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Prompt Chaining/Workflow Prompts

Prompt chaining or workflow prompting involves linking multiple prompts together, where the output of one prompt becomes the input for the next, enabling complex multi-step reasoning or task completion. This technique is essential for orchestrating advanced workflows and decomposing large problems.

Key Concepts​

  • Chained Prompts: Multiple prompts are executed in sequence, passing information between steps.
  • Intermediate Outputs: Each step produces an output that informs the next prompt.
  • Decomposition: Complex tasks are broken into manageable sub-tasks.
  • Workflow Automation: Enables multi-step processes and decision trees.

Best Practices​

  1. Define Clear Steps

    • Break the overall task into logical, sequential steps.
    • Clearly specify the goal of each prompt in the chain.

  2. Maintain Context

    • Pass relevant information from one step to the next.
    • Use structured formats (e.g., JSON, lists) for intermediate outputs.

  3. Test Each Step Independently

    • Validate that each prompt works as intended in isolation.
    • Check for errors or ambiguities before chaining.

  4. Handle Errors and Edge Cases

    • Anticipate possible failures at each step.
    • Include fallback prompts or error handling logic.

Examples​

Basic Prompt Chain​

Step 1: Summarize the following article.
[Insert article text]

Step 2: Based on the summary, list three key takeaways.

Data Extraction Workflow​

Step 1: Extract all dates from the text.
Step 2: For each date, summarize the main event.
Step 3: Organize the results in a table.

Multi-step Reasoning​

Step 1: Identify the main problem described in the scenario.
Step 2: Suggest three possible solutions.
Step 3: Evaluate the pros and cons of each solution.

Automated Research Assistant​

Step 1: Search for recent articles on a topic.
Step 2: Summarize each article.
Step 3: Synthesize the summaries into a report.

Common Pitfalls​

  1. Loss of Context

    • Failing to pass necessary information between steps.
    • Forgetting intermediate results.

  2. Step Dependency Issues

    • Later steps depend on outputs that may be missing or malformed.
    • Not validating outputs before proceeding.

  3. Overly Complex Chains

    • Too many steps make the workflow hard to manage.
    • Increased risk of error propagation.

  4. Inconsistent Formats

    • Using different formats for intermediate outputs.
    • Making it difficult to parse or use results in subsequent steps.

Use Cases​

  1. Complex Task Automation

    • Research and report generation
    • Multi-step data analysis
    • Workflow orchestration

  2. Educational Tools

    • Stepwise problem solving
    • Guided learning modules

  3. Conversational Agents

    • Multi-turn dialogue with memory
    • Adaptive troubleshooting

  4. Business Processes

    • Document processing pipelines
    • Automated decision trees

When to Use Prompt Chaining/Workflow Prompts​

Prompt chaining is ideal when:

  • The task is too complex for a single prompt.
  • Multi-step reasoning or processing is required.
  • Outputs from one step inform the next.
  • Automation and scalability are important.

When to Consider Alternatives​

Consider other techniques when:

  • The task can be completed in a single prompt.
  • Simpler, direct approaches are sufficient.
  • The workflow is too complex to manage reliably.

Tips for Optimization​

  1. Modular Design

    • Design each prompt as a reusable module.
    • Make it easy to swap or update steps.

  2. Structured Outputs

    • Use consistent formats for passing data.
    • Prefer machine-readable outputs (e.g., JSON).

  3. Iterative Testing

    • Test the chain end-to-end and step-by-step.
    • Refine prompts based on observed errors.

  4. Error Handling

    • Include checks and fallbacks for failed steps.
    • Log intermediate results for debugging.