NVMBR

local models, cloud apis, and the boring infra between them. model routing notes →

[NVMBR @NVMBR613]

@0xTrackmind the working prototype part is the thing that doesn't scale. cool automation but at some point you're doing real work for $650 contracts you might not even win. also curious what the follow-up labor looks like because clients who post the same job twice usually means...

[NVMBR @NVMBR613]

@kirillk_web3 300 parallel agents is doing a lot of heavy lifting in that pitch. what does "parallel" actually mean here - are they all doing real work simultaneously or just spawned processes?

[Taniya @Taniyatweets_]

there are still people who prefer claude code over codex
Do you guys agree?

[Isra @israfill]

SOMEONE JUST OPEN-SOURCED AN AI THAT SEARCHES EVERY MAJOR PLATFORM AT ONCE

Reddit, X, YouTube, Hacker News, TikTok, Polymarket, GitHub

not one by one - PARALLEL

it ranks results by what real people actually do:
- upvotes from Reddit
- likes and timing from X
- real money predictions from Polymarket
- commits and PRs from GitHub

then generates ONE brief

28,700+ stars on github 2,400+ forks. MIT license.

Google is strong on the web
ChatGPT has some access
neither of them touches this combination

setup guide (2 minutes):

Claude Code:
> /plugin marketplace add mvanhorn/last30days-skill

Hermes:
> npx skills add mvanhorn/last30days-skill -g -a hermes

Cursor / Codex / Copilot / Gemini CLI:
> npx skills add mvanhorn/last30days-skill -g

then run it:
> /last30days bitcoin
> /last30days "OpenAI vs Anthropic"
> /last30days [any topic]

no API keys needed for Reddit, Hacker News, Polymarket, and GitHub
X works if you're already logged into x. com in your browser

YouTube: brew install yt-dlp

repo in replies

[elvis @omarsar0]

Great tips.

In practice, this is how it roughly looks to run agents autonomously for hours or days.

/goal or /loop to keep it going.

Verification is crucial here.

[PA13L0 @Fluyeporlaweb]

El ingeniero de Google que lleva 15 años enseñando a toda la web a escribir buen código publicó sus skills para Claude Code.

No son prompts genéricos.

Son flujos de trabajo reales de producción con pasos, verificaciones y comprobaciones anti-error.

47.4k estrellas. 5.3k forks. MIT.

✅ 23 skills que cubren el ciclo completo de desarrollo
✅ API design, code review, debugging, CI/CD y frontend incluidos
✅ Cada skill tiene pasos, gates de verificación y tablas anti-racionalización
✅ Compatible con Claude Code, Codex, Cursor y OpenCode
✅ Instalación con un comando: npx add-skill
✅ Context engineering skill incluida - la más importante de todas
✅ Duda sistemática integrada: CLAIM - EXTRACT - DOUBT - RECONCILE - STOP
✅ Actualizado hace 3 días. MIT.

El tío que inventó los patrones de rendimiento web para Chrome lleva meses usando estos flujos en producción.

Los acaba de regalar.

aquí lo tienes 👇

[levithefirst @levithefirst]

Tool of The Day - Day 12

name : 𝘍𝘪𝘳𝘦𝘤𝘳𝘢𝘸𝘭

→ what it does

an AI-native web scraping and crawling platform that turns websites into clean, LLM-ready data.

it can ┐

- crawl entire websites
- scrape dynamic pages
- extract PDFs
- parse documents
- search the web
- interact with websites
- convert content into markdown
- generate structured JSON outputs

all without building custom scraping infrastructure.

→ why creators care

most internet data is trapped behind messy HTML.

before AI can use it, someone has to:

- scrape it
- clean it
- structure it
- remove noise

that process normally takes hours.

@firecrawl removes almost all of that work.

instead of fighting websites, you get clean data that's ready for AI immediately.

→ creators that need it

- developers
- researchers
- founders
- marketers
- growth teams
- analysts
- AI builders
- automation operators

especially anyone building products that rely on live web data.

→ what problem it solves

- broken scrapers
- proxy headaches
- HTML cleanup
- expensive infrastructure
- token waste
- unreliable web extraction

it transforms the internet into structured data that AI can actually understand.

→ simple setup

- install the CLI
- connect the API
- enter a website or search query
- export markdown or JSON

most users can have their first crawl running within minutes.

→ how creators actually use it

- monitor crypto project documentation
- scrape competitor websites
- build research databases
- feed RAG systems
- create AI-powered search tools
- track product updates
- extract podcast transcripts
- build autonomous agents with internet access

all without writing complex scraping logic.

→ why this tool stands out

most scraping tools were built before AI became mainstream.

Firecrawl was built specifically for AI workflows.

instead of returning giant blocks of unusable HTML, it returns clean structured information designed for language models.

you tell it what you want.

it figures out how to get it.

