Foundations of LLM-Assisted Code Review
How transformer models process Solidity — strengths and blind spots · Prompt engineering patterns for security review (few-shot, chain-of-thought) · Setting up a reproducible AI-audit workbench
- 01Understand and apply: How transformer models process Solidity — strengths and blind spots
- 02Understand and apply: Prompt engineering patterns for security review (few-shot, chain-of-thought)
- 03Understand and apply: Setting up a reproducible AI-audit workbench
How transformer models process Solidity — strengths and blind spots
This section covers how transformer models process solidity — strengths and blind spots. Content for this lesson is being developed by our practitioner team and will be available when the program launches.
Prompt engineering patterns for security review (few-shot, chain-of-thought)
This section covers prompt engineering patterns for security review (few-shot, chain-of-thought). Content for this lesson is being developed by our practitioner team and will be available when the program launches.
Setting up a reproducible AI-audit workbench
This section covers setting up a reproducible ai-audit workbench. Content for this lesson is being developed by our practitioner team and will be available when the program launches.
- 01Complete the hands-on lab for foundations of llm-assisted code review.
- 02Review the provided case study and answer the reflection questions.
- ✓How transformer models process Solidity — strengths and blind spots
- ✓Prompt engineering patterns for security review (few-shot, chain-of-thought)
- ✓Setting up a reproducible AI-audit workbench