Codez

Anthropic's Claude team just showed how to build an AI agent with real memory in under 30 minutes. 24-minutes. free. by the people who built Claude. one person + 10 agents with memory = a team that runs 24/7, remembers every customer improves itself. worth than $500 vibe-coding course.

This 26-min speech by Stanford professor will make you realise you've been thinking all wrong about AI "don't ask which model is best. ask which workflow is best." while everyone is waiting for "Claude Mythos" - Andrew showed how you can already get those results today. the lesson: stop upgrading your model. start building loops. Bookmark & give it 26-min today. It will change the way you are using your AI tools.

@0xMovez very useful guide, thanks Movez

HIGGSFIELD SUPERCOMPUTER = A $10K/MONTH CONTENT STUDIO IN ONE CHAT what makes it different from other "AI agent" tools : → goal mode: plan → act → test → review until done → shows credit cost BEFORE rendering → skills marketplace = installable workflows watch this detailed tutorial on SUPERCOMPUTER. 15 min. free. by Studio Creator this is the first cloud-native, self-learning AI agent for end-to-end creative production. agentic podcast below was made with ONE prompt and its insane.

@polydao btw mate, didn’t YouTube ban AI content? I heard that’s happening right now.

pov: you're scrolling YouTube at 2am > you find a faceless podcast channel about true crime > just audio, AI clips, animated captions > 346K subscribers > $14,200/month from AdSense > the channel is 8 months old here's the full system: > pick an algorithm-friendly niche (true crime, celebrity drama, conspiracy) > use Polymarket to spot trending topics before they peak > clip 45-90 second moments with AI tools > layer dynamic visuals + animated captions over audio > post consistently across platforms you don't need a studio, a mic, or a name > you need a system full breakdown in the article below

@0xWast3 damn $1B in paid out, crazy numbers bro

Roblox paid out $1,000,000,000 last year most people still think it's for 10-year-olds a 15-year-old cleared $2.1M from one game you haven't published a single one here's what's actually happening: > 1 game/month × 6 months = passive catalog > 500 private servers × $10 = $5,000/month > avatar items, upload once, royalty forever > Claude writes the Lua, you ship the teenagers figured this out first the window is closing behind them bookmarked and learn

@leopardracer Crazy what opportunities vibe coding is creating right now. Thanks for sharing, Leo.

THIS DEVELOPER CONTROLS HIS MAC FROM HIS PHONE AND CLAUDE CODE DOES THE REST WHILE HE’S LYING ON THE COUCH he opened telegram and typed one command vs code launched on his laptop while he was still in bed he browsed files and navigated the repo from his phone then pushed to git without touching the keyboard once his colleagues are still sitting at their desks debugging manually the only difference between him and them is one telegram bot connected to claude code bookmark & like this if you want your setup to work for you and not the other way around

@eng_khairallah1 Damn, amazing writing, mate. I’ve already started building my agent team.

@recogard @PolymarketTrade @Polymarket @zscdao i see the banger here ! thanks for the share bro

The developer with 10+ years of experience built a Polymarket trading bot with 4 different ready to use strategies and released it on GitHub for free… Thanks Dev, this repo comes with a detailed setup guide, so it took me around 15 min to get it running. Here’s how these strategies actually work: 1. Smart Money. The bot finds top traders in the selected market and filters them by these rules: 60%+ win rate, $1000+ total pnl, profit factor 1.5x+ with stable performance. After that, it creates a list with them for automated copy trading. 2. Direct trading. This is an advanced trading dashboard for Polymarket, with extra tools like stop loss, take profit, loss limits and sniper buys. You can also enable the auto mode and let this bot trade for you. 3. DipArb. It watches for sharp drops on BTC markets. If the price drops by more than 15% in a few seconds, which usually means panic sale. So the bot buys at the lower price before the market begins to recover. 4. Arbitrage. A classic arbitrage strategy - the bot looks for situations where YES + NO costs less than $1. For example, YES is $0.46 and NO is $0.50 - the total is $0.96. When the market resolves, one side pays out $1 - a guaranteed profit of $0.04. One very useful thing - you can run this bot in DRY RUN MODE (test mode), where it executes real trades but with fake money, so u can see how it performs without risking any funds at all.

@paonx_eth yeah, also i love dreaming feature bro, have you been using it ?

@0xCodez the loop is the part nobody explains and everybody wonders why their prompts feel random

This 3-minute workshop from Anthropic will make you realize you've been using Claude Code wrong this whole time "Claude Code runs on an agentic loop that gathers context, takes action, and verifies results" most people have no idea this loop is the entire reason Claude either nails a task or wastes 50% of your tokens this isn't only for developers - once you see the loop, you start using every AI tool differently watch it. it's 3 minutes. it changes how you prompt forever.

@kirillk_web3 top tier share bro ! thanks for alpha

@Shelpid_WI3M Crazy that developers are still manually coding when we have so many tools.

Most developers are using Claude at maybe 5% of its actual power. This 30-minute Claude Code demo makes that painfully obvious. debugging entire repos → terminal automation → agent workflows → context memory. One of the few AI videos actually worth watching till the end.

@cyrilXBT Bro is dropping alpha - that should cost $1,000, for free. Thanks, Cyril.

ANDREJ KARPATHY JUST SAID SOMETHING THAT SHOULD MAKE EVERY AI DEVELOPER UNCOMFORTABLE. "90% of your AI coding bill is paying for context you didn't need to send." You are not paying for intelligence. You are paying for waste. Here are the 10 things senior AI engineers stopped doing that cut their bills by 60 to 80%: Auto-loading 50 files for a 30-line fix. $1.20 per turn on tokens you never read. 80% input waste every single session. Running Opus on lint, format, and rename tasks. $0.60 for what Haiku nails at $0.02. 30x overpay on cleanup work. Tool call loops that re-send the full repo on every retry. 5x context cost per agentic flow. Fixing this one thing cuts 30 to 50% of your total bill. Defaulting to Sonnet in 2026. Kimi 2.6 matches it on most coding tasks at one sixth the cost. You are leaving 60 to 70% on the table every session. Streaming responses on stable-prefix workflows. Kills your prompt cache. You pay 10x for tokens that should have cost cents. Just in case file includes. 80,000-token prompts that should be 3,000. Context bloat is the silent budget killer. Per-session knowledge rebuilding. 10 minutes writing a SKILL.md once versus paying agents to re-figure out your environment every run. $4 versus $0.30 per execution. Single-model setups. Premium tier on every task is the most expensive mistake in AI coding right now. Asking 10 small questions one at a time. 10 separate input prefix charges versus one batched call. 70 to 90% savings on routine workflows. Paying for Claude Pro plus ChatGPT Plus plus Cursor Pro simultaneously. You seriously use one. The other two are habit not utility. What actually compounds: Context discipline. Grep before fetching. Always. Prompt caching on every stable prefix. Multi-model routing. Kimi 2.6 as default. Opus for the 10% that needs it. Graduated skills via SKILL.md files. The routing mindset. Right model for the right task. In 12 months the gap between developers shipping on $200 a month and $4,000 a month will not be skill. It will be how well they route. Bookmark this. Study it. Follow @cyrilXBT for every AI engineering insight that compounds your output and cuts your costs.

@thejayden Legendary watch! Love the info you’re sharing.

How a 2B$ quant fund uses linear algebra to generate alpha every day. They do not pick stocks, they manage a covariance matrix. Every position is defined by its contribution to portfolio variance, not expected return alone. When the matrix shifts, the portfolio rebalances automatically. No discretion. No opinion. Pure math. PCA, isolating real risk factors Principal Component Analysis decomposes the covariance matrix into independent risk factors. Component 1: market beta. Component 2: sector tilt. Component 3: style exposure. Quants build positions explicitly neutral to components 1 and 2. That is how you isolate alpha from beta. Factor models, the signal architecture Every security gets expressed as a vector of factor exposures: momentum, quality, low vol, liquidity. A cross-sectional regression runs daily across thousands of securities. Output: a ranked signal vector. Top decile bought. Bottom decile shorted. That is the trade. Portfolio construction = optimization as execution The fund solves a quadratic optimization problem daily. Maximize expected factor return subject to vol, turnover, and concentration constraints. Output is not a trade idea. It is an exact position vector across 500 to 2000 securities. Orthogonalization = the final edge The portfolio vector gets projected onto unwanted risk factors and stripped clean. Market beta hedged. Sector tilts neutralized. Pure factor exposure remains. This runs every night. By open, the portfolio is mathematically realigned. Execution is a control system, not a click The model does not ask: “Should we buy?” It asks: “How do we minimize slippage while preserving factor exposure?” Orders get sliced across venues and time windows. Every fill updates the optimization loop in real time. Alpha decays like a physical system Signals have half-lives. Some last months. Some decay in hours. The entire infrastructure exists to capture signal before the market arbitrages it away. Speed matters because alpha is perishable. The real moat is dimensionality Retail sees charts. Quants see tensors. Thousands of correlated assets. Hundreds of hidden factors. Millions of parameter interactions. The edge is not prediction alone. It is managing high-dimensional probability distributions better than everyone else.

@ridark_eth time to deep dive into roblox, now or never !

> Roblox > 2006: ~ $0.10 > 2026: ~ $30 billion > Claude Bot > $200 → $14,100 > me after reading the guide and staying up all night > $5 → $45

@dunik_7 Wow, haven’t seen this masterclass yet - booking it. Thanks for sharing, bro.

our firm fired a junior in February. cited "automation efficiency." we now pay him $4,000/month as a freelancer for the same work. his per-drawing rate is 3x what we used to pay him in salary equivalent. he turns deliverables in 4 days instead of 14. he stamps from his kitchen. he's never been on a video call with us. the senior who replaced him still drafts manually. still goes to the office. still waits for approval meetings. the stack the junior is using is on GitHub. free. open since 2024. we know about it. it's in our slack ai channel. nobody at the firm has installed it. we keep firing juniors and rehiring them as contractors at higher rates. we tell each other it's "efficient." the principal asked me last week why margin is down.

@eng_khairallah1 bro just made another banger, booking !

@zodchiii Damn, bro, another banger read on agents - thanks for sharing.

@thejayden this is legendary lecture, thanks for share Jayden !

The difference between a $60k job and a $300k software role is not skill anymore. As Andrej Karpathy said memory systems, routing, agent orchestration, and context engineering are the stack you need to learn as an AI software developer. Bookmark and watch it.

@cyrilXBT damn bro, what a great read i just had, thanks for sharing !