epg_

degen alt maxi with terrible risk management

[epg_ @suomynonys]

progress 7/22/26, gym peeps hmu
#gym

[epg_ @suomynonys]

watch parties here, no one does it like me

[epg_ @suomynonys]

@MrBeast 6,500,000 #Promotion

[E @Ellis_]

This referee has to be the worst referee I’ve ever seen in my life.

Paraguay have had 0 yellows cards in this game! I’ve only been able to watch 20 minutes and they could’ve had at least 6.

This is diabolical officiating.

[Stonks and Cards @stonksandcards]

I like to root for underdogs but wtf is wrong with Paraguay?

[epg_ @suomynonys]

@luuminize @Dodgers that luffy card is clean

[epg_ @suomynonys]

@mattshumer_ if so im gna make it my orchestrator and prompt opus 4.8 like a pro

[epg_ @suomynonys]

Looks like theyre finally turning their backs on the consumer to start making some profit. Oh capitalism how it stings sometimes… :/

[Anthropic @AnthropicAI]

Claude Fable 5 will be available again globally tomorrow.

After a series of productive conversations with the US government, we're redeploying the model with a new set of classifiers to target and block more cybersecurity tasks. In the near term, some routine tasks like coding and debugging will fall back to Opus 4.8. We’ll continue to refine these classifiers over the coming weeks to reduce false positives and better distinguish genuine misuse from legitimate requests.

We’ve also begun drafting a consensus framework—with Amazon, Microsoft, Google, and other Glasswing partners—for assessing the severity of AI jailbreaks and how AI developers should respond to them. We invite other industry partners and model providers to join us in this effort.

Finally, we’re scaling up our collaboration with the US government on model testing and safeguards. This will include pre-release access to models and safeguards for evaluation, information sharing on jailbreaks and misuse, and dedicated resources for joint research.

Thank you to our users for your patience, and to our partners across the government, industry, and the research community who worked alongside us to make Fable 5 available again.

Read our full blog: https://t.co/VHyum831ri

[epg_ @suomynonys]

LETS FUCKING GOOOOO

[Watcher.Guru @WatcherGuru]

UPDATE: Anthropic confirms it will restore access to Fable 5 models tomorrow.

[epg_ @suomynonys]

@WallStreetAlfa @world_xyz wen badge ? 🥸

[epg_ @suomynonys]

@beyond_broke @business hmmm you dont say…?

[epg_ @suomynonys]

@washington_EY “little in return”… bruh this guy is a bot. our strongest ally is obviously the Grays 🫪

[epg_ @suomynonys]

@codewithimanshu money

[Himanshu Kumar @codewithimanshu]

My girlfriend caught me smiling at my laptop at 2AM.

I was not trading. I was calculating.

Every price on Polymarket comes from one equation:

P(i) = exp(qᵢ / b) / Σ exp(qⱼ / b)

Softmax function. The same math GPT uses to pick the next word.

Polymarket uses it to price every contract.

Most traders see 40 cents and think cheap.

I see 40 cents and check the liquidity parameter.

b = 50 means one whale swings the market 20%
b = 100,000 means barely moves

Half my old trades were in thin pools. One order wrecked my fill. I was losing money to a formula I did not know existed.

So I learned it. Then I built a bot around it.

EV = true_prob x (1 - market_price) - (1 - true_prob) x market_price

The bot checks b, calculates EV, sizes with Kelly:

f = (p x b - q) / b

And executes before my morning coffee gets cold.

$200 starting bankroll.
6 weeks later: $18,700.

I did not predict a single outcome. The bot just reads the math that 93% of traders ignore.

I built the entire framework:

LMSR pricing model
Expected value calculation
Kelly sizing at 5%
Bayesian probability updates
5 cognitive traps that blow accounts

The system scans markets 24/7. Finds mispricing. Executes before the gap closes.

No emotions. No FOMO. Just math.

You only need Claude + device + 1 hour per day.

Giving this free for 24 hours.

To get it:

1. Comment the word "money"
2. Like and retweet this
3. Follow me @codewithimanshu so I can DM you

Save this post. Deploy the softmax system this week. Start with $200. Scale on evidence.

[epg_ @suomynonys]

@codewithimanshu Money

[Himanshu Kumar @codewithimanshu]

An Anthropic paid for my espresso at Sightglass when he saw my screen.

I was backtesting a Claude-built arbitrage system. Terminal open. Live trades firing.

He glanced over. Stopped walking.

That is not TradingView. What framework is that actually running.

Claude Code. Three repos. One prompt. $20 per month.

He sat down across from me without asking.

I work on AlphaGo successor models.
We test reinforcement agents for market simulation.
You are running something similar but you let Claude write the strategy layer.

Not just strategy. Detection.

github/warproxxx/poly_data

86 million Polymarket trades.
Every wallet. Every position. Every timestamp.

You are feeding Claude transaction history and letting it identify asymmetric behavior patterns. Then cloning the profitable ones in real time.

Exactly.

One prompt: Scan every wallet with 150+ trades and ROI above 65%. Rank by consistency. Export top 40.

Claude processed 18,600 wallets in 6 minutes. Returned 38.

Top 15 wallets outperformed the bottom 18,000 combined.

That is not analysis. That is alpha concentration.

Precisely.

And you did not write the ranking algorithm.

Claude built it. I just connected it to execution logic.

Then I opened the second repo.

github/Polymarket/polymarket-cli

Official Rust CLI. No auth required for reads.
600+ markets scanned in under 3 minutes.

Claude scores: liquidity depth, pricing gap, resolution timeline.

512 markets reduced to 28 before capital moves.

94.5% filtered out before entry consideration.

A notification hit. Position filled. +$127.

How does it decide entry timing.

Four agents. No shared state.
Arbitrage detector, convergence scanner, whale mirror, volume surge tracker.

3 agents agree: full position. 2 agree: half size. Split vote: skip.

Consensus filtering alone eliminated 46% of losses in backtest.

And exit logic.

The 38 top wallets almost never hold to settlement. 89% exit early. Average 71% of max profit captured. Immediate redeployment.

My bot exits at 82% of projected move or 4x volume spike. Whichever hits first.

You built a whale copy system that exits before the whales do.

Correct.

He set his coffee down slowly.
How many trades per day.
12 average. Most rejected by filters before I see notifications.

My setup:
Claude API: $20/mo
VPS Frankfurt: $6/mo
poly_data: free
polymarket-cli: free

$300 seed capital. 34 days ago. $18,700 now.

318 trades. 76% win rate. Sharpe 2.61.

I have not modified it in 34 days.

He stared at the terminal without blinking.

This is exactly what our adversarial testing team models. Market-adaptive agents with autonomous strategy evolution. Except you deployed it live.

He messaged me the next day.

Would you consider a conversation with our safety research lead.

I told him this post is the conversation.

Too late to contain.

The edge is not predicting markets. It is identifying who already wins and mirroring them before the pattern shifts.

You only need Claude + device + 1 hour per day.

Giving this free for 24 hours.

To get it:

1. Comment the word "Money"
2. Like and retweet this post.
3. Follow me @codewithimanshu so I can DM you

Save this post. Build the whale mirror system this week.

Start with $200. Scale on evidence.

[Bloomberg @business]

The US military said it struck Iran in retaliation to an attack on a commercial cargo ship in the Strait of Hormuz, an incident that further set back efforts to fully reopen the crucial waterway https://t.co/7r7Mgs0eq5

[epg_ @suomynonys]

@beyond_broke i agree

[epg_ @suomynonys]

@oCubann city is gna burn 🏃

[epg_ @suomynonys]

@TrumpTruthOnX bro was too busy all week with Iran to speak to this guy by name 🙂‍↔️🤣