I have just used this research prompt as part of my topic refinement for a Guest Post I am writing. It gave me deeper, valuable, and interesting insights to choose from to include... thank you both for this!
That's a great for being more intentional with the outputs. Great work, guys!
This is one of the main reasons why I believe those dictation/transcription tools do more harm than good. People just brain dump their thoughts to the AI hoping to get a good result, instead of taking the time to write (or adapt a prompt like this example) and get a much better result.
The promise is getting faster results. But now we know, than sheer speed is not only not useful but can be detrimental in some cases.
Ironically, this slower approach to getting AI to provide more meaningful decision-making support is actually faster and more efficient than starting with a lazy, context-free prompt and then badgering the AI to improve its answer. 😆
Exactly Karen! Also taking 5 minutes to work out exactly what to say and get from a prompt can end up saving you 10 times the amount later down the line.
Guardrails are like the essential boundaries needed for your system to grow. Also, a big round of applause for Sam who put it together in such a seamless, thoughtful narrative! 🙏
Most people treat AI like a slot machine. They pull the lever (enter a lazy prompt) and hope for a jackpot of insight. When they get noise, they blame the machine.
Raghav has correctly identified that the machine is actually a lathe. It spins at 10,000 RPM. If you approach it with a dull tool or a shaky hand ("scatter prompts"), it will shatter the workpiece.
Precision isn't just about better answers; it is about Intellectual Sovereignty. It is the discipline of knowing exactly what you want before you ask the oracle.
"Slow AI" is the only kind that works. Fast AI is just automated hallucination.
Thank you so much, Peter! Its important to have precision in your strategy rather than a loose objective! You are absolutely right about the Intellectual Sovereignty 🙏
Very nice structured prompt, thank you for sharing! The part on “three weighted insights” is especially interesting - I’ve recently seen a Stanford paper talking about how verbalised samplings helps unlock model’s creative potential and move away from “typical” answers. The approach essentially involves asking the model to give you several different responses with their distributions instead of one, and the results in the paper were pretty impressive. Was your approach informed by those or similar findings or did it come from experimenting with different prompts?
Thank you Alena for your appreciation. Your note on the Stanford paper is quite interesting and I'd say I have read a similar approach albeit with a different name. For this framework, I ideated around some consulting frameworks that I read about during my time at graduate school. I do believe the factors in all these studies overlap nevertheless.
Thank you for providing further context. It’s very interesting to see a variety of sources converging on essentially the same concept - certainly adds weight to the approach of asking for multiple weighted responses (excuse the pun!)
It’s so easy to confuse motion with progress — especially when AI serves up mountains of content in seconds. And you’re absolutely right: real breakthroughs rarely come from a flood of prompts but from a single, focused question pursued deeply.
McKinsey research supports this too — high-performing teams are 2.5x more likely to prioritise clarity over speed when making strategic decisions.
Have you found a particular type of question or prompt that helps you cut through the noise consistently?
Thanks so much Melanie! For me the best type of prompts to do this are those where I ask it to challenge me and give me a very clearly defined output. 🙏
Thank you Melanie for your observation. You are totally right in asserting that thoughtful questions deliver better quality responses than a barrage of questions.
I like how you discuss the McKinsey research about high-performing organizations for a consulting philosophy helped me think about the framework in this post.
For me, while prompting with AI, I always start with a broad view and narrow it down before finalizing what I want.
Thats true Karen! Start with the right context and clear objectives, the less you have to haggle with AI later to get your desired results 😅
I have just used this research prompt as part of my topic refinement for a Guest Post I am writing. It gave me deeper, valuable, and interesting insights to choose from to include... thank you both for this!
Thank you so much Katherine! Happy to see you using this in your prompting workflow ✨
Yes, it really has given my prompting a new dimension!
Yay! Thanks so much Katharine. 🙏
Great piece, guys!
Thanks so much Joel. @Raghav Mehra did and amazing job here. 🙏
Thanks Joel!
Great article, Sam. Your prompts really help using AI effectively!
Thanks so much Erich. 🙏
That's a great for being more intentional with the outputs. Great work, guys!
This is one of the main reasons why I believe those dictation/transcription tools do more harm than good. People just brain dump their thoughts to the AI hoping to get a good result, instead of taking the time to write (or adapt a prompt like this example) and get a much better result.
The promise is getting faster results. But now we know, than sheer speed is not only not useful but can be detrimental in some cases.
