Module 7 of 7
7. Chaining & Agents
Prompt Chaining
Output of each step becomes input for the next
Step 1: Research
Gather information, summarize sources, extract key facts
ValidateQuality gate
Check: are facts accurate? Is anything missing?
Step 2: Draft
Write first draft using research output as context
ReviewQuality gate
Check: does it match requirements? Tone? Length?
Step 3: Polish
Refine language, add formatting, finalize output
Key principle: Breaking a complex task into steps with quality gates between them produces dramatically better output than a single monolithic prompt.
A single prompt is powerful. But real-world tasks, writing a research report, building a marketing campaign, analyzing a dataset, require multiple steps where the output of one step feeds into the next. This module covers prompt chaining and how it leads to building autonomous agents.
Prompt Chain Architectures
Four patterns for chaining multiple LLM calls together
SequentialOutput of prompt A feeds into prompt BLow
ParallelRun multiple prompts simultaneously, merge resultsMedium
ConditionalRoute to different prompts based on classificationMedium
RecursiveOutput triggers re-evaluation until quality threshold metHigh