Jesus Sandoval

[Rohit @heyrohitai]

Anthropic pays $750,000+ a year for engineers who can build LLM architectures from scratch.

This 2-hour Stanford lecture gives you the exact pipeline LLM engineers get paid $750K/year for.

Data + architecture + scaling laws + post-training.

Bookmark it & watch today.

[Satya Nadella @satyanadella]

https://t.co/vLmiBKTtX3

[Alex Finn @AlexFinn]

5 months ago I bought $30,000 of Mac studios, Mac mini’s, and DGX Sparks

I did this because I predicted:
• Hardware prices would explode
• Governments would start limiting LLM usage
• Local models would get way more powerful

“AI influencers” torched me for this. Called me a dangerous hype merchant

Literally 100% of these predictions came true

Mac Studios above 100gb are not even sold anymore. Fable 5 got banned. The newest local models are Opus level

And now these same influencers are tweeting local models are the future

The good news for them is they are now actually correct about something

In the next year we will all have Fable running on our desks

Unlimited super intelligence running securely and privately

Get on the boat before you are left behind

[Alex Finn @AlexFinn]

This is your wakeup call.

Anthropic just took down Fable 5. It's over.

Here's the thing tho: no company or government will EVER be able to take away your local models.

There are Opus level models you can run right now on your home GPUs, and nobody can ever stop you from using them

This is only the beginning of events like this. Day 1. More government overreach will happen. This will only keep happening more and more as models get closer to AGI

Become sovereign. Buy your own compute. Before even that becomes illegal

[0xMarioNawfal @RoundtableSpace]

A 17-YEAR-OLD TURNED A $20 CLAUDE PLAN INTO A BUG BOUNTY SYSTEM THAT CAN CHASE $15,000 REPORTS ON LEGAL TARGETS

one free bundle gives Claude 51 security skills and 574 vulnerability patterns across 24 bug classes, so it stops guessing and starts working like a real security researcher.

[Rohit @heyrohitai]

Instead of watching an hour of Netflix, watch this 2 hour hour Stanford lecture will teach you more about how LLMs like ChatGPT and Claude are built than most people working at top AI companies learn in their entire careers.

[Alex Finn @AlexFinn]

AI subscriptions are dead

Claude Fable 5 will only be on the Anthropic subscription until June 22nd. After that, you will need to pay for usage per token

This will be the start of a much larger trend

Frontier models will no longer be included in subs

You’ll pay a fee and it will only get you access to older, much cheaper models

If you want access to that dank AI sour diesel, you’re going to need to pay for every token you use. No more subsidies

And it make sense. The subsidies were just a Ponzi scheme

For those that don’t know, when you pay $200 a month for an AI sub, you get thousands of dollars of tokens

These AI companies actively lose tremendous amounts of money because of these subscriptions. GDPs of most countries every year are lost on your $200 Claude Max sub

The investor money is running dry. IPOs are coming because of this. And with IPOs need to come profitability

The golden age of paying $200 a month and being able to code on 40 Claude Code instances and getting a usage reset every 5 minutes are about to die

The party couldn’t continue ever. You can’t just leverage the entire global economy for years and expect nothing to break. Now it’s time to pay up

Means a few things:

1. Time to be responsible when it comes to which models you use. You don’t need Fable 5 for GPT 5.5 Xhigh for everything. Build the skill of knowing when to use cheap models

2. Local LLMS/hardware will come even more in demand. I’m currently running GLM on my Mac Studio. It’s great. Is it Fable? No. But it gets the job done for free on simple tasks. Learn about local LLMs

3. This is the beginning of the wealth gap expansion. Those that can afford to spend $10,000 a month on Fable 5 will build incredible products that eat up more and more of the economy. Those that can’t afford Fable 5 will have an insane disadvantage

4. The government will need to step in eventually. There will be too much civil unrest. I hope the answer isn’t free money. That won’t do anything. I hope the answer is education/access to AI resources for ALL. Universal Basic Opportunity

5. You need to seriously reconsider where your money goes every month. If you are complaining about AI prices and in the back of your mind you know your skill set is becoming quickly irrelevant, all while spending money every month on Netflix, Xbox Live, Paramount +, drugs, DoorDash, Uber, and other things that bring nothing positive to your life, you are simply doing it wrong. AI is an investment in yourself. It’s an investment in your relevance to the global economy. You need to make sure you make that investment

The pieces on the board are quickly moving around. The rules are changing. The battlefield is shifting. If you’re not strategizing accordingly, you’re cooked.

[Elon Musk @elonmusk]

SpaceX was less than 10 people back then. We didn’t even have office furniture.

[Min Choi @minchoi]

AI just changed the game in filmmaking 📽️

Creators can now generate cinema quality short films, trailers, and teasers with 100% AI🤯

8 favorite examples that will blow your mind:

[AilaunchX @Ai_Tech_tool]

Instead of watching an hour of Netflix, watch this 2 hour hour Stanford lecture will teach you more about how LLMs like ChatGPT and Claude are built than most people working at top AI companies learn in their entire careers.

