BREAKING: Stanford just surveyed 1,500 workers and AI experts about which jobs AI will actually replace and automate.

Turns out, we've been building AI for all the WRONG jobs.

Here's what they discovered:

(hint: the "AI takeover" is happening backwards) → Workers don't want full automation. They want partnership.

46.1% of tasks got positive automation ratings, but here's the kicker:

Workers prefer "H3 equal partnership" with AI over full replacement.

The world's leading AI research center completed the most comprehensive study ever on kids and AI.

They surveyed 1,800+ children, parents, and teachers in UK.

Here's what they found:

(spoiler: children are outsmarting adults on AI) The Alan Turing Institute surveyed 780 children aged 8-12 and 1,001 teachers across UK schools.

Plus, they ran workshops where kids directly tested generative AI tools like ChatGPT and DALL-E.

The results reveal how AI is already reshaping childhood:

BREAKING: Apple just proved AI "reasoning" models like Claude, DeepSeek-R1, and o3-mini don't actually reason at all.

They just memorize patterns really well.

Here's what Apple discovered:

(hint: we're not as close to AGI as the hype suggests) Instead of using the same old math tests that AI companies love to brag about, Apple created fresh puzzle games.

They tested Claude Thinking, DeepSeek-R1, and o3-mini on problems these models had never seen before.

The result ↓

AI is killing entry-level jobs faster than LinkedIn can post them.

Anthropic's CEO predicts 50% of entry-level white-collar jobs will be gone in 5 years.

If you're under 30, here's what you should do: First, context:

• Big Tech hired 25% fewer new grads in 2024
• Entry-level tech ads down 37% year-over-year
• Legal review roles down 45%

The question is why it's getting so much worse? Let me explain ↓

Most ChatGPT answers are "yes-man."

After I began using the RPT prompt technique, ChatGPT cut its wrong answers by 40% and gave me much better results.

Here's what the RPT technique is and how to use it:

(my exact prompt + example) To prompt better, first understand why AI is so agreeable.

AI gets trained by human feedback (Reinforcement Learning from Human Feedback)

When we give thumbs up to answers that sound good, the AI learns to say what makes us happy.

It's pleasing us, not checking facts.

AI is eating up consulting.

I used 3 prompts on ChatGPT to mimic a $600/hour consultant, achieving in 4 hours what takes weeks for teams.

Here's how to make ChatGPT your pocket-sized McKinsey consultant:

(my exact prompt + examples) There are 3 main tasks that a consultant does:

1. Research
2. Making slide decks
3. Reading reports

I'll show you how to automate all 3 in a way that makes one person do the work of an entire team.

BREAKING: a new Chinese model is out.

And no. This is NOT DeepSeek.

Meet Qwen-2.5, from the giant Alibaba:

1. It can code, write text, search the web.
2. It can generate images, like Dall-E.
3. It can even generate videos.

Here's everything you need to know: 1. Omni-modal mastery:

☑Handles document parsing (tables, charts, handwriting)

☑ Object grounding (JSON coordinates)

☑Long video (hours-long footage with second-level event localization)

☑ Generates structured outputs for invoices, forms & spatial reasoning tasks

https://x.com/Alibaba_Qwen/status/1884263165984399486

BREAKING: DeepSeek released R1.

And it's already better than ChatGPT o1.

1. It's open-source.
2. API is 96.4% cheaper than chatgpt.
3. I run my tests below. A quick thread: test #1 → act as an indie hacker to promote my SaaS business.

DeepSeek is so fast. It's insane.

It gave me an entire strategy in 7 actionable steps. So I asked for more:

DeepSeek is shaking up the AI industry.

1. It's open-source.
2. It's multimodal (images, PDFs...).
3. API is 94.81% cheaper than chatgpt.

I run my own tests below:
#1 → write an SEO-optimized article #1. Search the web + write an SEO article

> DeepSeek provided 50 sources.
> chatgpt provided roughly 20 sources.

The article is even better than chatgpt.

DeepSeek won. Next test:

I manage my employee's Linkedin.

We went from 0 to 3,836,555 impressions in exactly 178 days of daily posting.

The trick is... I didn't write any posts.

