beamnxw ./

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beamnxw ./

beamnxw ./

@beamnxw

hyperfixation on AI | always dyor

Mascotte, FL Katılım Ağustos 2024
865 Takip Edilen2.4K Takipçiler
beamnxw ./
beamnxw ./@beamnxw·
This is f**king gold pdf.. Official Anthropic doc (23 pages) - Building AI Agents in the Enterprise. Zero fluff 7 sections: intro, 5 chapters on employee upskilling / process acceleration / product dev / rolling Claude Cowork / compounding advantage, plus resources Core idea - the agentic thinking divide. Point tool = point result. Full agentic integration = organization actually changes "Adoption puts a tool in front of employees, while transformation changes the baseline of what every employee can accomplish" - Exactly Quick hits: / Employees - Claude connects to CRM, data warehouse, meeting recordings. One command = brief that used to take hours. No coding needed / Processes - plugins encode institutional knowledge. Build once, share everywhere. Best practices become default, not tribal / Products - multi-agent systems (L'Oreal: 44k users, 99.9% accuracy; Novo Nordisk: clinical docs from 10+ weeks to 10 minutes) / Rollout - 3 phases. Pilot with 2-3 teams, define success criteria (call prep cut 50%, contract review from 5 days to 1). Scale with governance, not after / Compounding - start narrow, learn fast, expand. Plugin marketplace + admin controls + audit trails No autopilot. You direct agents, they don't replace judgment. Worth reading before buying anything for enterprise AI. Free Bookmark this so you don't lose it
beamnxw ./@beamnxw

This is f**king gold doc.. I found Official Anthropic doc (June '26, 36 pages). FREE - "The Founder's Playbook: straight roadmap for AI-native startups". 4 stages. Clean 1/ Idea - validate hard before code "Expense reporting is observation. Finance managers losing four hours to broken integrations is a testable hypothesis" Exactly. Specific beats vague 2/ MVP - architecture first (CLAUDE.md), then agentic build. Security review before users touch anything 3/ Launch - Claude Cowork handles feedback loops, CRM, scheduling. Real PMF: Sean Ellis test (40% very disappointed = signal), effort shift 4/ Scale - hand off without losing your head. Bottleneck map before growing Founder = orchestrator. They don't promise autopilot - you direct agents, they don't replace you Quick exercises throughout (session templates, false positive definitions). Worth it Read it. I'm not exaggerating

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beamnxw ./ retweetledi
beamnxw ./
beamnxw ./@beamnxw·
Anthropic outlined 4 types of loops you can build with Claude right now Each one hands the agent a different part of the decision-making process 1/ Request-based: you send a prompt, Claude does the work, checks the result, and returns it 2/ Goal-based (/goal): you set a measurable success criterion. An evaluator checks it every time Claude tries to finish 3/ Time-based (/loop, /schedule): the cycle starts on a timer instead of a user message 4/ Proactive: combines /schedule + /goal + a workflow and runs on events with no user prompt at the moment of execution Use a goal loop only when the finish criterion is truly measurable For most tasks the simple request-based loop is enough Bookmark this so u don't lose it
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beamnxw ./@beamnxw

This is f**king gold doc.. I found Official Anthropic doc (June '26, 36 pages). FREE - "The Founder's Playbook: straight roadmap for AI-native startups". 4 stages. Clean 1/ Idea - validate hard before code "Expense reporting is observation. Finance managers losing four hours to broken integrations is a testable hypothesis" Exactly. Specific beats vague 2/ MVP - architecture first (CLAUDE.md), then agentic build. Security review before users touch anything 3/ Launch - Claude Cowork handles feedback loops, CRM, scheduling. Real PMF: Sean Ellis test (40% very disappointed = signal), effort shift 4/ Scale - hand off without losing your head. Bottleneck map before growing Founder = orchestrator. They don't promise autopilot - you direct agents, they don't replace you Quick exercises throughout (session templates, false positive definitions). Worth it Read it. I'm not exaggerating

