Prompt Chaining: Multi Step Workflows by Hand
Link small prompts so each output feeds the next, with checks between steps you can actually see.
A taste of a lesson
I paste 10 customer interviews and ask for key findings, but the summary misses things. Would a chain help?
Very likely. One prompt over ten interviews forces the model to read, judge and write at once, and it tends to favour vivid points. Try three steps. Step one, per interview: 'List every distinct claim, with a short quote.' Step two, with all those lists: 'Group the claims into themes and count how many interviews mention each.' You review the themes. Step three: draft findings per theme, citing quotes. Run step one on a single interview now. How many claims does it find compared with what you remember?
Written by the teacher as an example. In your lesson the tutor answers your own questions, and like any AI it can be wrong.
What you will be able to do
- Design a chain with one job per step and clear handoffs
- Choose intermediate formats the next step can reliably read
- Place human checkpoints where errors would spread
- Decide when a chain earns its extra effort
Lesson plan
- 1 What chaining is and is not Understand chains as linked single job prompts with fixed handoffs. Start
- 2 Mapping your task into steps Turn a recurring task into a short sequence of steps with defined outputs. Start
- 3 Handoff formats Pick formats between steps that keep meaning intact. Start
- 4 Checkpoints and error flow Stop early errors before they spread through the chain. Start
- 5 Same chat or fresh chat Choose how to run steps based on drift and convenience. Start
- 6 Running, improving and retiring chains Maintain chains over time and know when to automate or drop them. Start
Try asking
About this tutor
Prompt chaining means splitting a job into a sequence of prompts, each with one narrow task, where the output of one becomes the input to the next. Done well, it makes complex work more reliable because every step can be inspected and fixed. This tutor teaches chaining by hand in an ordinary chat assistant, no automation tools needed: designing steps with clear inputs and outputs, choosing stable formats to pass between them, adding checkpoints, and deciding when a chain is overkill. You build two or three chains for your own recurring work, such as turning interview notes into a report or a long document into a briefing.
Reviews
4.3
3 ratingsSample
- Sana Q.Sample
Practical. Finding the first step where things went wrong is a debugging habit I use all the time now.
- Mateo L.Sample
Clear on handoff formats. I wanted more on automating chains, but the tutor was right that I needed it stable by hand first.
- Grace W.Sample
The interview notes chain now runs every month for our research team. The checkpoint after extraction is where we catch most problems.
About the teacher
Prompt workflows for heavy users: chaining, standing instructions, long documents and reasoning models
9 tutors 269 lessons taught Sample
I work with people who already use AI assistants every day and want more dependable results. My background is in operations and process design, which taught me to treat a prompt like a small procedure: inputs, steps, checks and a clear output. I teach chaining, reusable instructions, long document work and how to test whether a prompt change actually helped....
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