💨

[Backseat Passenger @bkseatpassenger]

🚨LEAKED 4 CHAN PSYCHIC METHOD!

A user on 4chan posted a method for developing psychic abilities using isochronic tones while focusing attention on a visual point

What if we simply just never understood ourselves well enough to use these abilities..

[Chief Goddiz🇺🇲 @GoddayIzakpa]

🙏Sometimes your soulmate isn't the person who enters your life with fireworks, it's the one who's been standing beside you all along, Jim and Pam's love story reminds us that true love is worth the wait.

[💨 @lightituppp1]

@SineQuaN0nUSA When people tell on themselves, let them. Being racist was this clowns who objective babe

[💨 @lightituppp1]

@carebear_the @financedystop She has the same access to information probably, and her employer has an ethnics component they expect staff to follow in their employment contract. I’m sure the information is auditable if a complaint is filed

[slash1s @slash1sol]

A DEVELOPER WALKED ON STAGE DRESSED AS A 1973 ENGINEER AND "PREDICTED" THE FUTURE OF PROGRAMMING. THE TWIST: EVERYTHING HE DESCRIBED WAS ALREADY INVENTED 40 YEARS EARLIER AND WE STILL REFUSE TO USE IT.

32 minutes from Bret Victor, doing the most quietly savage talk on our entire industry.

-> The idea that lands: we write code as step-by-step text instructions and call that "Just how programming is". He shows four better ways -- all discovered in the 60s and 70s, all abandoned.

Manipulate the data directly instead of typing blind code. Tell the machine your goal instead of every tiny step. We saw all this, then walked away.

Why? The moment you're sure you know what programming is, you stop seeing anything better. That certainty is the cage.

And now AI is dragging us back to exactly what he begged for -- you describe the goal in plain words, the machine works out the how. The future he mourned is arriving anyway.

You thought text files were just how code works. This is the talk that shows it was a choice, and maybe the wrong one.

Watch this one. It'll ruin how you see your job ↓

[vegastar @vegastarr]

Nobody Is Ready For This One. 👁️⚡️

Cymatics Shows Us Something Deep:

Sound Creates Pattern.
Vibration Creates Form.
Light Reveals The Structure.

What If This Is The Code Behind Reality? ✨

Everything Is Waves.
Everything Is Frequency. 🎶

[Tech_baby @Tech_babby]

If you wanna learn to sell softwares you should follow accounts like this and replicate everything he does! Building SaaS is cheap. The content and sales is what matters now.

[0xbobaa @0xbobaaa]

rockstar quietly turned gta modding into a paid storefront. almost nobody is positioned for it

you're waiting for nov 19 to play it
the people who'll actually cash out are building right now

what actually happened:

> take-two bought fivem back in 2023
> the official cfx marketplace went live jan 12, 2026
> bundles already listed up to $389
> recurring server mods at ~$24/month
> all of it runs on tebex the same rails modders sold on for years

the skill barrier just died too:
claude writes lua. job systems, custom huds, npc dialogue describe it in plain english, get working scripts back in minutes

here's the part nobody says out loud:
the marketplace is invite-only right now. ~16 creators at launch
that's not a wall. that's a head start for whoever applies and ships first

gta 6 drops nov 19 at $79.99
millions of players incoming. an official store that's basically empty. and a months-long review head start sitting there for the taking

gta online creators made $0 off a game that printed billions
that door is finally open and it's open early

save this

[HALO | CAREER SPECIALIST @Halosznn_]

I spent my whole weekend working on this.

So here are 500 email templates for your next job applications, broken down by roles

Plus:
• A “before you send” checklist
• What NOT to do (with real examples)
• The formula behind every subject line and opener
• Industry-specific numbers to plug into your CV

This is the thing nobody is giving away for free but I am 💗

You’re welcome 💗
https://t.co/MWzhwSE83b

[MindBranches @MindBranches]

Human 3.0 – A Map To Reach The Top 1%

article summary in 4k dark mode

[P Equity Research 📰 @pequityresearch]

J.P. Morgan: Power Semiconductor

1. Grid to Rack (20kV AC --> 800V DC)

Infineon stands out as a clear leader here, boasting the broadest portfolio and acting as the leading 1.2–3.3kV SiC MOSFET supplier, qualified by Nvidia for 800V architecture.

Navitas offers the highest voltage SiC (2.3–6.5kV) targeting SST applications.

STMicroelectronics and ON Semiconductor show strong presence with SiC portfolios, while Monolithic Power Systems (MPS) has no presence at this stage.

2. 800V DC --> 48V/12V/6V DC (Stage 1 - Inside the Rack)

Infineon and Navitas both show highly competitive GaN (Gallium Nitride) offerings. Navitas highlights a 10kW all-GaN 800V-to-50V platform achieving 98.5% peak efficiency.

Monolithic Power Systems is actively sampling 800V solutions and features integrated 48V direct-to-load modules.

Rohm is deploying its EcoGaN 650V HEMTs in AI server PSUs but has a more limited GaN breadth compared to Navitas or Infineon.

3. 48V/12V/6V to AI Chip (~1V DC) (Stage 2 - VRM / PoL)

This final stage delivers low-voltage, high-current power directly to the AI processor (GPU/ASIC) via Voltage Regulator Modules (VRM) and Point of Load (PoL).

Infineon remains dominant as the leading supplier of sub-100V MOSFETs and power stages to all major GPU makers and hyperscalers.

Monolithic Power Systems is a major force here, gaining significant share in VRM sockets and showing strength with hyperscalers for custom ASIC power delivery.

Analog Devices acts as an "intelligence layer" around the VRM, focusing on multi-phase digital controllers and monolithic smart power stages.

Rohm and STMicroelectronics have limited presence or are not significant players in this final AI chip delivery stage.

Key Suppliers:

Si MOSFET

Infineon $IFX.DE, ON Semiconductor $ON, Monolithic
Power Systems $MPS, Renesas $6723.T

Si IGBT

Infineon $IFX.DE, STMicroelectronics $STM,
Mitsubishi Electric $6503.T

SiC MOSFET

Infineon $IFX.DE, STMicroelectronics $STM, ON
Semiconductor $ON, Wolfspeed $WOLF, Rohm
$6963.T

GaN HEMT

Infineon $IFX.D, Navitas $NVTS, EPC, ON
Semiconductor $ON, Innoscience $2577.HK

Gate Driver

Infineon $IFX.DE, Texas Instruments $TXN,
STMicroelectronics $STM, ON Semiconductor $ON,
Analog Devices $ADI, Renesas $6723.T

Multi-Phase Controller

Infineon $IFX.DE, Monolithic Power Systems $MPS,
Renesas $6723.T, Analog Devices $ADI, Texas
Instruments $TXN

Power Modules/Integrated Power Stages

Infineon $IFX.DE, Texas Instruments $TXN, ON
Semiconductor $ON, Analog Devices $ADI,
Renesas $6723.T, Monolithic Power Systems $MPS

Protection/Monitoring ICs

Analog Devices $ADI, Texas Instruments $TXN,
Monolithic Power Systems $MPS, Infineon $IFX.DE, ON
Semiconductor $ON, Renesas $6723.T, Microchip
Technology $MCHP

[Moysei @0xMoysei]

Karpathy just wrote the manual for Claude + Obsidian as a real second brain.

Most vaults die the same way. A year of saved articles and highlights. None of it linked. The graph rots while it still looks impressive.

So he moved the upkeep to the model. You curate sources and ask questions. Claude files, links, and reconciles. You keep judgment. It keeps the books.

raw belongs to you and never gets edited. wiki belongs to Claude. It isn't RAG. Your sources compile once into linked pages and compound from there.

9 rules. Start with 10 sources, not 10,000.
Most people hoard notes. This turns them into a brain that maintains itself.

