Prompt Chaining & Workflows
Course with certificate — try 2 lessons free. Learn to break complex AI tasks into multi-step chains that produce dramatically better results.
You write a long, detailed prompt. The AI gives you something… close. You tweak it, add more instructions, try again. Still not quite right. So you add even more detail, and the prompt becomes a wall of text that the AI half-ignores anyway.
Sound familiar?
Here’s the thing: complex prompts often produce worse results than simple ones. Research from Google and ACL 2024 shows that breaking a task into smaller steps — each handled by a separate prompt — improves accuracy by 20-50% on difficult tasks. That’s not a minor improvement. That’s the difference between “decent output” and “nailed it.”
Prompt chaining is how AI engineers build reliable systems. Instead of asking one prompt to do everything, you create a pipeline: step one extracts data, step two analyzes it, step three formats the output. Each step is simple. The chain is powerful.
This course teaches you the technique from the ground up — no coding required. By the end, you’ll build multi-step workflows that handle content creation, data analysis, customer support, and more.
What You'll Learn
- Explain why prompt chaining produces 20-50% better results than single complex prompts on difficult tasks
- Build sequential, conditional, and parallel prompt chains for real-world workflows
- Apply Anthropic's five agentic workflow patterns — chaining, routing, parallelization, orchestrator-workers, and evaluator-optimizer
- Design quality gates between chain steps that catch errors before they cascade downstream
- Evaluate security risks in multi-step chains and implement input validation, trust boundaries, and sanitization
- Create a complete multi-step workflow that combines chaining with function calling and external tools
After This Course, You Can
What You'll Build
Course Syllabus
Prerequisites
- Basic experience with AI assistants (ChatGPT, Claude, Gemini, or similar)
- Comfortable writing simple prompts and getting useful output
- No programming required — all techniques work in plain language
Who Is This For?
- AI users who've hit the ceiling of single-prompt approaches and want better results
- Content creators looking to build repeatable AI workflows for writing, editing, and publishing
- Business professionals who want to automate multi-step processes with AI
- Prompt engineers ready to move beyond individual prompts into workflow design
Frequently Asked Questions
How is this different from basic prompt engineering?
Basic prompt engineering focuses on writing better individual prompts. This course teaches you how to connect multiple prompts into workflows where each step builds on the last — the technique behind AI agents, automated pipelines, and production AI systems. Think of it as moving from writing one email to designing an entire business process.
Do I need to know how to code?
No. Every technique is demonstrated in plain language you can use directly in ChatGPT, Claude, or any AI assistant. We mention tools like LangChain and n8n for those who want to automate their chains programmatically, but the core course is completely code-free.
Which AI models does this work with?
All of them. Prompt chaining works with Claude, ChatGPT, Gemini, Llama, Mistral, and any other LLM. The principles are universal — you're designing the workflow, not relying on model-specific features.
I already use chain-of-thought prompting. Is this the same thing?
No. Chain-of-thought (CoT) asks the AI to reason step-by-step within a single prompt. Prompt chaining uses multiple separate prompts where the output of one feeds into the next. They're complementary — you can use CoT inside each step of a chain for even better results.
