⁠Durektor97

Content creator | Researcher & Contributor |
@Polymarket

[⁠Durektor97 @Durektor97]

Anthropic just showed how to build agents the right way

45 minutes live breakdown and after watching it you finally understand why most agents keep breaking

The problem is not the model it never was

The problem is people take 400 lines of logic and stuff everything into one prompt then wonder why the agent behaves unpredictably

Anthropic took a real 402-line agent and broke it down piece by piece live after every change they ran evals and watched what broke and what started working

The conclusion is simple but most people ignore it

There are three things you need to separate a tool a skill and a subagent until you decide what is what your agent will keep glitching no matter which model you plug in

GPT-4o won't save bad architecture neither will Claude

The difference between an agent that works and an agent that constantly breaks is not tokens or parameters it's where the logic lives

Engineers who learn decomposition will beat the ones just waiting for the next model release

[Morlex @0xMorlex]

https://t.co/TFc6nT6CX5

[⁠Durektor97 @Durektor97]

@OddsLedger OMG..... very well

[⁠Durektor97 @Durektor97]

@pulmencr and this is just the beginning in this area

[⁠Durektor97 @Durektor97]

Claude Opus 4.8 just wrote a trading strategy for Bitcoin and tested it himself

The agent writes a strategy that follows the trend. Tests for statistical significance to filter out random noise. Iterates until the strategy becomes profitable. Stress-tests the results with Monte Carlo and out-of-sample analysis
One team zero manual work

It used to take weeks of work for an experienced quant
Now it's one team and a few minutes

If you are trading Bitcoin manually in 2026, watch this video and then explain to yourself why

[⁠Durektor97 @Durektor97]

@fort1kkk Probably so, but the information wouldn't be superfluous

[⁠Durektor97 @Durektor97]

@pulmencr This is a masterpiece, the guy found his niche

[⁠Durektor97 @Durektor97]

$10,025 in 24 hours using Claude AI
AI tools create opportunities faster than most people can notice them

It's not some magic or luck. It's a specific process with specific actions

The video breaks down each step — what instructions were used, what system is behind it, and how to repeat it
Honestly, this is exactly the type of content that is currently in dire need of — not "AI will change the world" but "here's what I did yesterday and how much it brought"

Watch while most are still debating whether to start👇

[⁠Durektor97 @Durektor97]

🖇️Claude + TradingView = the trading brain you don't have yet🖇️

📌If you're still doing this manually in 2026, watch this video before continuing

In this video, the girl shows how she built a complete trading workflow from scratch using Claude Code TradingView Python and automation

This is not a theory or a $1000 course, but a live process that she uses herself

From signal to trade, everything is automated. Claude analyzes TradingView executes Python processes

[⁠Durektor97 @Durektor97]

@armouredme thanks for the valuable information friend

[⁠Durektor97 @Durektor97]

@Kozh_Crypto i think you like it

[⁠Durektor97 @Durektor97]

Dario Amodei believes that the emergence of a "country of data center geniuses" is only a few years away

And in this issue, we'll break down everything behind it

What the Scaling Hypothesis Really Means in the Age of Reinforcement Learning. How AI Will Spread Across the Economy. Is Anthropic Underinvesting in Computing Given Its Timelines. How Top AI Labs Will Make Money at All. Will Regulation Kill the Technology's Advantage? US-China Competition

This isn't another podcast about how cool AI is this is a conversation about what's really happening inside the industry and where it's headed

00:00:00- What exactly are we scaling?
00:12:36 - Is diffusion cope?
00:29:42 - Is continual learning necessary?
00:46:20 - If AGI is imminent, why not buy more compute?
00:58:49 - How will AI labs actually make profit? 01:31:19 - Will regulations destroy the boons of AGI? 01:47:41 - Why can’t China and America both have a country of geniuses in a datacenter?
02:05:46 - Claude's constitution

Enjoy watching and don't forget to subscribe

[⁠Durektor97 @Durektor97]

@hammertime_one shows good results

[⁠Durektor97 @Durektor97]

Guy Creates Bot That Makes Him $763 a Day Without Any Code

- In this video, he explains how it's possible using predictive markets, automation, and simple systems that anyone can replicate
- If you've been looking for ways to make money online with cryptocurrency, prediction markets, or trading bots, this is one of the most underrated opportunities right now
- Platforms like Polymarket and Kalshi allow you to trade real events using probability, and when combined with automation and data-driven strategies, this becomes a powerful source of income
- In this video you will learn how to create a Polymarket trading bot, how no code tools can automate your trades, how to find profitable prediction markets, and how to scale your daily profits with systems instead of guesswork. This is not day trading or gambling, this is structured, repeatable execution based on advantage

Whether you're into crypto trading, AI automation, side jobs, or creating passive income online, this strategy can open the door to a steady daily income

[⁠Durektor97 @Durektor97]

@Bober_smart Not everything that is free can bring results

[⁠Durektor97 @Durektor97]

@mmoyshaa I think Sweden will win this match.

[⁠Durektor97 @Durektor97]

@mopozeuX @Polymarket @PolymarketTrade The "temporary show of force" theory actually makes the most sense here

[⁠Durektor97 @Durektor97]

@PolyDekos This is a very good result, friend

[⁠Durektor97 @Durektor97]

The Man Who Built Claude Code Hasn't Wrote a Line of Code This Year

Not Because He Can't. But Because He Doesn't Need to Anymore
Boris Cherny spent 1 hour 38 minutes on the Pragmatic Engineer podcast and broke down what his real workday will look like in 2026

Claude ->Agents -> Cycles

You write the logic the system does the work. The loop continues until the result is correct. You just read what came out

And here’s what strikes me the most this isn’t the future
It’s already happening right now. While most engineers are still arguing about whether AI will replace developers some of them have already stopped writing code and are simply managing systems that write for them

The question is no longer whether it will happen. The question is when you will stop ignoring that it has already happened

[Morlex @0xMorlex]

https://t.co/xch1y8O6K6

[⁠Durektor97 @Durektor97]

Anthropic and OpenAI are saying the same thing at the same timeAnthropic and OpenAI are saying the same thing at the same time

And it’s no coincidence

Both companies are telling engineers to forget about prompts and think of agents in cycles

When two of the biggest AI labs converge on the same pattern, it’s a signal that can’t be ignored
Most engineers still think this way

Input → Model → Output

Those who win in 2026 think differently
Output becomes the new Input. The model checks its own work. The cycle goes on until the result is correct
The difference between these two approaches is the difference between an agent that’s buggy and an agent that just works

Save it for now. Until cycles become the standard and everyone starts talking about it

[rari @0xwhrrari]

https://t.co/MI0iMdcW5o

[⁠Durektor97 @Durektor97]

@HarryTandy thank you for the post, very valuable

[⁠Durektor97 @Durektor97]

@mmoyshaa That guy does things.