An Anthropic Claude Tech Lead Shared a Prompt That Perfectly Sums It Up — One of the Few Prompts That Truly Improves AI Output Quality and Is Absolutely Worth Bookmarking.

It doesn’t ask the AI to write more. It forces it to go deeper on the task.

The brilliance of this prompt is that it simultaneously corrects four of the most common AI problems:

1️⃣ We often don’t know what we’re missing. Having the AI re-examine the task from the perspective of a top-tier practitioner uncovers requirements that a layperson would never think to ask about.

2️⃣ AI easily layers summaries on top of other summaries. Requiring it to go back to primary sources — original data, source code, papers, financial reports, logs, or user interviews — reduces the information distortion that occurs through multiple rounds of paraphrasing.

3️⃣ “Analyze in depth” is far too vague. Only after specifying methods and tools does the analysis become an executable, reviewable process.

4️⃣ And most critically: you can’t let the AI declare its own answer correct. Code needs to pass tests, research needs traceable sources, predictions need to be tested against data, and product plans need to be validated by real users and business outcomes.

The thinking behind this prompt is actually a complete workflow: first identify what’s been overlooked, then return to primary materials; clarify professional methodology, and finally have it verified by external evidence.

Next time you feel like an AI’s response looks complete but you haven’t gained any genuinely new insight, don’t just ask it to keep expanding. Send this prompt back and have it redefine the task.

Felix Rieseberg (@felixrieseberg): Hi, I’m Felix. I’m an eng lead working on Claude. I love watching people take flight and do things they never thought possible.

We often describe that as “being more ambitious” when using AI, which is tricky advice to follow. I wrote a tutorial: