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Google Brain founder Andrew Ng: "Prompting will be dead in 6 months Agent harnesses built with loops and graphs will replace it" Agent → Harness → Feedback → Loops → Graphs → Self-Improving Systems In this 1-hour Stanford lecture, he explains what the best engineers are building instead and how you can start today Prompt → Run → Verify → Improve The first 20 minutes teach what most $1,500 courses try to sell you For free Bookmark and watch it today Then read the guide below on building an agent harness that improves itself
rari130,010 次观看 • 21 天前

Anthropic hired this engineer at $250K-$750K a year because he knows how to build harnesses for multi-agent systems In this 15-minute workshop, he shows exactly how to build one from scratch AI → Agents → Harness → Loops → Graphs step 1 → start with the Claude Agent SDK - the harness handles loops, context, and sandboxing step 2 → separate the brain from the hands - reasoning in one place, tools in a sandbox, 60% faster to first token step 3 → run it server-side and log every step - close your laptop and it keeps running, crashes resume from the log step 4 → make failure cheap - retry dead sandboxes and replay lost context instead of starting over step 5 → turn yesterday's logs into new memory and skills - the harness wakes up smarter Anthropic calls this "dreaming" Most people spend weeks building this by hand You don't have to Bookmark and watch it Then read the full harness engineering guide below ↓
rari184,775 次观看 • 1 个月前

Anthropic engineer: "90% of our engineers were already running self-improving loops Now everyone is moving toward agentic graphs" "Prompting is basically finished" In just 10 minutes, she builds her complete Claude Code setup live from an empty terminal Agents → Loops → Graphs → Self-Improving Systems Prompting was the old workflow Graph engineering is the next one This 10-minute breakdown is worth more than most $1,000 agent engineering courses Watch it today Then save the full guide below before everyone catches on ↓
rari203,865 次观看 • 1 个月前

Ran into an Anthropic engineer at an airport lounge in Frankfurt last month. SFO delayed six hours. Nothing to do. I had my laptop open. Bot running. Three agents scoring markets in the background. Guy sits two seats down. Glances at my screen. Looks away. Looks back. "Is that Polymarket?" I said yeah. "You're running it with Claude Code?" I nodded. He pulled his chair closer. "I'm on the agent team. We stress-test this exact setup internally. You built it in your kitchen" I asked what stress-test meant. "Red team. We simulate what happens when someone gives Claude raw wallet data and tells it to find the winners. You're running the thing we were scared about" I showed him the scanner. One prompt. Find every wallet with 100 plus trades, 70 plus win rate. Rank by profit. Export top 50. Claude chewed through 14,000 wallets in under 4 minutes. Came back with 47. Top 20 made more than the bottom 13,000 combined. "That's not a distribution. That's a hit list" I said yeah. "And the scoring function?" Claude wrote it. I just wrapped it in an if-statement. A fill landed on screen mid-conversation. +$128 on an ETH dominance market. He stared at it. "How does it decide to enter" Three agents. Shared wallet. No shared memory. Arbitrage, convergence, whale copy. 2 of 3 agree, full size. 1 alone, half. Disagree, no trade. That consensus filter alone killed 40% of losing trades. "And the exit" The 47 whales never hold to settlement. 91% exit early. Capture 73% of max. I cut at 85% of the expected move. Or a 3x volume spike. Whichever comes first. "So you built a whale copy bot that exits before the whales" Yeah. He put his coffee down. "That's exactly the thing we gamed out in March. Management killed the internal version on policy. Nobody outside the team should have shipped this yet" I asked what he was going to do. "Fly home and pretend I didn't see it" $600 seed. 31 days. Net +$35,200. 479 trades. 75% win rate. Sharpe 2.63. I haven't touched the bot in three weeks. Copytrade for those who don't want to build - Before boarding he slid a card across the table. "When the next agent model drops, rerun your prompt. You'll see what I mean"
rari619,502 次观看 • 5 个月前

Anthropic Research Lead: "99% of our engineers run swarms of 300+ self-improving agents" "Close the loop, give the model a way to verify its own output" In a 20-minute session, an Anthropic Team member breaks down how to build agents that improve themselves The real setup is Claude running through loops, plan mode, and dynamic workflows Better than most $300 agent courses Bookmark and watch the talk Then read the article below
rari382,950 次观看 • 3 个月前

Google CEO, Sundar Pichai: "If you don't learn how to orchestrate agents now, you'll spend 2027 catching up to people who started today" In 30 minutes, he explains why the best engineers are moving from writing code to running agents One agent researches One writes One tests One reviews One fixes The human becomes the operator, not the bottleneck Bookmark and watch the interview
rari346,831 次观看 • 3 个月前

Most people think prompting is just writing better sentences Anthropic shows why that's wrong This 32-minute workshop breaks down how prompts are built for production Not prompt hacks Not "act as" Not another $300 course Actual systems Evals Edge cases Model migration Agent loops Good prompt is not one message It's a workflow the model can follow, test and improve This matters because every new claude opus or sonnet will still reward the same rules Watch the prompting playbook Bookmark it before your next bad ai answer is just a bad setup
rari391,609 次观看 • 4 个月前

Google Brain founder Andrew Ng: "Prompting will be dead in 6 months" "Loops and graphs are replacing it" In just 2 hours, he shows how to build agents that work, learn, and improve on their own LLMs → Agents → Loops → Graphs → Self-Improving Systems The first 15 minutes alone are more valuable than most $500 AI courses Most people are still learning prompts while AI engineering is already moving beyond them Watch the lecture first Then read the full guide to loops and graphs below ↓
rari133,727 次观看 • 1 个月前

Andrew Ng: "100% of my tasks now run through AI agents, the hype actually passed my expectations, graphs are the next step" "In 3-6 months, everyone will be using self-improving graphs, prompting alone is over" In a 30-minute talk, Andrew Ng breaks down how to build self-improving agentic systems with graphs Agents → Feedback → Memory → Graphs → Self-Improving Systems Worth more than most $500 graph engineering courses Bookmark and watch the talk today Then read the full article on graph engineering below ↓
rari111,145 次观看 • 1 个月前

I gave Claude one Polymarket equation and told it to find every mispriced contract It hasn't stopped running in 4 months $600 → $14,190 Every Polymarket contract is priced by one formula: C(q) = b × ln(Σ e^(qi / b)) The pricing function inside it is softmax - the same math Claude uses to pick its next token Claude doesn't just understand this equation, it thinks in it So I gave it a task: "Scan every open contract, compute fair value, flag anything the market has wrong 24/7" It finds the gap, sizes the position by Kelly, enters before the crowd corrects Market shows 0.38, math shows 0.57, bot buys Resolution hits, bot collects 120 days 61.2% win rate 2.31 sharpe -3.8% max drawdown 425 trades 87% of Polymarket wallets are underwater They trade feelings against a formula that doesn't bluff, doesn't tilt, doesn't chase losses The edge is having something that reads the math faster than any human - and never stops looking
rari311,933 次观看 • 6 个月前

Got laid off on a Friday Spent the weekend reading Polymarket docs instead of updating my resume By Monday I had 3 agents running on a Mac Mini $500 → $3,140 Before my boss even posted my replacement job listing Weather data is public NOAA publishes forecasts every 6 hours The models are accurate But the market prices contracts off weather apps and vibes That's not a gambling problem That's a latency problem So I built 3 agents to exploit it Agent - 01: Reads raw NOAA forecast grids Not weather The actual meteorological data Agent - 02: Compares NOAA confidence intervals against live Polymarket prices Finds the gap before it closes Agent - 03: Enters the position EIP-712 signature, direct to CLOB on Polygon No middleman, no delay Not because the agents are smart Because the crowd updates slowly And the agents update constantly 71.2% win rate $26.40 average 3.9% max drawdown Built a live terminal to watch it all run in real time Balance, P&L, win rate, active markets - all updating live And the agents report back directly: Agent - 01: Batch filled 12 positions Avg +$26 Edge holding Agent - 02: Cold front repricing 8 markets Entering now Agent - 03: 3 losses in a row Drawdown at 6.8% Need wider capital base to hold variance It's not glamorous It's just a black screen with green text And numbers going up Copytrading open:
rari324,995 次观看 • 7 个月前

NVIDIA CEO Jensen Huang: "Nobody is just writing prompts anymore, the new job is building and running loops" He says this is the shift that defines the rest of 2026 In 23 minutes, he explains why the best engineers are moving from prompting to looping Prompt Output Check Fix Run again That is the new workflow Bookmark and watch the interview Then save the full framework below
rari169,874 次观看 • 3 个月前

Anthropic Research Lead: "99% of our engineers run swarms of 300+ self-improving agents" "Now everyone is building agentic graphs" In a 20-minute session, an Anthropic team member breaks down how graph engineering turns isolated agents into systems that improve themselves The real setup is Claude running through graph workflows, plan mode, and dynamic orchestration Agents → Loops → Graphs → Self-Improving Systems Better than most $300 graph engineering courses Bookmark and watch the talk Then read the article below
rari76,231 次观看 • 1 个月前

