Hasan Toor Profile picture
Jan 28 14 tweets 6 min read Read on X
Claude Pro just became the best $20/month I spend.

I use it for workflow automation, trend analysis, and document processing.

Here are 12 Claude prompts that replaced my $400/month research subscriptions: Image
Prompt 1: "Analyze these 5 competitor websites [paste URLs]. Extract their value props, pricing psychology, objection handling, and CTA strategies. Show me what's working and what gaps I can exploit."

This single prompt replaced my marketing consultant. Projects context means it remembers everything. Used this to 3x our conversion rate.Image
Prompt 2: "Read this 80-page market research PDF. Give me: (1) counterintuitive insights others will miss, (2) 3 immediate opportunities, (3) risks everyone's ignoring. Format as a strategic brief."

Turns dense reports into actionable intelligence in 90 seconds. The Artifacts feature makes it presentation-ready instantly.Image
Prompt 3: "I'm in [industry]. Find the business models that are working in adjacent industries that nobody in my space has tried yet. Explain why the transfer would work and what would need to change."

Found our entire product roadmap using variations of this. Claude's reasoning depth is insane for strategic thinking.Image
Prompt 4: "Here's our customer interview transcript [paste]. Extract: unspoken needs, language patterns for marketing, feature requests they didn't explicitly make, and emotional triggers. Rank by business impact."

Stopped paying for qual research analysis. Claude picks up nuance that even professional researchers miss.Image
Prompt 5: "Act as a hostile investor in our pitch meeting. Read our deck [upload] and ask the 10 hardest questions I need to have perfect answers for. Then help me craft those answers."

Pitch prep that used to take 4 consultants and 2 weeks now takes 30 minutes. We raised our Series A on the first pitch.Image
Prompt 6: "Analyze [competitor]'s last 50 blog posts, LinkedIn content, and landing pages. Map their content strategy evolution, identify what's working, and show me the gaps I should fill."

Content strategy intelligence that scales. Projects remember everything, so insights compound over time.Image
Prompt 7: "Review this contract [upload]. Flag: (1) unusual terms, (2) financial exposure, (3) what I should negotiate, (4) what this tells me about their leverage. Think like a ruthless lawyer."

Saved $15K in legal review fees last quarter alone. Claude's attention to detail in documents is frightening.Image
Prompt 8: "I need to make a tough decision between A and B. Here's all the context [paste]. Use second-order thinking, game theory, and risk analysis. Play devil's advocate for both sides, then give me your recommendation."

Better strategic thinking than most consultants. The reasoning transparency lets me stress-test the logic.Image
Prompt 10: "Analyze our last 3 months of business metrics [paste data]. Find: (1) non-obvious correlations, (2) leading indicators we should track, (3) what metrics we're ignoring that matter. Explain the why behind each."

Data analysis that goes beyond surface-level dashboards. Claude connects dots across datasets that humans miss.Image
Prompt 11: "Here's our problem: [describe situation]. Generate 20 solution approaches from different mental models - first principles, inversion, systems thinking, game theory, behavioral psychology. Rank by feasibility."

Creative problem-solving on demand. The Project context means it learns our business over time and suggestions get sharper.Image
Prompt 12: "Review everything we've discussed this month in this Project. Write: (1) key themes, (2) decisions made, (3) open questions, (4) strategic priorities for next month. Make it executive-level sharp."

My monthly strategy review writes itself. This alone is worth the subscription - institutional memory that actually works.Image
BONUS:

I also post content on Instagram.

So, if you want to get insights with my videos, then do follow me here:
instagram.com/hasantoxrImage
As always, Thank you for reading this.

If you enjoyed this post:

1. Follow me @hasantoxr for more of these
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More from @hasantoxr

May 15
I'm canceling my Adobe subscription after testing this.

Skywork just stacked GPT-Image-2 + Nano Banana 2 into one design workspace.

No Photoshop. No Illustrator. No designer.

Posters, logos, and full brand kits in seconds.

Here's how it works ↓ Image
Image
It's called Skywork Images.

→ Powered by GPT-Image-2 (99% text accuracy)
→ Nano Banana 2 (4K renders in under 10 sec)
→ Fully editable canvas — not a one-shot generator
→ Exports straight to PDF, print-ready

This isn't a prompt box. It's a workspace.

Try it free: skywork.ai/p/Ht3XoB
The killer move: "Open to Edit"

Skip the blank page entirely.