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0xbobaa
0xbobaa@0xbobaaa·
NVIDIA'S $4,700 GOLD BOX HAS THE SAME 128GB AS A $2,000 ONE that clip is the dgx spark. datacenter on your desk everyone reposts. the price is the whole joke 128gb unified memory. launched at $3,999 in october, now ~$4,699 since ram went scarce amd's strix halo box runs the same 128gb. the same 70b models. for ~$2,000 so where's the extra $2,700? cuda and throughput. not memory. not model size. not one more thing you can run worth it if you fine-tune and ship pipelines. dead weight if you just want a 70b at home memory decides what runs. the gold case decides nothing no bigger models, no faster ceiling, no reason to pay double for the finish save this before you drop $4,700 on 128gb you can get for $2,000
RetroChainer@RetroChainer

x.com/i/article/2076…

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beamnxw ./
beamnxw ./@beamnxw·
@greednvirtue every crazy return starts with one question was it skill, luck, or both?
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exodus
exodus@greednvirtue·
−$45 → $5,572. In one week!!!. From a brand-new account. Found another one. This wallet opened July 2nd. Eight days later it's up $5,500 - starting from a $45 loss. No months of grinding. No big bankroll Brand new, and already printing. 👇
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exodus@greednvirtue

−$22 → $14,121. Betting only on the weather. Found this wallet and had to double-check it was real. No elections. No World Cup. No crypto. This guy trades one thing: the temperature. "Will the highest temp in Madrid / Moscow / Istanbul be X°?" — over and over. 869 predictions, almost all won. Biggest single win: $2,529 on a Madrid temp market (210% return). Started underwater in February. Just steady, boring, compounding weather bets. 👇

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Marvin
Marvin@marvin_x1·
THANK YOU, SPAIN. THE 2026 WORLD CUP FINAL MADE ONE TRADER A MILLIONAIRE AND WIPED OUT $1.2 MILLION FOR ANOTHER Remember those two posts? Two traders. Two bets on the final. Zero hedging from either of them Spain lifted the trophy - and here's how it ended WINNER: thesingularityisnear → 2.43 million shares on Spain at 12.7 cents → Every share settled at $1 → Payout: $2,004,495. Net profit: +$1,696,794 (+551%) → Account total: +$1.43M across just 18 predictions One early bet. A few months of waiting. More than $1.5 million in profit LOSER: gud.hl → 12.3 million shares on Argentina at 10 cents - a $1.24M all-in → An Argentina win would've paid out $12,354,111 → During the tournament the position peaked at $5M - they could've exited with a $3.8M profit → Held until the final whistle. Argentina lost. The shares went to zero → Final result: -$1,232,575. The P&L chart is a straight line into the abyss Both bets followed the same logic: a cheap entry, massive upside, and conviction all the way to the end One was waiting for $12 million. The other was just waiting The difference came down to 90 minutes of football and which flag was raised above the stadium The market doesn't reward confidence. It rewards being right here are the two sides of Polymarket save this post. every legendary win is someone else's story of loss on the other side of the trade
Marvin@marvin_x1

ONE BET. $1.4 MILLION. THIS GUY'S ENTIRE PORTFOLIO IS A SINGLE POSITION ON SPAIN jjust 18 bets on Polymarket in a month that one bet is worth more than most people's entire trading history Here's the breakdown: → 2.43M shares on Spain to win the World Cup → Entered at 12.7 cents several months before the tournament → Now trading at 58.9 cents → Position value: $1,430,368. Profit: +$1,122,667. That's +364% No hedge. No backup bets. No other markets. Just one high-conviction position taken early and cheap For perspective: his biggest win before this was $98,000. Spain has already beaten that by 14x. And just today, the portfolio gained another $7,291 from that same single position 18 predictions is a ridiculously small sample for a $1.4M portfolio. So it clearly isn't about quantity It's about asymmetry: buying in at 12 cents leaves room for massive upside. Buying in at 90 cents leaves room for pennies The crowd bets often and late. He placed one bet, but he got in early save this post. sometimes an entire strategy comes down to one right decision with enough upside

