Better Prompting with Pseudocode
summary
Pseudocode prompting with SudoLang and GPT‑3/4 yields concrete gains: prompts convert to runnable specifications, generate unit tests and transpile to JavaScript/Python, and compose multiagent workflows that actually work. Measured improvements include 10–20x productivity on teams, a 20–30% token reduction, and about 10–14% higher accuracy on tasks. Examples include a longest increasing subsequence implementation produced from a few constraints, typed command interfaces for a robot, and templated response formats that reduce malformed outputs.
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chapters (8)
- 0:00Introduction and background
- 4:20Why pseudocode works better
- 11:48Output control and templates
- 14:16AI-driven development demo
- 17:08Democratizing software development
- 18:32Constraint-based programming
- 21:51Common use cases
- 23:40Q&A and conclusion
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