[Hubert Thieblot @hthieblot]

Major green flags in a founder:

1/ crazy grit, won’t give up
2/ started building before pitching investors
3/ constantly moving, constantly generating new information
4/ very technical
5/ not addicted to founder cosplay
6/ goes out and talks to users
7/ finds creative, experimental marketing channels
8/ genuinely cares about what they’re building
9/ never blames others or external factors
10/ tinkered with projects obsessively at a young age
11/ constantly comes up with interesting ideas
12/ knows their metrics cold
13/ doesn’t chase hype, chases truth
14/ excellent storyteller. Can sell the vision to hires, investors, and customers
15/ can clearly explain what they are building in one sentence
16/ can’t stop talking to customers

If you hit a good chunk of these, tell me what you are building

[0xMarioNawfal @RoundtableSpace]

AI IS TURNING RETAIL TRADERS INTO QUANTS

• This BTC bot runs 10,000 Monte Carlo simulations before every trade
• Claude handles strategy logic while simulations stress-test possible outcomes

[Alex Jones @RealAlexJones]

⚠️HAPPENING NOW: Recently Declassified CIA Documents Reveal How The Agency Targeted The American People Through Food, Water, & Medicine To Poison & Dumb Down The Population To Make Us More Subservient To Their Depopulation Agenda!

Government Documents Also Reveal Known Treatments To Counter The Effects Of Their Attack On Our Water-Based Biology

This Is NEXT-LEVEL Must-Watch/Share Information!

@realEdwardSzall

🔴WATCH/SHARE THE LIVE X STREAM HERE:
https://t.co/vXCEH9Pqju

[Andrew Ng @AndrewYNg]

AI-native software engineering teams operate very differently than traditional teams. The obvious difference is that AI-native teams use coding agents to build products much faster, but this leads to many other changes in how we operate. For example, some great engineers now play broader roles than just writing code. They are partly product managers, designers, sometimes marketers. Further, small teams who work in the same office, where they can communicate face-to-face, can move incredibly quickly.

Because we can now build fast, a greater fraction of time must be spent deciding what to build. To deal with this project-management bottleneck, some teams are pushing engineer:product manager (PM) some teams are pushing engineer:product manager (PM) ratios downward from, say, 8:1 to as low as 1:1. But we can do even better: If we have one PM who decides what to build and one engineer who builds it, the communication between them becomes a bottleneck. This is why the fastest-moving teams I see tend to have engineers who know how to do some product work (and, optionally, some PMs who know how to do some engineering work). When an engineer understands users and can make decisions on what to build and build it directly, they can execute incredibly quickly.

I’ve seen engineers successfully expand their roles to including making product decisions, and PMs expand their roles to building software. The tech industry has more engineers than PMs, but both are promising paths. If you are an engineer, you’ll find it useful to learn some product management skills, and if you’re a PM, please learn to build!

Looking beyond the product-management bottleneck, I also see bottlenecks in design, marketing, legal compliance, and much more. When we speed up coding 10x or 100x, everything else becomes slow in comparison. For example, some of my teams have built great features so quickly that the marketing organization was left scrambling to figure out how to communicate them to users — a marketing bottleneck. Or when a team can build software in a day that the legal department needs a week to review, that’s a legal compliance bottleneck. In this way, agentic coding isn’t just changing the workflow of software engineering, it’s also changing all the teams around it.

When smaller, AI-enabled teams can get more done, generalists excel. Traditional companies need to pull together people from many specialties — engineering, product management, design, marketing, legal, etc. — to execute projects and create value. This has resulted in large teams of specialists who work together. But if a team of 2 persons is to get work done that require 5 different specialities, then some of those individuals must play roles outside a single speciality. In some small teams, individuals do have deep specializations. For example, one might be a great engineer and another a great PM. But they also understand the other key functions needed to move a project forward, and can jump into thinking through other kinds of problems as needed. Of course, proficiency with AI tools is a big help, since it helps us to think through problems that involve different roles.

Even in a two-person team, to move fast, communication bottlenecks also must be minimized. This is why I value teams that work in the same location. Remote teams can perform well too, but the highest speed is achieved by having everyone in the room, able to communicate instantaneously to solve problems.

This post focuses on AI-native teams with around 2-10 persons, but not everything can be done by a small team. I'll address the coordination of larger teams in the future.

I realize these shifts to job roles are tough to navigate for many people. At the same time, I am encouraged that individuals and small teams who are willing to learn the relevant skills are now able to get far more done than was possible before. This is the golden age of learning and building!

[Original text: https://t.co/1pUxNC5UXk ]

[Jesus Sandoval @CryptoJesus702]

@WillingWitness @Volker464046 I accept the challenge to question my thoughts and go to the next layer.

[Derek Broes @WillingWitness]

Prophecy fulfilled. March 2018 on youtube. If you hear what is spoken, leave a comment and let me know you heard.