Vaxor

Planning doesn't always lead to the result you want.

[Vaxor @Vax0r]

Most people ask Claude random questions and get random answers.

This 4-prompt chain turns it into a money-making machine.

Prompt 1: Ask for the fastest way to hit your income goal, but limit it to one offer and one channel.

Prompt 2: Ask who is the most successful person doing that and get one name.

Prompt 3: Tell Claude to act as that person and create a 90-day plan to get your first paying customer with under $1,000 upfront.

Prompt 4: Switch to entrepreneur coach mode. Find what’s holding you back, reframe it, and give you a 2-week action plan to prove it works.

Instead of motivation and generic advice, you get a clear step-by-step blueprint.

Most people waste months jumping between ideas. Those who use structured prompts like this move from zero to first customer much faster.

[Vaxor @Vax0r]

Claude just started creating full UGC ads by itself.

You upload one product photo. Claude generates the model, places the product in the scene, writes a natural script, and creates 5 different variations for A/B testing — all inside one chat.

No switching between Midjourney, CapCut, or any other apps. No manual editing.

What used to take 2–3 hours of work now takes under 10 minutes. And the quality is actually good enough to run tests.

Most people are still making UGC ads the old way — manually shooting, editing, and writing scripts. Those who switched to this workflow are producing content 5–10x faster.

The skill that connects Claude with Arcads is what makes it possible. Once it’s set up, you just drop the product photo and let it do the rest.

[Vaxor @Vax0r]

@ridark_eth Great system. Especially impressive that the channel publishes daily with zero human involvement. This is no longer “AI helps” — it’s “AI does everything by itself”.

[Vaxor @Vax0r]

@andreysuperior The fact that he’s not just selling agents, but a complete system (with invoicing, support, briefs) is the real value. People pay for results, not for “AI”.

[Vaxor @Vax0r]

@IndianTechGuide After the pandemic, solutions like this became even more relevant. Fast book processing is both hygiene and care for readers.

[Vaxor @Vax0r]

@ApoStructura The scale is literally cosmic. One structure in orbit producing as much energy as the entire planet combined. If this ever gets built, it will be a turning point for energy.

[Vaxor @Vax0r]

@Rainmaker1973 Japanese engineering in action A tail for balance — sounds like something from anime, but the idea is very smart. The main thing is that it’s comfortable and not too heavy

[Vaxor @Vax0r]

Running good LLMs locally is now stupidly easy for beginners.

You don’t need a gaming PC or expensive cloud credits anymore.

Just install Ollama, go to the Hugging Face leaderboard, filter models for consumer devices or edge hardware, pick a GGUF quantized version (Q5K works great for most people), copy the command and paste it in terminal.

The model downloads and runs directly on your machine. It’s smaller, faster, and the quality drop is minimal.

Works on normal laptops and even low-end GPUs. No subscriptions. No rate limits. Everything stays private.

Most people still believe running serious models locally is complicated and requires powerful hardware.
That stopped being true a while ago.

Ollama + Hugging Face made the whole process beginner-friendly.

[Vaxor @Vax0r]

Running LLMs locally just became beginner-friendly.

You don’t need a powerful GPU or complicated setup anymore.

Install Ollama, go to the Hugging Face LLM leaderboard, filter for consumer or edge devices, pick a GGUF quantized model (like Q5K), copy the command and paste it in terminal.

That’s it.

The model downloads and runs locally. It’s smaller, faster, and loses almost no quality thanks to quantization. Works on normal laptops and even low-end GPUs.

No subscriptions. No rate limits. No data sent to anyone.

Most people still think running good models locally is hard or expensive.
The barrier dropped hard in the last year.

Ollama + Hugging Face made it stupidly simple.

[Vaxor @Vax0r]

Running serious LLMs locally is easier than most people think.

This guy runs Gemma 2 4B (and even multimodal models) on a tiny mini PC with Intel N97 and only 16GB RAM — no GPU at all.

He uses LM Studio. Install takes a few minutes. You pick a model based on your hardware, download it, and start chatting. It even supports images.

Performance on this weak hardware: around 3.6 tokens per second. Not lightning fast, but completely usable and 100% private.

No subscriptions. No rate limits. No data leaving your machine.

Most people still think you need a powerful GPU or expensive cloud plans to run good models locally.
That barrier is already gone for a lot of use cases.

LM Studio makes it stupidly simple.

[Vaxor @Vax0r]

@andreysuperior The most interesting part is the 85% margin and that clients almost never leave. Because the math simply doesn’t allow it. This isn’t selling anymore — it’s creating dependency on the result.

[Vaxor @Vax0r]

@lukas_m_ziegler Very strong approach. Most companies test until it breaks in the customer’s hands. Dyson breaks it themselves and learns. That’s the difference between marketing and real quality.

[Vaxor @Vax0r]

@sutoroveli_news Looks like something out of sci-fi or the Moomins But the vortex vibration idea is really smart. Fewer moving parts = fewer breakdowns.

[Vaxor @Vax0r]

@Botan_cr Very impressive BrazeFX implementation in Unity. The downwash and smoke look extremely natural. Respect to the creator!

[Vaxor @Vax0r]

People are still paying monthly for AI video credits.

This open-source tool generates cinematic videos locally — with sound effects and emotional audio — completely free and unlimited.

You just upload an image or type a prompt. It creates full scenes, controls camera movement, adds sound, and keeps going without credit limits or subscriptions.

No more “you’ve reached your generation limit” messages.
No more recurring bills.

Everything runs on your machine.

Most people will keep paying for convenience.
Those who switch will save hundreds every month and have full control.

The tool is open source and already works.

[Vaxor @Vax0r]

A guy lied his way into a $72k job.

He told them he’s an expert in technical SEO, AI automation, and full funnel strategy.

Day one they asked for a Semrush audit, LLMs.txt file, and competitive gap analysis by EOD.

He panicked… then opened ChatGPT.

Now he’s actually learning technical SEO while getting paid to fake it.

The best part? He went from “I have no idea what any of this means” to “Wait… am I becoming employable?”

Fake it till you make it just got an AI upgrade.

[Vaxor @Vax0r]

NVIDIA just made paid AI APIs optional.

80+ top models are now available for free with real limits.
No credit card required. Instant API key.

You get DeepSeek, Kimi, GLM, MiniMax, OpenAI models and many more — all in one place.
Generate the key in seconds at https://t.co/X3WevtyTo9 and use it directly in Claude Code, Cursor or any other tool.

People were easily spending $200–500 every month on API access.
Now the cost for testing and building can be zero.

Most builders will keep paying because they won’t believe it’s real.
Those who check it will have a clear advantage for the next few months.

The offer is live right now.

[Regalos Digitales @RegalosDigitals]

@Vax0r Is very creativity,
I just followed you. Here is the step-by-step setup guide. What do you think about this? Is it useful to you?

https://t.co/vEieMN5xrK

[Vaxor @Vax0r]

@RegalosDigitals Thanks! I just checked the guide, looks really detailed. Appreciate you sharing it and for the follow

[Vaxor @Vax0r]

A mini PC the size of a router just killed his $20/month AI subscription.

New AMD chip built specifically for running AI models locally.
No cloud round-trip. No company logging every prompt you send.
Everything stays on the device.

Most people think AI lives in a browser tab.
It doesn't have to anymore.

This thing runs serious language models directly on the hardware —
private, offline, no monthly bill creeping up every year.

Cloud AI made sense when local hardware couldn't keep up.
That excuse is running out fast.

[Vaxor @Vax0r]

https://t.co/2Wu7x6yjV0