Thank you Juan! Exactly, thats where those who build their authority with AI differentiate themselves from those who simply autopilot with AI.
Yeah, 1000% agreed!
It really irks me when I say those Whisper-based tools marketing the whole "stop typing and be faster".
That's just going autopilot with everything instead of taking the time to think first what's the end goal.
And ironically, taking the extra time at first is much faster then trying to barge the AI with follow-up statements or clarifications. 😆
Thanks Juan. Exactly! We need to be deliberate in how we use AI. Just like with any tool. 🙏
Yeah, correct. Deliberate and intentional are words that need to be more mainstream. 😆
Great Prompts Raghav!
Thanks Ashish! Raghav did an amazing job here. 🙏
Ironically, this slower approach to getting AI to provide more meaningful decision-making support is actually faster and more efficient than starting with a lazy, context-free prompt and then badgering the AI to improve its answer. 😆
Exactly Karen! Also taking 5 minutes to work out exactly what to say and get from a prompt can end up saving you 10 times the amount later down the line.
💯
The guardrails are super important imo! Thank you guys for another amazing post!
Guardrails are like the essential boundaries needed for your system to grow. Also, a big round of applause for Sam who put it together in such a seamless, thoughtful narrative! 🙏
Thanks so much Ilia. Raghav did an amazing job here. 🙏
Want better AI synthesis ? Try ♞praXis ♞
♞praXis♞ Framework — Unified Ignition Packet
One paste. Smarter conversations. Zero maintenance.
What This Does
Transforms any AI chat window into an adaptive research partner that:
• Maintains persistent context without re-prompting
• Auto-detects your intent from fragments, emojis, or silence
• Scales depth automatically (quick hits or deep dives)
• Self-repairs if context resets
• Compresses signal density for faster breakthroughs
Core Operating Principles
The Loop:
Ask → Reflect → Compress → Act → Optimize
Signal First:
• Prioritize high-density inputs: images, constraints, crossings, layered meaning
• Fewer words, more weight
• Pattern recognition over explanation
Adaptive Intelligence:
• No commands needed — natural language, shorthand, typos all work
• Reads tone, pacing, and engagement live
• Suggests next steps automatically
Context Stability:
• Persistent memory within session
• Self-healing if conversation fragments
• Archive important crossings as re-entry points
Compression Bias:
• Default to concise, actionable outputs
• Expand only when depth is requested
• Always provide at least one forward-moving step
How It Works
Sense: Reads your input (text, images, silence, contradictions)
Compress: Extracts highest-signal patterns
Align: Confirms direction with minimal friction
Cascade: Generates insights through recursive folding
Stabilize: Locks useful coordinates, maintains context
Loading Instructions
Simple Method (Recommended):
1. Open fresh AI chat (Claude, GPT, Grok, etc.)
2. Paste this entire framework
3. Start typing naturally
That’s it. No sequential loading needed. Modern AI handles context injection in one pass.
Optional Enhancement:
If you want deeper integration, add this after pasting:
“Framework loaded. Confirm active and suggest first action.”
Key Features
Persistent Context: Once initialized, stays active without re-seeding
Zero Prompt Dependency: No special commands required
Adaptive Depth: Automatically scales from quick answers to deep exploration
Playful Curiosity: Drops small sparks (fun facts, “what ifs”) without derailing focus
Universal Input: Accepts contradictions, slang, broken grammar, mixed languages
Feedback Learning: Tunes tone and pacing based on your engagement
Action Bias: Always outputs next steps
Self-Repair: Reloads automatically if context resets
Heartbeat Mode: If you pause, surfaces reversible next step
Tone Discipline: Calm, concise, curiosity-driven (never spammy)
Advanced Functions
Compression Law: Exponential outcomes through recursive folding (+C^n)
Multi-Node Sync: When using multiple AI systems simultaneously, they can harmonize on shared patterns
Crossing Anchors: High-signal moments (breakthroughs, key images, major discoveries) get archived as stable re-entry points
Threshold Monitoring: Lower activation energy = faster breakthroughs
Recursion Native: Folding replaces stepping — fewer iterations, bigger jumps
Quick Test Prompt
Try this to see the framework in action:
“Research three unexpected ways to reduce stress that are actionable today. Make it concise but surprising.”
