Maximum Liquidity (Crypto Arc)

3 months ago

FREE Claude max for 6 months! Want to know how to also get this?👇🏾

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4 months ago

Are people forgetting this was already possible and much better? This is just Google making it easy for consumers to use with a sleek interface. -

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9 months ago

How AG1 replaced a $221K/year UGC team with this Nano Banana Ad factory. Most brands are stuck in the UGC nightmare: Paying $15K+ monthly for inconsistent Creators Waiting 2-3 weeks for basic testimonial videos Getting 5-8 generic videos max per campaign Creators ghosting mid-production This system obliterates that completely. Upload your product → AI generates 200+ UGC variations → ready-to-launch video ads. Not mockups. Real scroll-stopping content. Built after watching brands burn $200K+ on creator networks that deliver recycled testimonials. The efficiency gains? Ridiculous: → 20x UGC production velocity → 97% cost reduction vs agencies → Unlimited video variations → Zero creator dependencies ever again How it works: AI Avatar Generation Engine, Creates 15+ authentic spokespeople in seconds Script Intelligence System, Maps product benefits to testimonial angles automatically UGC Production Stack, Generates lifestyle demos, unboxings, testimonials instantly Platform Optimization, Auto-formats for TikTok/FB/Instagram algorithms 47-second production time per video. Complete UGC independence.

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9 months ago

I find every ai saas landing page looking exactly the same. - Simple header - the circle profile picture testimonials - The money saved / time saved - The boring looking buttons - Simple footer When are you guys coming up with something new….

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Maximum Liquidity (Crypto Arc) @maxliq

9 months ago

Marketing is more important then the product. Convince me otherwise.

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9 months ago

@openaicommunity Small

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9 months ago

What if I told you that this is possible for every small account? Like and retweet this post and comment “Small” I will dm you how to target premium users only and that’s how you get paid more with less impressions.

openaicommunity's tweet photo. What if I told you that this is possible for every small account?

Like and retweet this post and comment “Small”

I will dm you how to target premium users only and that’s how you get paid more with less impressions. https://t.co/UFbBLgv3E2

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10 months ago

I sold the exact same AI service at 5 different prices. $97 → nobody wanted it $4,997 → everyone bought it The shocking reason why 👇 https://t.co/4CYqRYCcxU

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10 months ago

Why Claude Code Exists And Why It Destroys CodeX, Cursor, Replit, etc. Most think “better AI model = better coding tool.” Wrong. The system around the model matters more than raw IQ. Claude Code’s Origin Story: Anthropic didn’t build it for consumers. They built it to supercharge their own engineers shipping features, fixing bugs, and running multi-agent workflows faster than human-only teams could. That meant: Every prompt & workflow optimized for Claude’s quirks Project-completion checks baked into the core No “MVP” only the features Anthropic devs actually used daily It wasn’t supposed to be released. Internal debates happened. Boris (the creator) even said they weren’t sure it should go public because it was that good. So why release it? Talent magnet: Show the dev world Anthropic is the place to be Ecosystem play: Get more engineers building in Claude’s style Competitive pressure: Cursor, CodeX, Gemini were creeping into the space Here’s the key difference: OpenAI’s CodeX = “Rocket engine on a bicycle” huge power, but the frame can’t handle it. Claude Code = Formula 1 car designed around the engine from day one. Even GPT-5 with raw intelligence can’t beat a tight, integrated system that was battle-tested inside a billion-dollar company before release. If you’ve tried Cursor or CodeX and then Claude Code… You already know.

theuniversityai's tweet photo. Why Claude Code Exists And Why It Destroys CodeX, Cursor, Replit, etc.

Most think “better AI model = better coding tool.”
Wrong. The system around the model matters more than raw IQ.

Claude Code’s Origin Story:

Anthropic didn’t build it for consumers.
They built it to supercharge their own engineers

shipping features, fixing bugs, and running multi-agent workflows faster than human-only teams could.

That meant:
Every prompt & workflow optimized for Claude’s quirks
Project-completion checks baked into the core

No “MVP” only the features Anthropic devs actually used daily

It wasn’t supposed to be released.

Internal debates happened. Boris (the creator) even said they weren’t sure it should go public because it was that good.

So why release it?

Talent magnet: Show the dev world Anthropic is the place to be

Ecosystem play: Get more engineers building in Claude’s style

Competitive pressure: Cursor, CodeX, Gemini were creeping into the space

Here’s the key difference:

OpenAI’s CodeX = “Rocket engine on a bicycle” huge power, but the frame can’t handle it.

Claude Code = Formula 1 car designed around the engine from day one.

