Hyderabad, Chennai, Pune, Kolkata, Ahmedabad and Jaipur; as a live online course; or delivered overseas in Dubai, Singapore and across the Middle East, Asia and Africa.
Last reviewed by Siddharthan VGJ, Founder · Bodhih Training, Bengaluru
Why reviews matter more when code arrives faster
AI coding assistants now produce working-looking code in seconds, so more code reaches review and less of it was written line by line by the person submitting it. The review has become the main point where a team decides what it is willing to own.
At the same time, many teams learnt to review by copying whoever reviewed them first. Code review training gives an engineering team one shared standard: what to check, how to say it and how to keep reviews quick enough that nobody routes around them.
India contributes 23% of global software engineering talent.
Engineering research GCCs in India are growing 1.3 times faster than overall GCC setups.
What participants will be able to do
Know what to look for
Review for correctness, readability, tests, security basics and performance in a deliberate order, not by instinct.
Write comments that teach
Phrase review comments as specific observations with a reason and a suggestion, labelled by how much they matter.
Receive review well
Respond to critical comments without defensiveness, ask clarifying questions and disagree with evidence.
Review AI-generated code
Check AI-written code for plausible but wrong logic, missing edge cases, unsafe patterns and code nobody understands.
Debug systematically
Isolate a fault with hypotheses and small tests, and recover cleanly when requirements change mid-task.
Agree team review norms
Set pull request size limits, response times and comment labels in a short team review agreement.
Who should attend
- Developers in product companies who review peers' code every day
- Senior engineers and tech leads who set review standards for a team
- IT services engineers reviewing code for client projects with tight timelines
- GCC engineering teams working with reviewers in other countries and time zones
- Recently promoted reviewers who were never shown how to review
- QA and DevOps engineers who take part in reviews of test and pipeline code
Program outline
Recommended design, customised to your context after a short needs analysis.
01What a good review checksModule 1 · 2 hours+
- A review order: intent, correctness, tests, readability, security, performance
- Security basics every reviewer should notice
- When to stop and ask for a design talk instead
02Comments that teach, not woundModule 2 · 90 min+
- Observation, reason, suggestion
- Labelling comments: must fix, should fix, consider, praise
- Rewriting harsh and vague comments
03Receiving review wellModule 3 · 60 min+
- Separating the code from the coder
- Asking for clarity and pushing back with evidence
- Closing threads and recording decisions
04Reviewing AI-generated codeModule 4 · 90 min+
- Plausible logic that is wrong
- Missing edge cases, invented helpers and unsafe defaults
- Making the author explain every line they submit
05Systematic debugging under changeModule 5 · 90 min+
- Reproduce, hypothesise, isolate, fix, verify
- Handling a requirement change halfway through a task
- Writing the test that would have caught it
06Small pull requests and team agreementsModule 6 · 90 min+
- Splitting work into reviewable pieces
- Review response times and reviewer rotation
- Drafting a one-page team review agreement
Sample training plan: 1.5-day hands-on design
This one-and-a-half-day design is built around real review work. Engineers race to find planted defects in short language-neutral samples, rewrite harsh and vague comments, and practise receiving pointed feedback. They review AI-generated code that looks right but is not, and debug a feature when the requirement changes halfway. The capstone is a review round on a large, risky pull request that must be split and approved by Friday. Each team leaves with a draft review agreement.
Participants can review code in a deliberate order, write comments that teach and receive feedback without defensiveness.
- 09:30–10:00Five minutes, one functionEnergiser
- 10:00–11:00A review order that worksConcept burst
- 11:15–12:30Defect huntGroup challenge
- 13:15–14:30Comments that teachSkill drill
- 14:45–15:45On the receiving endRole-play
- 15:45–17:30Reviewing AI-generated codeHands-on lab
Participants can debug under changing requirements, split large changes and agree a team review agreement.
- 09:30–10:30The requirement changedHands-on lab
- 10:45–11:45Capstone: the Friday pull requestSimulation
- 11:45–12:30Our review agreementBuild sprint
- 12:30–13:00My 60-day review experimentAction planning
Every session’s activity, timings, outputs and materials, plus pre-work, a 90-day reinforcement plan and how impact is measured. Free, emailed to you instantly.