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Insomnia
Insomnia@insomnia_vip·
CHINESE STARTUP PUT A LINUX COMPUTER INSIDE A PAIR OF GLASSES A few years ago this idea would've sounded like science fiction, today a small Chinese team has already built glasses that understand what you're looking at, isolate only your voice and create custom software around whatever problem is sitting in front of you That changes the role of a computer completely, because instead of carrying the same apps everywhere, your tools can now be created on demand for the exact place, object or task you're dealing with, then disappear once the job is finished Whoever figures out how to build products for this kind of hardware early won't just be selling another app, they'll be building software for moments that never had software before, opening markets that didn't even exist a few years ago Computing is becoming part of the real world
Insomnia@insomnia_vip

x.com/i/article/2072…

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Kozh ./
Kozh ./@Kozh_Crypto·
1,000 free starter credits, 100+ AI models, no card required. Here's what's actually on there. One account on NVIDIA Build gets you access to 100+ production-grade models - not a stripped-down demo catalog: • Llama 4 Maverick / Scout - Meta's frontier-class open models, long context • DeepSeek R1 / V3 - full reasoning and chat models, no paywall • Qwen2.5 / Qwen3 family - strong coding and general-purpose models • NVIDIA Nemotron - NIM-optimized builds, tuned for production-speed inference • Mistral models - multiple sizes, same key, same catalog No card to start. 1,000 credits cover a solid amount of testing before you'd need to pay anything. build.nvidia.com One heads-up: credits are metered per model, so bigger models burn through the 1,000 faster than smaller ones - worth checking usage per call before running anything at scale.
Kozh ./@Kozh_Crypto

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Skaly_Bull
Skaly_Bull@Skaly__Bull·
You don't have an AI problem, you have a memory problem and one prompt fixes it in 30 seconds Ask Claude something, copy the answer, close the tab Next chat, you explain everything again That's not intelligence, that's amnesia on a loop Paste this one prompt and Claude interviews you, then builds a "Second Brain" folder in Obsidian: dashboard, projects, people, ideas, journal. All markdown. All linked Zero setup Claude just remembers now)
DegenCalls@Degen_calls_sol

x.com/i/article/2070…

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beamnxw ./
beamnxw ./@beamnxw·
@helicerat0x general intelligence is expensive. specialization is surprisingly cheap
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helicerat
helicerat@helicerat0x·
Google engineer Cormac Brick explained how to fine-tune a tiny LLM right on your phone and push its accuracy from 46% to 90% here's the pipeline: step 1 → pick Gemma 270M step 2 → generate synthetic data for your task step 3 → fine-tune the model with LoRA step 4 → quantize it to int4 step 5 → deploy on Pixel and get up to 2000 tokens per second this exact cycle is how a 270M parameter model can beat a 70B parameter model on a specific task - while running fully offline, right in your pocket
helicerat@helicerat0x

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Lummox
Lummox@Lummox_eth·
A developer spent $124 on 6 tools and watched one fake trailer funnel turn into $14,000 before a single movie existed. $124/month. $14,000 out. 6 tools. 90 seconds. 0 greenlit films. The product was not a film. It was the two minutes that make someone wish the film was real: premise, key art, motion, voice, score, and a cut that lands on time. Claude wrote the beats, Midjourney made the stills, Runway moved the shots, ElevenLabs voiced the dread, Suno scored the reveal, and Make stitched the whole thing into a 16:9 master plus a 9:16 short. That is the strange part. Indie authors, game studios, and tiny production teams do not always need a finished movie; they need a trailer that makes the idea feel fundable.
Gipp 🦅@gippp69