[darkzodchi @zodchiii]

A Stanford team just published the 16-page PDF on “How to structure an AI agent”

Structure matters more than how you prompt it, and it's backed by hard numbers.

Build → Reflect → Curate → Reuse

• Build: the agent starts with a structured context, not a clever one-off prompt.

• Reflect: it watches what actually worked during execution, no labels needed.

• Curate: it folds those wins into an evolving playbook instead of a static prompt.

• Reuse: the next run starts from that refined structure, getting stronger each time.

This is exactly why senior engineers build the structure first in Claude Code, then let the agent run.

Read the paper, then grab the setup below 👇

[Roan @RohOnChain]

this is the EXACT architecture to build hedge fund using "loop engineering" that prints alpha 24/7

it would replace a 100 person quant team

if I had this a year ago, I would've built my hedge fund in a week instead of a year, bookmark now

[darkzodchi @zodchiii]

A senior Anthropic engineer just published the clearest blueprint on "How to give your AI agent a real memory" and it's a 15-page PDF.

Write → Consolidate → Recall → Apply

• Write: after every attempt, the agent records what it tried and what happened.

• Consolidate: it distills those raw attempts into a few reusable lessons, not a transcript dump.

• Recall: before the next task, it reads those lessons first.

• Apply: it skips the dead ends it already learned, even on a brand new problem.

This is exactly how engineers now build agent loops in Claude Code.

Read the paper, then grab the setup below 👇

[Roan @RohOnChain]

this is f*cking dangerous

someone just open sourced the entire "LOOP ENGINEERING" framework for free

build a hedge fund printing alpha 24/7 by feeding it into claude code with my article below

bookmark before someone takes it down

[RJC @RJCcapital]

This is my equity analyst from now on for these types of post just follow this guy put notif on

[Teknium 🪽 @Teknium]

Not everything needs an llm involved - Hermes can run regular scripts through its cron system and use its gateway to update you on outcomes without the agent burning money 😇

[Mo Elgaraihy @EngMoElgaraihy]

الصين تفجر أكبر قنبلة علمية وتدخل بالذكاء الاصطناعي إلى عصر "الماتريكس" الفعلي؛ فريق Qwen الشهير بنى شيئاً مرعباً سيغير طريقة تطوير الـ AI للأبد

​الفكرة ببساطة: بدلاً من تدريب الذكاء الاصطناعي على كيفية استخدام الإنترنت أو نظام الأندرويد أو اللابتوب، قاموا ببناء موديل خارق اسمه Qwen-AgentWorld ومهمته أنه "يحاكي ويتخيل" أنظمة التشغيل والإنترنت والـ Terminal بالكامل داخل عقله البرمجي!

​يعني الموديل أصبح عبارة عن "عالم افتراضي كامل" يضم 7 بيئات تشغيلية ضخمة داخله؛ يتفوق في دقة محاكاتها على أعتى الموديلات الحالية مثل GPT-5.4 و Claude Opus 4.8

[Hex Horizon @Noderunner_Hex]

SOMEONE DROPPED 900+ NANO BANANA PRO PROMPTS INTO A FREE GITHUB REPO

The guy in the video is walking through a library with over a thousand structured JSON prompts.

Product photography, 3D miniatures, character design, cinematic portraits, logos.

Every category a paid prompt pack usually charges 40 to 200 dollars for.

The prompts are not one-liners. They are full JSON objects with subject, scene, composition, lighting, camera settings.

The exact format models like Nano Banana Pro respond to best.

Three months ago people were selling 50-prompt PDFs on Gumroad for 27 dollars. That entire market just got undercut by a single repo with 18x the volume at zero cost.

This is the pattern with every AI tool. A skill becomes scarce, someone monetizes it, then someone else commoditizes it inside a quarter.

The window to sell prompts as a product is basically closed.

What survives is the layer above. Workflows, automations, finished assets, clients.

Selling the raw input stopped working the moment GitHub became the distribution channel.

The prompt economy died faster than the NFT one.