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Course contents

  • Getting Started with AI for VLSI Engineers5
  • Just Enough AI: Models and Context15
  • Prompting13
  • Trust and Verification14
  • Using AI for Engineering Work17
  • Engineering Walkthroughs7
  • Practical Foundations for AI Workflows4
    • APIs: Requests, Responses and Errors
    • JSON Records and Meaningful Validation
    • Repositories, Diffs and Isolated Changes
    • Working with Waveforms and Report Images
  • Engineering Data5
  • Retrieval-Augmented Generation6
  • Agents and Tool Use18
  • Agent Design8
  • MCP and Skills6
  • Multi-Agent Design6
  • Practical Capstone6
  • Tokens, Cost and Latency12
  • Agentic Workflows for Chip Teams18
  • Interview and Judgment10
  • AI Skills: Full Course Index
  • Working with AI Glossary
  • Working with AI Cheatsheet
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‹AI Skills for VLSI Engineers
  1. Topics
  2. AI Skills for VLSI Engineers
  3. Practical Foundations for AI Workflows

Practical foundations · Beginner

Practical Foundations for AI Workflows

APIs, JSON, repository changes and visual evidence without a software-infrastructure detour.

  • 4topics
  • 4lessons

You do not need to become a backend developer to build a small engineering assistant. You do need to recognise what crosses an API boundary, validate a record, inspect a proposed change and check a screenshot against its source. These short lessons connect the earlier prompting exercises to the later data and agent labs.

Lesson

Artifact

APIs: Requests, Responses and Errors

A worked decision, an exercise and an independent check.

JSON Records and Meaningful Validation

A worked decision, an exercise and an independent check.

Repositories, Diffs and Isolated Changes

A worked decision, an exercise and an independent check.

Working with Waveforms and Report Images

A worked decision, an exercise and an independent check.

Tip

All examples use synthetic data. No live service or credential is required. Your organisation decides which real services, files and jobs may be used.

Related topics

  • Small scripts and dry runs

  • Next: engineering data

PreviousNext: APIs: Requests, Responses and Errors

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See also

  • Getting Started with AI for VLSI Engineers
  • Just Enough AI: Models and Context
  • Prompting