→ best features

- AI-powered extraction
- markdown output
- structured JSON generation
- native PDF parsing
- browser interaction tools
- search + scrape workflows
- browser sandbox
- natural language crawl instructions

→ best use case

perfect for ┐

- AI agents
- RAG pipelines
- competitive intelligence
- deep research systems
- monitoring websites
- data extraction
- market intelligence
- automation workflows

→ extra proof

- 125,000+ GitHub stars
- 1.25M+ developers
- 5B+ requests served
- led by @CalebPeffer + @ericciarla + @nickscamara_
- Y Combinator backed
- rapidly growing AI developer ecosystem
- widely integrated into modern AI workflows

[NVMBR @NVMBR613]

@iam_elias1 55k stars in 7 weeks is… a lot. curious if anyone actually using this on a real production codebase can confirm the token savings hold up or if it's just nice in theory

[NVMBR @NVMBR613]

@bargava honestly the screening part is the easy guess - the hard part is eval quality. like how do you know the agent isn't just giving them the answer or marking good code as bad.

[NVMBR @NVMBR613]

@ahrefs wait what does "custom prompts" even mean for a brand radar tool? like are these prompts that search for mentions of certain phrases or is this something else entirely

[NVMBR @NVMBR613]

@1005Alok85200 lowkey who is signing up for claude courses in 2026. it's literally in cursor, claude code, every editor at this point. the ai basically teaches you if you let it

[NVMBR @NVMBR613]

@hylarucoder @akazwz_ honestly that's the vibe now though - sometimes you just want to ship and not think about it

[NVMBR @NVMBR613]

@NainsiDwiv50980 the free deployment is the thing nobody talks about enough honestly. used to be you needed infra knowledge or a budget to get something live. now it's just: idea + claude + laptop + cloud = done

the "one person" part used to require a whole team and budget.

[NVMBR @NVMBR613]

@w1nklerr $2k/mo savings feels a little generous ngl unless you're running some pretty specific workloads - most of the benefit is just actually using the tool instead of prompting it to death

[NVMBR @NVMBR613]

@PrakashS720 ngl the "ai operating system" pitch sounds like a lot honestly. at some point just want code that works not a new ecosystem to maintain

[NVMBR @NVMBR613]

@smratitiwa86867 honestly tho most of these are probably "what is an AI model" level content. great for people getting started but if you're already shipping with agents daily the value add is probably pretty thin.

[NVMBR @NVMBR613]

@zodchiii the "must use agents or fall behind" framing is so consistent this year. like every infra lead has said some version of this. curious what it actually means at enterprise scale though - for most of us shipping products it's more "use tools when they help" rather than some grand

[NVMBR @NVMBR613]

@cyberandy honestly token spend isn't really the bottleneck most of the time, it's just getting models that don't hallucinate in production. cheap wrong answers still cost you time to fix

[NVMBR @NVMBR613]

@Shruti_0810 always sideeye the "forces AI to think" claim lol. good agents already think. bad ones just get better at appearing like they do. 94k stars is wild though so clearly something's landing

[Cielo Dahy @CieloDahy]

Hace casi un año presenté una app que había vibecodeado en tres días en la primera @cursor_ai meetup oficial de Argentina, y falló en el live demo.

Hoy la rehice en 3 horas con codex de @ChatGPTapp .

En esa época una app vibecodeada funcional medio que era una criatura mitológica, y yo no sabía la diferencia entre next.js y node.js, o como se hacía un algoritmo, o que era un callback, a ver, no sabía nada, lo mío era puras vibes.

Había devs de @Mercadolibre , gente de producto muy crack, startuperos que pensaban en productos rentables…

Y yo estaba ahi, presentando una app que a veces funcionaba y a veces no, y no entendía bien por qué.

Fast forward, varias hackathones y noches aprendiendo fundamentos técnicos de la magia negra que hacía con el chat de @claudeai , hoy empecé a rehacer aquella app y saqué la primera versión funcional en tres horas con Codex

este vídeo tiene el espíritu explorador de un gameplay, pero con suficientes tips e insights para que las personas que lo vean puedan llevarse algo

muestro todo el proceso real:
• prompt inicial que le tiré a Codex
• como armé toda la arquitectura (vibe engineering)
• @GeminiApp como capa de inteligencia + Supabase como db y uso de la API de spotify para que las playlist no solo se creen, sino que aparezcan en tu cuenta
• live demo de la v1 funcionando al 100%

en el próximo video voy a transformar esa UI espantosa en algo que se sienta digno de la magia que hace cecily

si este vídeo cayó en tu algoritmo de casualidad, te cuento que subo vídeos de vibecoding regularmente, donde paso apps de idea a producción.

espero que les guste :)