Summary
Single prompts for complex tasks lead to incomplete or incorrect implementations. Break complex tasks into explicit multi-step workflows with verification at each step to reduce cognitive load, isolate errors, and maintain context. Each step builds on verified previous work, resulting in higher quality and fewer regressions.
The Problem
Single prompts for complex tasks overwhelm the LLM’s cognitive capacity, leading to incomplete implementations, missing edge cases, truncated outputs, and forgotten requirements. When errors occur, it’s difficult to isolate which part failed, requiring complete re-generation.
The Solution
Break complex tasks into explicit multi-step workflows where each step focuses on one thing, has clear verification criteria, and builds on verified previous work. Use verification gates between steps to catch errors early. This reduces cognitive load, enables error isolation, and maintains clear context throughout implementation.
Related Concepts
- Chain-of-Thought Prompting – Reason through steps before implementing
- Declarative Constraints Prompting – Define constraints for each workflow step
- Few-Shot Prompting with Project Examples – Use examples at each step
- Layered Prompts Architecture – Structure workflow context in layers
- Progressive Disclosure Context – Load step-specific context as needed
- Explicit Constraints and Non-Goals – Scope each step with clear boundaries
- Incremental Development Pattern – Build incrementally with verification
- Actor-Critic Adversarial Coding – Critique at each workflow step
- Verification Sandwich Pattern – Verify between steps