My sniper spotted insiders buying the bottom on $JUGGERNAUT Then my phone lit up before the chart did I opened the alert Someone was loading up near the lows Then the pump started and that notification suddenly looked a lot more interesting JUGGERNAUT The sequence → Buying near the bottom → Insider activity flagged → Token tracked → Alert sent before the move That is the kind of notification I want to wake up to A token, the wallets behind it, and a reason to open the chart Drop the next Robinhood Chain token below Let's see who is loading up before everyone starts posting about it
rari44,166 次观看 • 29 天前

Anthropic dropped a free 59-minute Claude Code course From autocomplete to real agents: 00:00 - From autocomplete to agents 04:50 - How the agentic loop works 14:07 - CLAUDE.md as project memory 26:53 - Why Plan Mode comes first 33:31 - Live task from brief to commit 54:46 - Skills vs CLAUDE.md Most people still use Claude Code like a smarter autocomplete This shows how Anthropic uses it to plan, call tools, test, and ship real work Worth more than 99% of paid Claude Code tutorials Bookmark and watch it later
rari120,349 次观看 • 2 个月前

Andrew Ng just released a 2-hour course On building agentic skills from scratch with Anthropic: 00:00 - How to build agent skills with Claude 22:32 - Claude pre-built skills for AI agents 41:07 - Agentic skills vs tools, MCP, and subagents 01:06:06 - Skills for long-running agents This 2-hour watch can replace 10 paid courses on building agents Taught with Anthropic themselves Bookmark and watch it tonight Then read the article below
rari104,612 次观看 • 2 个月前

OpenAI just mass-fired their robotics team. One of the engineers DM'd me 20 minutes later. I didn't know him. He found me through a Polymarket thread. His first message: "I have 30 days of severance and nothing to lose. Let me tell you what we actually use internally. It's not GPT" I thought he was trolling. "Every serious team at OpenAI prototypes on Claude Code. Not ChatGPT. Not the API. Claude Code connected to a repo. That's the actual workflow" I asked why. "Because Claude reads the codebase. GPT reads the prompt. There's a difference. One guesses. The other one understands the full context and builds on top of it" He sent me one link. 86 million Polymarket trades. Every wallet. Every entry. Every exit. Open source. Free. "Point Claude Code at this. Say - find every wallet with 70%+ win rate and 100+ trades. Watch what happens" I did it that night. Claude pulled 47 wallets in 4 minutes. Average profit: $214K. Hold time: 7 hours. 91% exit BEFORE resolution. They never wait for the outcome. "Now look at how they exit" Top wallets capture 86% of the move and cut at 12%. Everyone else captures 58% and holds losers to 41%. Same entries. Completely different results. He sent another link. "Three commands. Your bot sees 500+ markets. No key needed. Read-only. Claude scores them in 20 minutes" I asked why he's telling me all this. "Because I just got fired for saying we should open-source more. So here I am open-sourcing everything I know" Then he sent me an article where someone built the full bot from these repos in a weekend -> Three exit triggers: Target 85% of move. Volume spike x3 - smart money out. 24h silence - thesis dead. I copied the stack. Claude Code $20. VPS $5. $25/month. No team. No office. No GPT subscription. 17 days. 191 trades. 73% win rate. $850 seed. +$9,400. I sent him my results. He replied: "This is exactly what I built as a side project at OpenAI. They made me delete it" I asked if I could post this. "Post it. What are they gonna do. Fire me again?"
rari157,503 次观看 • 5 个月前

4 Anthropic engineers just shared one hour of their best prompting lessons One of the most valuable prompting masterclasses on the internet and it's completely free 14:12 - Real prompts used inside Anthropic 32:33 - The simple fix that improves your prompts 59:44 - How to give Claude the context it actually needs 1:07:59 - The prompt that keeps working while you sleep Spend one hour learning from the people who write prompts at Anthropic Worth more than most paid vibe coding courses Bookmark and watch it tonight Then read the step-by-step guide below
rari77,399 次观看 • 2 个月前

Do not spend 2 years learning AI agents the slow way Andrew Ng just shared a complete 2-hour roadmap On becoming an agentic AI engineer in 2026: 00:00 - Learn the foundations of AI agents 12:12 - Design agentic workflows 53:27 - Build agents that work in practice 1:20:30 - Create self-improving loops 1:30:19 - Orchestrate multi-agent systems Most people are still learning how to prompt one model Andrew Ng is already teaching the complete stack: Agents → Workflows → Loops → Multi-Agent Systems Prompting is the old workflow Building autonomous systems is the new one Anthropic pays top engineers up to $750K a year to understand this stack Bookmark this and give it two hours today Then read the full graph engineering guide below
rari58,117 次观看 • 2 个月前