1"use strict";(self.webpackChunk_N_E=self.webpackChunk_N_E||[]).push([[4563],{34563:e=>{e.exports=JSON.parse('["Step 1: Analyze the current prompt structure. Step 2: Identify areas for improvement. Step 3: Research best practices for this prompt type. Step 4: Redesign the prompt with enhancements. Step 5: Test the new prompt. Step 6: Compare results. Step 7: Refine based on feedback. Step 8: Document the final version. Apply this process to optimize: \'Write something about AI.\'","Phase 1: Understand the user\'s intent and requirements. Phase 2: Gather relevant context and background information. Phase 3: Design the initial prompt structure. Phase 4: Add specificity and constraints. Phase 5: Include examples and reference materials. Phase 6: Format for clarity and readability. Phase 7: Validate against objectives. Phase 8: Iterate and improve. Use this methodology for creating a prompt about machine learning applications.","First, define the primary objective clearly. Second, establish the target audience and their knowledge level. Third, determine the desired output format and style. Fourth, gather necessary context and examples. Fifth, structure the prompt logically. Sixth, add constraints and guidelines. Seventh, include quality criteria. Eighth, test with sample inputs. Ninth, refine based on results. Tenth, finalize and document. Execute this workflow for: \'Generate technical documentation.\'","Task 1: Identify the core question or request. Task 2: Determine what information is needed to answer it. Task 3: Consider what format would be most helpful. Task 4: Think about potential challenges or edge cases. Task 5: Design the prompt to address all aspects. Task 6: Add context that guides the AI effectively. Task 7: Specify the tone and style preferences. Task 8: Include validation criteria. Task 9: Create variations for testing. Task 10: Select the optimal version. Apply to: \'Explain prompt engineering.\'","Workflow Step 1: Clarify the exact goal and success metrics. Workflow Step 2: Map out all components needed in the response. Workflow Step 3: List any constraints or limitations. Workflow Step 4: Identify examples that would help guide the output. Workflow Step 5: Draft the initial prompt. Workflow Step 6: Review for clarity and completeness. Workflow Step 7: Enhance with specific instructions. Workflow Step 8: Add formatting requirements. Workflow Step 9: Include error handling guidance. Workflow Step 10: Finalize and test. Implement for creating a prompt about AI safety."]')}}]);
Line numbers count LF bytes from the start of the resource, as the search results do. Vendor segments are library code the classifier recognised; they are stored but not indexed. Bytes are shown as Latin1 characters, one per byte.