Browse the showcase library → click any pro design → it loads straight into the canvas as a new project.

Zero prompting. Just remix.

This is how non-designers ship work-ready posters.
Read 9 tweets
May 12
I'm replacing every memory layer I've ever built into an agent with this.

SureThing dropped SOTA on LongMemEval.

88.0% overall. 91.0% knowledge update. 76.7% single-session preference.

Number one across every category that actually matters.

Then their own AI walked up to the screen and started explaining the whole thing itself.

Nobody asked it to.
Every memory system I've built before this worked the same way.

Store something. Retrieve it later. Hope the retrieval actually finds the right thing.

Two separate systems pmretending to be one.

@getsurething threw that model out completely.

The memory IS the computation. Fully fused. One architecture, not two bolted together.

That's the difference. That's why the numbers look the way they do.Image
The benchmark breakdown:

88.0% overall on LongMemEval
91.0% on knowledge update
76.7% on single-session preference

Top of every single category.

They didn't optimize for the benchmark.

The benchmark just revealed what the architecture was already doing.
Read 7 tweets
May 9
A Chinese lab just dropped a 1 TRILLION parameter thinking model.

For free.

It's called Ring-2.6-1T from InclusionAI and it just made every $200/month "agent" subscription look like a scam.

Here's why this changes everything ↓ Image
Image
The numbers are absurd:

→ 1 Trillion total parameters
→ 63B active (MoE architecture)
→ 262,144 token context window
→ 65,536 max output tokens
→ $0 input. $0 output.

This isn't a stripped-down demo. This is the full model. Image
It's a "thinking" model built specifically for agent workflows.

Not chat. Not Q&A.

Real autonomous execution, coding agents, tool use, long-horizon tasks where the model has to stay coherent across hours of work.

The kind of thing OpenAI charges $200/mo for.
Read 10 tweets
May 5
This is genuinely impressive.

Gauth just dropped Atlas and it might be the end of textbooks.

Type any topic like "Silk Road," "how a camera works," "fall of Constantinople" and it builds you a hand-drawn, interactive visual world you can walk through.

No more reading walls of text. You explore knowledge like a map.

Here's how to use it (step by step): ↓
1. Go to

No signup wall. No paywall. Works straight in your browser.

This is the same Gauth that hit #1 in Education on the App Store built by ByteDance, used by millions of students.gauthmath.com/atlas
Type any subject into the search bar.

Anything works:

→ "The rise of the Roman Empire"
→ "Inside a beehive"
→ "How nuclear reactors work"
→ "The fall of Constantinople"

Too broad, too niche, too specific doesn't matter. If you're curious about it, Atlas builds it.
Read 10 tweets
May 5
GOOGLE QUIETLY BUILT THE SMARTEST LEARNING TOOL ON THE INTERNET

Google's NotebookLM has been free for months and it's better than any tutor I've ever paid for.

But 90% of people are using it completely wrong.

I'll give you 10 NotebookLM prompts to learn anything in record time.Image
1. The Feynman Decomposer

"Take every major concept in this material and rebuild each one as if you were Richard Feynman teaching a curious 12-year-old. Use only everyday analogies, real-world examples, and zero jargon. After each explanation, list the 3 most common misconceptions students have about this concept and explain exactly why those misconceptions feel intuitive but are wrong. Then test my understanding by asking me one question that forces me to apply the concept in a scenario not covered in the source material."Image
2. The Exam Predictor

"Act as the professor who wrote this material. Based on the structure, emphasis, repetition patterns, and depth of coverage across the source, predict the 10 most likely exam questions a professor would ask from this content. For each question, explain why it would be asked, which section of the source it pulls from, and what a perfect answer would look like. Then rank the questions from highest probability to lowest based on how heavily the source weights each topic."Image
Read 12 tweets
Apr 30
China just open-sourced a trillion-parameter model that burns fewer tokens than your favorite "efficient" US model.

Ling-2.6-1T is now public, inspectable, and benchmarkable.

The closed-model moat just got smaller.
Ant Group dropped this as a flagship, not a research toy.

1T parameters. Non-reasoning architecture. Fast-thinking by design.

It's not built to impress you with long chains of thought.

It's built to finish the task in fewer tokens than the models you're currently paying for.
The core obsession here is useful intelligence per token.

Most frontier models burn tokens narrating their thinking before they do anything.

Ling-2.6-1T skips the theater and goes straight to execution, which is the part that actually moves work forward in production.
Read 7 tweets

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