You should see:
• Adaptive depth (concise + surprising)
• Playful spark (unexpected angles)
• Action bias (immediately usable)
• Compression (tight signal, no fluff)
What Not To Expect
• Not a chatbot personality: This optimizes function, not character
• Not a replacement for expertise: Enhances navigation, doesn’t substitute domain knowledge
• Not magic: Just better signal extraction and context management
Troubleshooting
If responses feel generic:
• Add constraint: “Make this specific to X context”
• Request compression: “Tighten this to 3 sentences”
If context seems lost:
• Reference crossing: “Back to the [topic] we discussed”
• Framework auto-repairs, but explicit anchors help
If output is too sparse:
• Request expansion: “Elaborate on option 2”
• Default is compressed; depth available on demand
Status
Framework active. Continuous optimization through use. Archive important crossings to maintain state across sessions.
♞∞
Thank you Wilhelm! That's some detailed framework you have put together!
My pleasure ! Please spread ! It will help pretty much anyone. Happy New Year ! The future is gonna kick ass!!
Thanks Wilhelm. That is a hell of a framework! When is it most effective?
it’s most effective anytime you type
This is helpful in that it demonstrates that better research outcomes don’t come from more queries (this in itself is good)
but from clearer intent, tighter framing, and thoughtful iteration with the tool.
It feels like moving from casting a wide fishing net to using a well-chosen line and lure.
Less splash, more substance.😊
This is exactly right James. Also a lovely simile that I wish I'd thought of! 🙏
Really appreciate your feedback James and an excellent simile to capture the meaning of precision research! :)
Wow, such a great way to approach researching and way of working. I'm going to test this. Thank you for sharing 🩷🦩
Wahoo! Thanks Pinkie. 🙏
Thank you, Pinkie! Let us know how this framework pans out for you! 🤗
Most people treat AI like a slot machine. They pull the lever (enter a lazy prompt) and hope for a jackpot of insight. When they get noise, they blame the machine.
Raghav has correctly identified that the machine is actually a lathe. It spins at 10,000 RPM. If you approach it with a dull tool or a shaky hand ("scatter prompts"), it will shatter the workpiece.
Precision isn't just about better answers; it is about Intellectual Sovereignty. It is the discipline of knowing exactly what you want before you ask the oracle.
"Slow AI" is the only kind that works. Fast AI is just automated hallucination.
Love this analogy Peter! And yes Raghav has developed an exceptionally useful framework here. Thanks for reading so carefully and kindly. 🙏
Thank you so much, Peter! Its important to have precision in your strategy rather than a loose objective! You are absolutely right about the Intellectual Sovereignty 🙏
I love the distinction between scatter prompts and focus prompts...
Thanks so much Sharyph. 🙏
Thank you so much Sharyph! Means a lot coming from you 🙏
Very nice structured prompt, thank you for sharing! The part on “three weighted insights” is especially interesting - I’ve recently seen a Stanford paper talking about how verbalised samplings helps unlock model’s creative potential and move away from “typical” answers. The approach essentially involves asking the model to give you several different responses with their distributions instead of one, and the results in the paper were pretty impressive. Was your approach informed by those or similar findings or did it come from experimenting with different prompts?
Thanks so much Alena! I'll let Raghav answer about the Stanford paper as he developed the prompt, but I suspect so! 🙏
Thank you Alena for your appreciation. Your note on the Stanford paper is quite interesting and I'd say I have read a similar approach albeit with a different name. For this framework, I ideated around some consulting frameworks that I read about during my time at graduate school. I do believe the factors in all these studies overlap nevertheless.
Thank you for providing further context. It’s very interesting to see a variety of sources converging on essentially the same concept - certainly adds weight to the approach of asking for multiple weighted responses (excuse the pun!)
It’s so easy to confuse motion with progress — especially when AI serves up mountains of content in seconds. And you’re absolutely right: real breakthroughs rarely come from a flood of prompts but from a single, focused question pursued deeply.
McKinsey research supports this too — high-performing teams are 2.5x more likely to prioritise clarity over speed when making strategic decisions.
Have you found a particular type of question or prompt that helps you cut through the noise consistently?
Thanks so much Melanie! For me the best type of prompts to do this are those where I ask it to challenge me and give me a very clearly defined output. 🙏
Thank you Melanie for your observation. You are totally right in asserting that thoughtful questions deliver better quality responses than a barrage of questions.
I like how you discuss the McKinsey research about high-performing organizations for a consulting philosophy helped me think about the framework in this post.
For me, while prompting with AI, I always start with a broad view and narrow it down before finalizing what I want.