I do this instead: Step 1: Pinterest

1. I go to Pinterest. I pick a viral quote.
2. Copy-paste it on ChatGPT.
3. Ask it to extract the quote.

I took over someone's Linkedin, and grew it to 6.3M+ views & 6,000+ followers.

AI did everything, from copies to videos.

Here's exactly how: Eitan branding is all about the humans behind AI, through interviews.

→ He shares only video clips.
→ He finds them on YouTube, X, or reddit.

Then he edits it with Opus Clip:

Google put together a prompt library.

I've tested all of them.

Here's my top 5 prompts you can try ↓

#1. Blog Post Creator You can write a blog post from a picture.

I uploaded a picture of AI tools & gemini generated an explanation of each tool.

It's not perfect but it's a good first draft.

Now, second prompt:

Anthropic just released new interactive prompt engineering courses.

9-course links & academic papers.

Here's the link + a summary of each:

#1 → basic prompt structure Anthropic shared a course on the basic structure of prompts used for AI models.

They explain the importance of the following parameters:
> model
> max_tokens
> system prompts

The system prompt is optional but a good way to provide context & instructions.

Prompt Chaining is the best way to prompt — according to academic papers.

But I want to run a test to be sure:
→ prompt chaining vs. stepwise prompt.

I made this quick benchmark below: First, what is prompt chaining?

Prompt chaining links multiple prompts together, using each response as input for the next, to create complex results.

It uses 3 separate prompts for drafting, critiquing & refining.

So step 1:

Yesterday, I ran some tests comparing gemini 1.5 pro exp vs. gpt-4o.

Google beat OpenAI, every-single-time.

But now, is gemini better than claude?

I run the same tests:
test #1 → write a viral twitter thread #1. Generate a Twitter thread

Left: gemini 1.5 pro
Right: claude 3.5 sonnet

I provided a tweet and asked for a thread.

→ gemini suggested a better 1st tweet.

It even gave me an explanation of choices based on my prompt.

gemini won. Next test:

gemini 1.5-pro-exp outperforms gpt-4o.

Some say it's the end of OpenAI reign.

So I ran my own tests:
test #1 → write a viral twitter thread #1. Generate a Twitter thread

I provided a tweet and asked for a thread.

gemini suggested a better 1st tweet & added at the end:
→ "Here's why"

gpt-4o added emojis everywhere.
I hate them.

gemini won. Next test:

I'm the one managing my team's Linkedin.

I went from 0 to 3 million impressions in exactly 72 days, using their accounts.

The trick is... I use AI to write the posts.

Here's how I do it: Step 1: Branding

Axelle shares daily AI news videos.

Anisha shares daily inspirational messages to help people write their first post.

They share the topic with me, and here's how I write their posts:

I ditched google search for perplexity.

I run some tests to show you why:

#1: "how to write a founder agreement" First, I asked google search.

And it has too many ads:
> the 2 top links are sponsored
> too much scrolling

You need to give your email to download a founder agreement template.

I asked the same question to Perplexity:

LMSYS released Route LLM.

It cuts costs by 80% while keeping 95% of gpt-4o's quality, making it very cost-effective for LLMs.

Here's a quick recap:

#1 → Cost vs. Performance Dilemma RouteLLM balances high-quality responses with significant cost savings.

It offers comparable performance to high-cost models like claude 3 opus.

→ optimizes for quality, efficiency, cost, and privacy by using local devices.

#2 → RouteLLM Framework Overview

Perplexity just upgraded it's "Pro search" version.

They claim it's now better at research, programming & travel planning.

So I ran my own little tests: #1. Programming:

They supercharged Pro Search with powerful data analysis.

I asked for Nvidia's stock information and a graph to show its evolution.

I got:
> nvidia performance in 2024.
> graph showing stock growth.
> analysis & potential for expansion.

I'm impressed.

I don't know how to write a line of code.

So I tested which one was better between claude 3.5 vs. gpt-4o.

The goal is to create a form from scratch for my LinkedIn: I asked them to explain how to create a form with 0 code experience.

gpt-4o was much more specific.

It gave me a step-by-step on:

> which tool to choose.
> how to integrate the form.
> example of the summary section.

Then, I asked for recommendations: