J.B.
@VibeMarketer_ • 38,022 subscribers
ai systems for content, media, and growth
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call me crazy but the first AI agent most companies should build is an autonomous analyst. you can build one using Kimi K3. it watches your competitors while you sleep, remembers every move, and wakes your team with the launches, pricing changes, and positioning shifts they need to act on. don't bookmark this if it crosses your timeline. paste the full article into Kimi and tell it to build the first version for your market.
J.B.1,087,797 次观看 • 2 个月前
ok. kimi k3 is insane. you can build an autonomous analyst that runs your entire competitive intelligence operation while your team sleeps. here’s how to do do it: 1. give it the market: “build a context graph containing every competitor, product, launch, price, integration, positioning claim, and trusted source in my market.” > now the analyst has one living map of everything your team tracks. 2. put it on watch: “compare today’s evidence with the current graph. ignore anything unchanged. surface only new, updated, disputed, or stale information.” > your team stops reading repeat research and wakes up to the changes worth caring about. 3. connect each change to an action: “for every material change, identify what it affects and which team should respond.” > a pricing change updates the battlecard. > a new integration creates a partnership opportunity. > a positioning shift gives marketing something to counter. 4. make every correction permanent: “when a human corrects a fact, source, relationship, or rule, save it and apply it to every future run.” > the analyst stops returning with the same mistakes. > kimi keeps that entire map current and brings your team the few moves worth acting on with the evidence behind them. don’t leave this sitting in your bookmarks. open the post below, paste the full article into kimi, and tell it to build the first version for your market.
J.B.711,874 次观看 • 2 个月前
this is hands down the fastest way to make everyone on your team better with AI: build a shared Company Brain. your best prompts, decisions, corrections, and workflows become the default for every person and AI agent. Claude, Cursor, Codex, and every teammate start from the same playbook. one person learns something once. the whole company gets smarter. the full guide to building your own Company Brain is below:
J.B.354,371 次观看 • 1 个月前
Vercel CEO Guillermo Rauch thinks the future of multi-agent work may look like one agent. Vercel gives employees one front door. behind it, the company harness routes each request to the right knowledge, tool, or specialist agent. employees shouldn’t need to understand the agent architecture. they should just ask the company. here’s how to build the shared harness behind it.
J.B.114,312 次观看 • 2 个月前
McKinsey wrote a whole report about the AI-native marketing team. most good research gets consumed once and then disappears into the content void. for growth marketers, that feels like a waste. the same idea can travel a lot further when you rethink the format, not just the message. so I gave it to Framer's Agent and asked it to make the report interactive. it turned the research into a visual field guide for what an agentic marketing org could actually look like all built + iterated directly inside Framer feels like a much more interesting way to consume research than another 20-page PDF
J.B.33,853 次观看 • 29 天前
call me crazy but company knowledge should look more like this. > every file becomes a node > every import, call, and dependency becomes an edge > every answer points back to the exact code behind it click one class and the system shows what it depends on, what depends on it, and where it sits inside the architecture. now apply the same idea to the company: decisions. projects. people. policies. workflows. learnings. AI should not search through a pile of documents and guess how they connect. it should navigate the company as a system. don't bookmark this if it crosses your timeline. paste the full article into your agent and tell it to build the first version for your company.
J.B.57,687 次观看 • 1 个月前
Claude just became your personal automation engineer. (This will change how you build in n8n forever) using n8n’s new MCP server, you can now describe a workflow in plain English… and Claude builds + deploys the entire n8n workflow for you - automatically. you can now: - build full workflows in plain English - deploy straight into your n8n instance (no JSON copy/paste) - spin up custom agents for ads, inventory, email, Slack - whatever - ship automations 10x faster, with 0 tech bottlenecks this is like having a full-time backend engineer for $20/month want the full Claude setup + install guide? comment “AUTOMATE” + follow + repost and I’ll DM you everything (must be following so I can DM)
J.B.380,580 次观看 • 1 年前
Alex Hormozi says his AI SDR is already matching the performance of his human team. but the agent did not learn how to sell from a prompt. his point is that businesses compare a half-built AI workflow with a sales process refined over many years, then blame the AI when it falls short. the same applies to outbound. if your ICP, offer, exclusions, qualification logic, customer examples, and approved claims only live in your head, the agent has to invent the strategy account by account. you can build a Hermes agent around that playbook instead. it turns a raw market into a ranked pipeline of qualified accounts, matches each account with the right buyer, and writes outreach grounded in the sales process that already works for your business. the full system is inside the article below:
J.B.63,888 次观看 • 2 个月前
ok so i finally got this working bulk ad creation > configure once > push to meta, tiktok, snapchat > all live in minutes here's the setup: told claude code to build a bulk ads launcher using the meta, tiktok, and snapchat APIs what it does: -> add as many ads as you want. each with its own creative, copy, CTA. -> set shared defaults across all ads. override individual ones where needed. -> upload 4:5 for feed, 9:16 for stories/reels. per-ad placement optimization. -> launch into a new campaign, new ad set, or existing ad set. your choice. -> push to one platform or all three at the same time. -> all meta auto-enhancements turned OFF by default. no more clicking through every single ad to disable advantage+ creative, music, text optimizations. it's just off. (this one was for all my media buyers out there) -> auto UTM tagging on every URL. source, medium, campaign, ad set, ad name. no manual work. -> structured naming conventions. brand, product, concept, creator. ad accounts stay organized across platforms. -> media flexibility. upload files, paste URLs, or drop google drive / dropbox links. it handles all of it. -> campaign config in one screen. objective, budget, optimization goal, bid strategy, targeting. -> launch as active or paused. preview everything before pushing. -> per-ad error handling. if one fails, the rest still launch. you see exactly what happened. what used to take 2+ hours clicking through three different ad managers now takes 10 minutes. drag in creatives. set config. select platforms. hit launch. done.
