ChatGPT for Work: Prompts, Productivity, Automation, Custom GPTs, and Agent Mode Course

Lesson 1 • How Large Language Models Work

Explains token prediction, training data, and model limitations without jargon. Grounds every later prompting decision in accurate mental models.

Lesson 2 • Setting Up for Workplace Use

Configures accounts, team workspaces, and privacy settings for professional environments. Prevents data-exposure mistakes from day one.

Lesson 3 • Navigating the ChatGPT Interface

Covers the web and mobile UI, conversation management, and settings. Ensures fluency with the tool before tackling advanced features.

Lesson 1 • Prompt Patterns for Professional Contexts

Applies established prompt patterns—persona, template fill, and critique—to workplace scenarios. Accelerates prompt writing by reusing proven structures.

Lesson 2 • Iterating and Refining Responses

Teaches follow-up prompting, targeted correction, and regeneration strategies. Converts mediocre first drafts into polished, usable outputs efficiently.

Lesson 3 • Anatomy of an Effective Prompt

Breaks down role, context, task, format, and constraints as the five core prompt components. Provides a reusable scaffold for every prompt written in later chapters.

Lesson 4 • Building and Managing a Prompt Library

Organizes reusable prompts into a searchable personal library for consistent results. Reduces rework and standardizes quality across a team.

Lesson 1 • Summarizing and Extracting Key Information

Condenses long documents, meeting notes, and articles into actionable summaries. Saves hours of reading time across research-heavy roles.

Lesson 2 • Editing, Rewriting, and Tone Adjustment

Applies targeted editing prompts to improve clarity, conciseness, and tone. Teaches how to preserve the author's voice while upgrading quality.

Lesson 3 • Translating Content Across Formats and Audiences

Converts technical content into plain language and vice versa for different stakeholders. Expands communication reach without additional writing effort.

Lesson 1 • Supporting Strategic Decisions with AI

Uses scenario planning, devil's advocate prompts, and assumption testing to stress-test decisions. Reduces cognitive bias by externalizing reasoning through structured dialogue.

Lesson 2 • Verifying and Fact-Checking AI Outputs

Establishes a systematic verification workflow for AI-generated research and analysis. Prevents costly errors from undetected hallucinations in professional deliverables.

Lesson 3 • Structuring and Analyzing Information

Applies frameworks like SWOT, pros-and-cons, and root-cause analysis through prompting. Converts raw information into structured insights ready for decision-making.

Lesson 4 • Data Interpretation and Insight Generation

Feeds structured data into ChatGPT to generate plain-language interpretations and trend narratives. Bridges the gap between raw numbers and stakeholder-ready insights.

Lesson 1 • Measuring and Optimizing Automation Impact

Tracks time saved, error rates, and output quality to evaluate automation effectiveness. Establishes a continuous improvement loop for AI-assisted workflows.

Lesson 2 • Identifying Automation Opportunities

Maps repetitive, text-based tasks in daily work that are strong candidates for AI automation. Creates a prioritized automation backlog before any implementation begins.

Lesson 3 • Designing Prompt-Driven Workflows

Structures multi-step prompt sequences that handle end-to-end tasks with minimal human input. Introduces workflow design principles that scale beyond single prompts.

Lesson 4 • Integrating ChatGPT with Productivity Tools

Connects ChatGPT outputs to tools like spreadsheets, project managers, and email clients via copy-paste and API-adjacent methods. Embeds AI into existing tool stacks without coding.

Lesson 1 • Writing Effective System Instructions

Crafts system-level instructions that define persona, scope, tone, and behavioral guardrails. Determines the consistency and reliability of every Custom GPT built.

Lesson 2 • Adding Knowledge and Context Files

Uploads documents, style guides, SOPs, and reference data to ground GPT responses in organizational knowledge. Transforms generic AI into a domain-specific expert.

Lesson 3 • Configuring Actions and Integrations

Connects Custom GPTs to external APIs and tools to enable real-time data retrieval and task execution. Extends GPT capability beyond static knowledge into live workflows.

Lesson 4 • Understanding the Custom GPT Architecture

Explains how Custom GPTs differ from standard chats through system instructions, knowledge files, and actions. Provides the conceptual foundation for all build decisions.

Lesson 1 • Advanced Agentic Workflow Patterns

Combines multiple agent runs, custom tools, and handoff logic into sophisticated end-to-end workflows. Prepares professionals to tackle complex, multi-day autonomous tasks.

Lesson 2 • Designing Tasks for Agentic Execution

Identifies task characteristics that make them suitable for autonomous execution and structures them for reliable agent performance. Prevents common failure modes through upfront task design.

Lesson 3 • Supervising and Correcting Agent Runs

Establishes human-in-the-loop checkpoints to catch errors, redirect agents, and approve consequential actions. Balances autonomy with accountability in professional settings.

Lesson 4 • What Agent Mode Is and How It Works

Explains the agentic loop of planning, tool use, observation, and iteration that drives autonomous task execution. Distinguishes agent mode from standard chat to set accurate expectations.

Lesson 1 • Establishing AI Governance and Policies

Creates usage policies, data-handling rules, and quality standards that govern AI use across the organization. Reduces risk while enabling confident, broad adoption.

Lesson 2 • Sustaining and Scaling AI Capabilities

Establishes feedback loops, update cycles, and centers of excellence to keep AI capabilities current. Prevents capability decay as models, tools, and business needs evolve.

Lesson 3 • Building an AI Adoption Strategy

Defines a phased roadmap for rolling out ChatGPT across departments with clear goals and milestones. Aligns AI investment with measurable business outcomes from the start.

Lesson 4 • Training and Upskilling Teams

Designs role-specific training programs that build practical AI skills across diverse teams. Accelerates adoption by meeting employees at their current skill level.