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AI Career Skills Course
Module 5: AI For Coding
AI, Machine Learning and Generative AI Basics
LLMs, Tokens and Context Windows
Hallucinations, Confidence and AI Limitations
Clear Task Prompts and Output Formats
Context, Examples and Few-Shot Prompting
Prompt Debugging and Iteration
AI for Writing, Summaries and Emails
AI for Research and Meeting Notes
AI Automation for Routine Office Work
AI Study Planning and Concept Learning
AI Practice Questions and Feedback Loops
Using AI Responsibly in Assignments
AI for Code Explanation and Debugging
AI for Tests, Refactors and Code Review
AI Pair Programming Workflow
AI for Spreadsheet Cleanup and Analysis
Asking Better Data Questions
Chart, Insight and Decision Summaries
Embeddings and Semantic Search
RAG Workflows and Knowledge Bases
AI Agents, Tools and Automation
Privacy, Sensitive Data and Access Control
Bias, Fairness and Harmful Output Checks
Evaluating AI Answers Before Use
CONTENTS

AI Pair Programming Workflow

Work with AI in short cycles while keeping design and correctness decisions human-led.

AI Career Skills Course
Module 5: AI For Coding
AI career skills
generative AI
+6
May 28, 2026
27
A

Learning Outcome

Work with AI in short cycles while keeping design and correctness decisions human-led.

Core Ideas

  • Small batch: A limited change reviewed before continuing.
  • Human ownership: Developer remains responsible for correctness.
  • Diff review: Inspecting what changed line by line.
  • Acceptance criteria: Observable conditions for done.

Career Use Case

A developer can work with AI in short cycles: state intent, inspect a small patch, run tests, and decide the next step.

Practical Workflow

  1. Start by naming the outcome: what should improve after using AI Pair Programming Workflow?
  2. Add the input material, constraints, and success criteria before asking for output.
  3. Ask for assumptions and uncertainty when the answer affects a real decision.
  4. Verify important claims, numbers, and policy statements before publishing or acting.

Hands-On Mini Task

  • Design a three-step AI pair-programming loop for a bug fix or small feature.
  • A good loop keeps scope small and verifies each change before expanding.
  • Before moving on, explain how Small batch and Human ownership change the decision.

Common Mistakes

  • Using a generic prompt when the task needs clear context.
  • Accepting polished wording as proof of accuracy.
  • Sharing private data without redaction or approval.
  • Skipping a final human review for important decisions.

Quick Revision

Module 5: AI For Coding lesson 15 is about practical judgement: use AI to increase speed, but keep the goal, context, evidence, and accountability clear.

FAQs

Is AI Pair Programming Workflow only for technical users?

No. The course treats AI as a practical workplace and learning skill, with technical depth only where it improves judgement.

Should I trust AI output immediately?

No. Use AI to accelerate work, then verify facts, privacy, source fit, and reasoning before relying on the result.

What should I practice after this lesson?

Design a three-step AI pair-programming loop for a bug fix or small feature.

How does the linked practice quiz help?

The practice quiz checks the lesson concepts immediately with feedback, while the paid mock bundle uses separate assessment questions.

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mediumAI Career Skills
Practice Quiz 15: AI Pair Programming Workflow
12 questions12 min

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Lesson 3 of 3 in Module 5: AI For Coding
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AI for Tests, Refactors and Code Review
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AI for Spreadsheet Cleanup and Analysis
Module 6: AI For Data And Analysis
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