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PEOPLEPILOT ACADEMY • CERTIFICATION

From Prompts to Production — Build Software with AIProgramming with AI

From prompts to production — master the art of building software with artificial intelligence. Decode how LLMs think, craft expert-level prompts, wield every major AI coding tool, and architect AI-powered features that ship. 7 modules, 1 capstone, zero magic — just systematic skill.

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8
Modules
36
Lessons
14h
Duration
0.0
0 reviews
Certificate of Completion included
Our 3-Layer Framework:
1. Foundations
2. Tools & Techniques
3. Architecture & Production

The "What & Why" of Programming with AI

Understand what this course covers, why it matters, and the journey ahead.

AI-augmented development is the practice of using large language models as thinking partners throughout the software lifecycle — from design through deployment. Not replacement. Amplification.

TaskWithout AIWith AI
Write boilerplateCopy from old projects, adapt manuallyDescribe the pattern, get a tailored scaffold in seconds
Debug a cryptic errorGoogle the error, scan Stack Overflow threadsPaste the stack trace, get a root-cause explanation and fix
Write testsManually enumerate edge cases, write each testAI identifies edge cases you missed, generates test scaffolds
Review a PRRead every line, check patterns from memoryAI catches security issues and style violations; you focus on logic

Developer productivity insight

AI adoption metrics preview

Interactive Course Syllabus

Click on a module to expand the curriculum and try a hands-on preview.

Module 1

The New Programmer's Companion — Understanding AI for Code

1h 40m5 lessons

Module Overview

Demystify how large language models work — from next-token prediction to model selection. Build the mental model that grounds every module that follows.

Key Topics Covered

  • Next-Token Prediction
  • Tokens & Context Windows
  • Model Comparison
  • Hallucination & Temperature
  • The Centaur Developer Mindset
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Interactive

This interactive element is available in the full course.

Module 2

Speaking AI's Language — Prompt Engineering for Code

2h5 lessons

Module Overview

Transform from vague prompt-writer to systematic prompt engineer. Master the 5-component structure, Chain-of-Thought, reusable patterns, and prompt debugging.

Key Topics Covered

  • Role-Context-Task-Constraints-Format
  • Chain-of-Thought Prompting
  • Prompt Patterns Catalog
  • Prompt Iteration & Debugging
Interactive Preview
  1. Role — Who should the AI be? (e.g., senior Python developer)
  2. Context — What does it need to know? (codebase, constraints)
  3. Task — What exactly should it produce?
  4. Constraints — What rules must it follow? (no external deps, type-safe)
  5. Format — How should the output look? (JSON, function, diff)
Module 3

Your AI Copilot — Mastering AI Coding Assistants

2h 10m5 lessons

Module Overview

Hands-on mastery of GitHub Copilot, Cursor, Claude Code, and conversational AI coding. Know when to use each tool and how to get the best results.

Key Topics Covered

  • GitHub Copilot & Ghost Text
  • Cursor & AI-Native IDEs
  • Claude Code & CLI Agents
  • Chat-Based Coding
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Flashcard

Inline Completions

Click to flip in the LMS

Module 4

Quality Control — Debugging, Testing & Code Review with AI

2h5 lessons

Module Overview

AI as your quality assurance partner. Master AI-assisted debugging, automated code review, test generation with TDD, and documentation.

Key Topics Covered

  • AI-Assisted Debugging
  • Code Review with AI
  • Test Generation & TDD
  • Documentation & Refactoring
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Knowledge Check

Your AI generates a function that passes all tests but uses a deprecated API. What should you do?

Ship it — the tests pass
Review the AI output, update the API call, re-run tests
Regenerate until it uses the correct API
Add a comment noting the deprecation
Module 5

Building with AI — APIs, SDKs & AI-Powered Applications

2h 20m5 lessons

Module Overview

Graduate from using AI tools to embedding AI as a building block. Cover LLM APIs, prompt caching, structured outputs, and production concerns.

Key Topics Covered

  • LLM API Fundamentals
  • Prompt Caching & Cost Control
  • Structured Outputs & Tool Use
  • Safety, Monitoring & Fallbacks
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Module 6

The AI Architect — RAG, Agents & Advanced Patterns

2h 20m5 lessons

Module Overview

Advanced AI system design: Retrieval Augmented Generation, AI agents with tool use, multi-agent orchestration, and fine-tuning decisions.

Key Topics Covered

  • RAG Pipelines & Vector DBs
  • AI Agents & ReAct Pattern
  • Multi-Agent Orchestration
  • Fine-Tuning vs. Prompting
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Module 7

The Responsible AI Engineer — Ethics, Security & the Future

1h 30m5 lessons

Module Overview

The compass for responsible AI-augmented development. Cover bias, IP concerns, OWASP LLM Top 10, prompt injection defense, and the future.

Key Topics Covered

  • Bias in Code Generation
  • IP & Attribution
  • OWASP LLM Top 10
  • Prompt Injection Defense
  • Future of AI Development
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  1. Prompt Injection — manipulating AI through crafted inputs
  2. Data Leakage — sensitive data exposed through model responses
  3. Over-Reliance — trusting AI output without verification
  4. Model Poisoning — corrupting training data to influence outputs
  5. Supply Chain — compromised plugins, tools, or model providers
Module 8

Capstone — AI-Powered Code Review Bot

1h1 lessons

Module Overview

Design, architect, and secure an AI-powered code review bot from scratch. Five phases, real-world decisions, every module applied.

Key Topics Covered

  • Requirements & Stakeholders
  • Prompt Engineering at Scale
  • System Architecture
  • Security & Incident Response
  • Rollout & Governance
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Capstone: AI-Powered Code Review Bot

Design, prompt-engineer, and architect an AI code review system for a SaaS company with 50 developers. Apply skills from all 7 modules across 5 phases: Requirements, Prompt Engineering, Architecture, Security, and Rollout.

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