Even GPT-5 with raw intelligence can’t beat a tight, integrated system that was battle-tested inside a billion-dollar company before release.

If you’ve tried Cursor or CodeX and then Claude Code…
You already know.

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Maximum Liquidity (Crypto Arc) @maxliq

10 months ago

GPT-5 is Here… and It’s Underwhelming But These 6 Tweaks Unlock Its Real Power: I’ve been testing GPT-5 for 4 hours straight. And honestly? It’s not the leap we all hoped for. But here’s the twist with a few key tweaks, you can make GPT-5 perform like the upgrade we were all expecting. Here are 6 practical changes you can apply right now. 1. Unlock “Expert Mode” With Self-Critique Loops GPT-5’s first answer often isn’t its best.  After it replies, immediately say: “Critique your answer, find weaknesses, and improve it.”  This triggers a refinement loop that feels like human expert review. 2. Split Roles Into Sub-Agents Don’t ask GPT-5 to do everything at once.  Break big tasks into Researcher → Strategist → Writer → Editor.  Removes the “jack of all trades, master of none” effect. 3. Use Output Formats That Force Precision Tell it to respond in JSON, tables, or step-by-step lists.  Forces GPT-5 to commit to details instead of vague answers. 4. Leverage External Memory GPT-5 forgets context over long sessions.  Save outputs, feed them back in as a “project log,” and watch consistency skyrocket. 5. Chain-of-Persona Reasoning (New in GPT-5) Just found this: GPT-5 can hold multiple personalities in one answer without blending them.  Prompt: “Answer this as 3 different experts a risk analyst, a visionary founder, and a skeptical investor then merge their views into one final decision.”  GPT-4 always bled the voices together. GPT-5 keeps them razor-sharp and then integrates them like a debate. 6. Real-Time Hypothesis Testing GPT-5 can now simulate scenarios step-by-step and change its approach midway if evidence shifts.  Prompt: “Plan this marketing launch, but at each step, pause and ask: ‘If this assumption was wrong, how would I adjust?’”  GPT-4 stayed locked into its first plan. GPT-5 actively course-corrects like a strategist in a live meeting. Final Take GPT-5 isn’t broken it’s just under-optimized out of the box. Apply these 6 tweaks, and you’ll get the leap forward you were expecting. Have you found a tip that boosts GPT-5’s output? Drop it I’m testing them all.

theuniversityai's tweet photo. GPT-5 is Here… and It’s Underwhelming But These 6 Tweaks Unlock Its Real Power:

I’ve been testing GPT-5 for 4 hours straight. And honestly? It’s not the leap we all hoped for.

But here’s the twist with a few key tweaks, you can make GPT-5 perform like the upgrade we were all expecting.

Here are 6 practical changes you can apply right now.

1. Unlock “Expert Mode” With Self-Critique Loops GPT-5’s first answer often isn’t its best. 
After it replies, immediately say:

“Critique your answer, find weaknesses, and improve it.” 
This triggers a refinement loop that feels like human expert review.

2. Split Roles Into Sub-Agents Don’t ask GPT-5 to do everything at once. 
Break big tasks into
Researcher → Strategist → Writer → Editor. 
Removes the “jack of all trades, master of none” effect.

3. Use Output Formats That Force Precision Tell it to respond in JSON, tables, or step-by-step lists. 
Forces GPT-5 to commit to details instead of vague answers.

4. Leverage External Memory GPT-5 forgets context over long sessions. 
Save outputs, feed them back in as a “project log,” and watch consistency skyrocket.

5. Chain-of-Persona Reasoning (New in GPT-5) Just found this:

GPT-5 can hold multiple personalities in one answer without blending them. 

Prompt:
“Answer this as 3 different experts a risk analyst, a visionary founder, and a skeptical investor then merge their views into one final decision.” 

GPT-4 always bled the voices together. GPT-5 keeps them razor-sharp and then integrates them like a debate.

6. Real-Time Hypothesis Testing GPT-5 can now simulate scenarios step-by-step and change its approach midway if evidence shifts. 

Prompt:
“Plan this marketing launch, but at each step, pause and ask: ‘If this assumption was wrong, how would I adjust?’” 

GPT-4 stayed locked into its first plan. GPT-5 actively course-corrects like a strategist in a live meeting.

Final Take GPT-5 isn’t broken it’s just under-optimized out of the box. Apply these 6 tweaks, and you’ll get the leap forward you were expecting.

Have you found a tip that boosts GPT-5’s output? Drop it I’m testing them all.

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10 months ago

@theuniversityai @elonmusk FPS is crazy

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