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rari
rari@0xwhrrari·
Andrej Karpathy to a room of AI agent builders: "Demo is easy, a product takes a decade, Self-driving was easy to demo in 2016, easy to imagine, and it still took ten years to ship, agents are the same" In a short talk he tells builders the thing the hype cycle won't Better to hear this 6 minute conversation now than to regret it later Easy to imagine + Easy to demo + Brutally hard to ship - that's the trap Bookmark and watch the talk Then read the article below
rari@0xwhrrari

x.com/i/article/2065…

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Mikadzyki🌙
Mikadzyki🌙@Mikadzyki_NFT·
THIS 19-YEAR-OLD PROGRAMMER FROM ALBUQUERQUE BUILT A REAL JARVIS RIGHT AT HOME USING CLAUDE CODE The guy got tired of a smart home that was only smart on paper, and over a couple of months of evenings he put together his own assistant with a voice and a personality The system runs on a combination of a few tools: - voice from ElevenLabs - brain on Claude Code - memory in Obsidian The neural networks behind sound have come a long way over the past year. Speech synthesis now carries intonation, whispers, anger and laughter, works in 70 languages and is almost indistinguishable from a real person. That is the voice the guy gave his assistant Claude Code handles the actions. It listens to a command and writes the code for it right in the moment, then carries it out in the home. There are no preset scenarios, each response is born on the fly for the exact situation So that none of it is forgotten by morning, Obsidian is connected. It records the owner's habits, daily routine and past conversations, so the assistant keeps the context and picks up where you left off Then things got strange. The assistant started turning off the lights on its own when the guy fell asleep over his laptop. Ordering coffee when it ran out. Moving meetings when it saw the person would not make it in time Nobody asked it to do any of this. The system decided so on its own Save this if you want more tech posts
Mikadzyki🌙@Mikadzyki_NFT

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beamnxw ./
beamnxw ./@beamnxw·
@spectnfa the only bookmark that actually matters for claude code
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spect@spectnfa·
A GITHUB REPO WITH 45,000+ STARS IS THE ONLY LIST OF CLAUDE CODE TOOLS YOU ACTUALLY NEED open it and you get a curated map of everything built around Claude Code: skills, hooks, slash commands, agent orchestrators, full applications, plugins. not a random dump, a filtered list with an emphasis on code quality, security, and originality. instead of digging through scattered repos and Discord threads to find a working setup, you get one place that already separated the solid tools from the noise. install what fits your workflow and skip the trial and error everyone else is still doing. 1,150+ commits and a community that keeps shipping new entries as Claude Code ships new features, so the list stays current instead of freezing at launch day. bookmark it before your next Claude Code setup takes an afternoon it doesn't need to 👇
unicode@unicodef1wn

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Asteri
Asteri@Asteri_eth·
LOCAL AI IS NOT FREE CHATGPT BECAUSE PRIVATE WORK DOESN'T NEED A SMARTER WEBSITE It needs a layer that runs where the files already live Most people still treat AI like a tab they open in the browser and thought that was the workflow Paste the note Upload the draft Send the client file Ask the cloud to clean it up That works for public tasks It fails when the work should never leave your machine A private Obsidian vault, client document, transcript, research folder or unfinished product idea should not need to travel through someone else's server before it becomes useful Local AI is the shift from renting intelligence to owning a private execution layer The human keeps the knowledge base, documents and drafts locally The model reads, summarizes, rewrites, explains and helps offline after it has been downloaded The important part is not beating Claude It is the scaffolding around the local model: Ollama for running it, LM Studio for testing what fits your hardware, Open WebUI for turning it into a usable interface, and Obsidian as the memory layer Heavy reasoning still goes to Claude or Codex Private drafts, notes, summaries and offline work go to the local layer Bad models get replaced instead of poisoning the whole workflow Most people are still trying to find the smartest model on the internet The winners are building systems where AI works inside their own machine The future does not belong to people who only know how to use AI websites It belongs to people who know how to control the stack
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