7. The Silent Assumption Extractor "Before answering, list every implicit assumption baked into my question. Then answer." The engineers at xAI use this before any architecture review prompt. What comes out in the assumption list is almost always more useful than the answer
@godofprompt
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AI prompt reduces code review cycles via self-critique
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3. The Anti-Expert
— God of Prompt (@godofprompt) 17 février 2026
"Explain this as if the most skeptical engineer on the team is trying to poke holes in it. What would they say?"
Gets the model to argue against itself.
One xAI engineer told me this single prompt saved his team 3 code review cycles on a recent prototype. pic.twitter.com/2z4zOIs4rh3. The Anti-Expert "Explain this as if the most skeptical engineer on the team is trying to poke holes in it. What would they say?" Gets the model to argue against itself. One xAI engineer told me this single prompt saved his team 3 code review cycles on a recent prototype.
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AI Failure Audit Method for Blind Spot Detection
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2. The Failure Audit
— God of Prompt (@godofprompt) 17 février 2026
"Complete this task, then list every assumption you made that could be wrong. Rate each assumption 1–10 on confidence."
Forces the model to surface its own blind spots.
These engineers use it before shipping any AI-generated output to production. pic.twitter.com/jiTLYPMpMh2. The Failure Audit "Complete this task, then list every assumption you made that could be wrong. Rate each assumption 1–10 on confidence." Forces the model to surface its own blind spots. These engineers use it before shipping any AI-generated output to production.
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AI models self-doubt to reduce hallucinations
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1. The Chain-of-Doubt
— God of Prompt (@godofprompt) 17 février 2026
"Walk me through your reasoning step by step. After each step, ask yourself: could this be wrong? If yes, say why."
Kills hallucination confidence.
The model second-guesses itself mid-answer instead of committing to a wrong path.
Two Meta engineers… pic.twitter.com/j4KAYmSnQy1. The Chain-of-Doubt "Walk me through your reasoning step by step. After each step, ask yourself: could this be wrong? If yes, say why." Kills hallucination confidence. The model second-guesses itself mid-answer instead of committing to a wrong path. Two Meta engineers
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Adversarial prompts change how you write AI prompts
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First thing I noticed: every one of them writes prompts that assume the model will fail. Not optimistic prompts. Adversarial ones. They're not trying to get a good answer. They're trying to catch where the model breaks. That changes everything about how you write prompts.
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Edge-case prompts powering AI prototypes
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After chatting with 8 engineers from OpenAI and Meta, I discovered they all swear by the same 7 "edge-case" prompts. Not the viral ones from Reddit. These are what power cutting-edge prototypes and debug complex models. Steal them here ↓
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Gemini writes and designs entire books in 48 hours
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BREAKING: Gemini can now write and design an entire book in 48 hours. Here are 5 insane prompts to become a published author this month: (Save for later):
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AI dev agency workflow with fixed pricing and 48-hour turnaround
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What makes this different from a dev agency: → AI scans your codebase first (architecture, dependencies, file structure)
→ You chat with an AI assistant that asks the right clarifying questions
→ Price is fixed before any work begins
→ Average turnaround: 48 hours
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Developers slower with AI tools despite feeling faster
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A METR randomized controlled trial found something wild: Experienced developers were actually 19% SLOWER when using AI coding tools. Despite believing they were 20% faster. The perception gap is real. Vibe coders feel productive. But one cybersecurity firm found Fortune 50
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Vibe coding and AI-driven MVP development challenges
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Andrej Karpathy coined "vibe coding" in February 2025. The idea: describe what you want, let AI build it. Cursor, Bolt, Replit… founders went all in. Weekend MVPs. No engineers. Just prompts and prayers.
Then production happened. Bugs they couldn't debug. Database errors