J.B.145,447 次观看 • 7 个月前
nobody likes building out an n8n workflow from scratch... that's why I turned Claude into my personal n8n builder I just tell it what kind of flow I want (or drop a screenshot) and it: – builds the entire thing – adds full documentation – leaves sticky notes explaining each node want the Claude prompt + cheat sheets to set this up? like + comment “claude” and I’ll send it over (must be following so I can DM)
J.B.276,181 次观看 • 1 年前
i genuinely don't understand why everyone isn't doing this yet someone ran Kimi K3 through 8 different agent harnesses on the same 25 tasks. the takeaway is to stop switching models and rather build the environment around the model you use. my setup takes an afternoon: > write a task contract: what must exist, what must not happen, what proves it's done > give it a context map, not an instruction dump. it loads the files the step needs, nothing else > split the tools: read and edit run free. publish, spend and deploy wait for your approval > split the roles: a researcher, a builder, and a verifier whose only job is to reject the work > keep project state in a file, not the chat. a fresh session picks up exactly where the last one stopped > add a stop hook: kimi cannot say finished until the deliverables exist and the checks pass the people running this have agents that actually work. everyone else has an impressive demo that falls apart on real work six months from now they'll have a harness that survived hundreds of runs and got sharper on every one. you'll have a folder of prompts full step-by-step guide below bookmark this before the feed buries it
J.B.31,943 次观看 • 1 个月前
Ryan Carson just gave Greg Isenberg the clearest picture i've seen of where companies are heading. he once ran Treehouse with 110 employees. his new company, Untangle, has one. revenue was on track to 4x that month. the company with 110 employees taught him how to manage people. the company with one is teaching him how to manage agents. that means: > give every agent a clear outcome > let several work in parallel > check the work > automate what repeats > step in for the decisions that still need you the biggest companies of the next decade could be run by the smallest teams. the article below shows how to build the operating layer behind one:
J.B.32,725 次观看 • 1 个月前
I used this n8n workflow to scrape X for top-performing posts in my niche (it's a big part of how I went from 600 → 6k followers in 13 days) most creators scroll for hours to find content ideas that work... whereas I just run this flow and get a full swipe file in minutes - organized by likes, comments, shares and URLs. here’s what it does: - drop in a keyword - scrapes X for top posts - pulls engagement data + content - auto-sorts it all into a Google Sheet now you've got data-backed insights ready to plug into your tweets, ads, or even video scripts. workflow takes 5 minutes to set up want the full JSON? comment “SWIPE”, follow, + repost and I’ll send it over (must be following so I can DM)
J.B.181,088 次观看 • 1 年前
you should spend an afternoon building a second brain with jev... here's how i'd set it up: > create one inbox for saved posts, articles, meeting notes and ideas... give your agent access to it > give jev your active projects and interests so it can sort incoming material into categories that mean something to you > have your agent find similar notes, then use jev to flag duplicates and spot which ones add something new > save everything with its original link and date so you can always check where it came from > whenever you start a task, have your agent search the archive and let jev score which notes are relevant > feed those into your writing agent before it starts working... your customer conversations, examples and previous decisions are already there writing a proposal? bring back what the customer said on the call and the case study that answers their objection. working on a post? pull up the idea you saved three weeks ago alongside your own notes on the topic. start with one project and the material you've already collected for it. ask your coding agent to build that workflow, then check what it brings back on your next real task.
J.B.13,511 次观看 • 29 天前
the best way to find ad ideas, is to scroll TikTok, but nobody wants to do that for hours on end... so I built an AI agent that can do it for you, completely hands-off just give it a keyword and it: – scrapes the top-performing TikToks – pulls the pain points, trigger events, and emotional hooks – rewrites the viral script for my product or service want the full n8n flow + set up guide? like + comment “script” and I’ll send it over (must be following so I can DM)
J.B.134,956 次观看 • 1 年前