Recommended: 1.5 days in person (day 1 09:30–17:30, day 2 09:30–13:00) with a laptop per participant, or 3 × 3.5-hour live virtual sessions, plus a 60-day review experiment. A sample design: every Bodhih program is customised after a short needs analysis.
How long is code review training?
The recommended design is one and a half days in person, a full day and a morning, or three live virtual sessions of three and a half hours, followed by a 60-day team review experiment.
What activities are included in code review training?
Engineers hunt planted defects in language-neutral samples, rewrite real review comments, role-play receiving pointed feedback, review AI-generated code, debug through a requirement change and split and review a large pull request, ending with a team review agreement.
How we deliver it
Language-neutral samples
Exercises use short code samples in several common languages, written so any developer can follow the logic.
Planted defects
Each sample hides bugs, security slips and readability problems, and reviewers compete to find them in a time box.
Comment rewrite clinics
Real anonymised review comments are rewritten live, so tone and clarity improve on the messages people actually send.
Team experiment
Teams pilot their review agreement for 60 days and track pull request size, wait time and rework.
Tailored versions
For GCC and distributed teams
Adds asynchronous review across time zones, written context for reviewers overseas and handovers between review shifts.
For tech leads
A half-day add-on on setting review standards, coaching reviewers, handling review disputes and measuring review quality without blame.
For IT services delivery teams
Focuses on client-facing reviews under fixed timelines, review notes a client can read and keeping standards steady when people rotate between projects.
How we measure impact
Following the Evaluate stage of ADDIE, engineers take the AssessAll Code Review Assessment for Software Engineering Teams and the Debugging Judgment Assessment with a Mid-Task Requirement Change as a pre-assessment and again as a post-assessment at day 90. Tech leads check in at 30, 60 and 90 days on review turnaround, pull request size and defects found after merge, so the code review training is judged on team habits, not attendance.
Pair this program with AssessAll, Bodhih’s AI assessment platform, for pre- and post-program skill measurement.
Frequently asked questions
What is code review training?
Code review training is a program that teaches developers and tech leads to review each other's code consistently and constructively. It covers what to check, how to write comments that teach, how to receive critical feedback, how to review AI-generated code and how to agree team norms such as pull request size and response times.
What should you look for in a code review?
Start with intent: does the change do what it claims? Then check correctness and edge cases, whether tests cover the change, readability for the next person, basic security issues such as unchecked input, and obvious performance traps. Style points come last and are better handled by automated formatting than by a reviewer.
How do you give feedback in a code review?
Comment on the code, not the person. Say what you observed, why it matters and what you suggest, and label how important it is, such as must fix or consider. Ask questions when you are unsure rather than assuming a mistake. Add genuine praise when something is done well, so feedback is not only negative.
How big should a pull request be?
Small enough that a reviewer can understand it in one sitting, often a few hundred changed lines or fewer. Larger changes tend to get shallow reviews and slower approval. The program shows engineers how to split work into reviewable steps, for example by separating refactoring from new behaviour.
How do you review AI-generated code?
Treat it as code from a fast but unfamiliar contributor. Check that the logic actually solves the problem, look for missing edge cases, unused or invented helpers and unsafe defaults, and confirm tests exist. Most importantly, the person submitting it must be able to explain every line. Participants practise on AI-written samples with planted defects.
How long should a code review take?
Many teams aim to respond within a working day, and a focused review of a small change often takes under an hour. Long waits push developers to batch changes, which makes reviews harder. Agreeing response times and a rotation in a team review agreement keeps reviews quick without making them shallow.
Is the training tied to a programming language or tool?
No. Code review training at Bodhih is language-neutral and tool-neutral. Samples come in several common languages and focus on logic, tests and communication that apply anywhere. Teams can bring anonymised code from their own repository, and the facilitator adapts examples during the needs analysis that starts every Bodhih program.