DeepMind AI code review: write prompts with a one-sentence check
from MBA Training AI Hosted by MBA Training
AI writes roughly three quarters of Google DeepMind's production code, yet only about one change in eight is fully handed to the AI. What does that mean for how you prompt? The episode argues that reliability comes from scoping and review, not from the model or magic phrases, and that delegation works best on well-defined, verifiable tasks. You will be able to write a one-sentence check before writing a prompt, split vague tasks, and use Google's Gemini Argon tips such as grill-me questions and AGENTS file retrospectives. You also get Wharton findings on threats, tips and chain-of-thought, a 20-input test set method, few-shot prompting, prompt caching, and Asana's measurable-target example. 0:00 DeepMind's AI code and human review 1:32 Why verifiable tasks get delegated most 4:23 Write the check before the prompt 5:54 Google's Gemini Argon prompting tips 7:21 Prompt folklore: threats, tips, step by step 8:55 Checkable prompts for memos and forecasts
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