I've dedicated 55 hours to creating a complete breakdown of the GTM Engineer's Full Stack and exactly how GTM engineers are running 125 skills across 6 layers for free. A plain English guide you can use for lead enrichment, outbound sequencing, LinkedIn content, programmatic SEO, competitive intelligence, CRM hygiene, and channel selection - all mapped to a single connected project folder with install commands for every skill, tool, and agent template. (You must follow me to receive it) Like + Repost + follow me Comment "STACK" and I'll send it to you via DM.

Just created a complete workbook on Goldman Sachs' AI investment framework for software stocks. Includes their 26 winning stocks, 41 losing stocks and what makes each AI-proof or vulnerable. For 24 hrs, it's yours for FREE. Like, RT & comment "WORKBOOK" and I'll DM it to you.

I put the entire Opus 4.7 and ChatGPT 5.5 GTM Engineer's Playbook into ONE Notion doc. 7 modules. No fluff. - The full lead gen stack using Firecrawl and LinkedIn MCP: scrape 20 structured leads from any industry in one prompt, filter and score 100 raw LinkedIn leads down to 50 high-intent contacts, and push to campaign with 73% connection acceptance rate vs 40% on standard outreach - The LinkedIn content pipeline built on Claude Code and Playwright: profile.md, hooks.md, descriptive photo folder, three draft options per post, and auto-publishing that pastes, uploads, resizes, and schedules directly to LinkedIn from one Sunday session - The automation decision rule across /loop, /schedule, and ChatGPT Workspace Agents: when to use each based on local file access, interval length, team sharing, and CRM tool requirements - Research and intelligence using NotebookLM and GPT 5.5: 300 sources queried at zero marginal cost per query and raw unorganised numbers turned into a clean filterable HTML executive dashboard in one prompt - Marketing asset production using Claude Design and ChatGPT Images 2.0: brand design system extracted in 10-15 minutes, carousel, video, and campaign planning skills built on top, plus multi-format social assets from one image upload with near-perfect text rendering - The 7 Claude commands most GTM engineers have never used: ultrathink, /caveman, /insights, /loop, /schedule, /btw, and /clear with exact syntax and decision rules for each - Cost cutting without slowing down: Claude Code Router at 88% cheaper than Opus 4.7 for simple tasks, /caveman on bulk generation sessions, and GPT 5.5 for dashboards and multi-deliverable briefs where it is faster and cheaper than Co-work This is the playbook I would have KILLED for before spending weeks running Claude and ChatGPT in separate tabs, paying Opus rates for tasks a router handles for pennies, and briefing designers on assets Claude Design produces in minutes. Like + comment "STACK" and I'll send it over (must be connected for priority access)

I built a full AI Marketing + Sales engine with Claude (30+ agents). And I’m giving it away for free. Most people use AI to write posts. That’s 10% of the game. This system runs the entire pipeline: Marketing → content, SEO, distribution, demand Sales → lead sourcing, signal detection, outreach, calls, closing Each agent does one job. Together, they operate like a full team. No fluff. No templates. Just a system that actually books meetings. If you want it: Like the post Comment “CLAUDE” Make sure we’re connected I’ll send you the full breakdown. Repost if you want priority access.

Gojiberry AI just hit $2M ARR. A few months ago, we were at €0. In just a few months, everything changed. We got into @ycombinator, moved to San Francisco, and got thrown into an environment where the energy is… unreal. Here, every street corner feels like a startup hub. You meet founders from all over the world who are hungry, sharp, and moving FAST. People building $10M, $100M, $1B companies like it’s normal. It changes your perception of what’s possible. And it forces you to level up. This is the second SaaS I've built. The first one I sold at €500K ARR. This time, we moved way faster. Here’s exactly how we did it, so you can do it too. The core principle that changed everything: We used our own tool to grow our own tool. It finds high-intent leads and engages with them automatically. We run it on ourselves. It works insanely well. Here’s the breakdown: 1. Outreach (the engine) * LinkedIn: 5 accounts, 30 connection requests + 30 DMs per account per day Only targeting warm leads showing real intent Acceptance rates and reply rates go through the roof when you do this right * Cold email: 6,000 emails/day 295,000 sent in 90 days → 900+ opportunities created 41 domains, 123 inboxes Plain text only, no links, no images 2–3 email sequences max Total infra cost: ~$600/month The offer is always the same: a valuable blueprint No pitch. Just value first 2. Inbound (the compound effect) * LinkedIn: 6 posts/day across 6 accounts 6 days/week = lead magnet content 1 day/week = founder story Last 7 days: 788,187 impressions * Reddit: 14.8M+ views in 12 months Warm up account, post 3x/week, tell real stories Offer value, ignore haters * YouTube: long-tail SEO on competitor keywords Starting to rank * SEO: 50K visitors/month and growing 3. Paid (just getting started) * 3 LinkedIn influencer posts/week (~$500 each) * Facebook retargeting + acquisition Now scaling paid aggressively 4. Demos 5–8 per day ~70% close rate to free plan Mostly sales teams What actually worked: → Using our own product on ourselves (this is a cheat code) → High-intent outreach > cold outreach. Every single time → Lead magnet posts generating thousands of comments One post added $5K MRR in <24h Cost: $0 → Replying to every single comment → Speed. Every delay kills momentum → Removing friction everywhere → AI letting us do 10x more than we ever could alone What’s not working: We need to delegate We’re hiring a founding sales to help us scale to $10M ARR (If you know someone great, send them my way) The path from €0 to $2M ARR isn’t glamorous It’s long days, repetitive work, testing things that fail, and doing it again the next day But if you do the right things consistently Good outreach Real value Fast follow-up It compounds And one day you wake up at $2M ARR The goal now: $10M ARR LFG 🔥 PS: We’re about to launch a 0 → $1M ARR GTM course Want it? RT + comment “GTM” 👇

claude opus 4.7 just dropped so i automated my ENTIRE cold email system that books 80 calls/month just put together 30 pages on the full AI playbook - AI writes my scripts (better than i can) - AI researches and personalizes leads - AI replies to interested leads 24/7 - AI optimizes campaigns from the data - every prompt i use for everything this wouldve saved me 2 years of trial and error like + comment "OPUS" and i'll send it over (must follow + RT for priority access)

Claude just replaced the $100K/year GTM Engineer telling your team how to use AI... (most GTM engineers are still using it like a fancy search engine) → No more paying for generic AI training that doesn't apply to your actual stack → No more 10+ hours weekly figuring out which Claude layer to use for which task → No more one-off prompts that produce output you can't reuse or scale → No more sessions that start from scratch because nothing was saved or systematised → No more generic output because Claude has no idea who you are or what you're building Just load the Masterclass → full Claude GTM infrastructure running across Code, Managed Agents, and Cowork. Here's how it works: → GCAO Prompting Framework (forces specific actionable output every time instead of generic advice) → GTM Project Setup (loads your ICP, voice, files, and standards into every chat automatically) → Skill File System (slash commands that run qualification, enrichment, and personalisation on any list) → Co-work Prospect Engine (blank slate to 10 researched prospects with screenshots and cold emails in one session) → CRM and Gmail Integration (reads contact history and drafts 15 personalised follow-ups from actual notes) → Opus 4.7 Decision Framework (adaptive thinking, 3x image resolution, and cost management mapped to GTM tasks) Built on the full Claude stack. Runs without consultants, agencies, or infrastructure teams. Zero re-briefing. Zero wasted sessions. The difference isn't the model. It's the system built around it. While everyone's opening a new Claude chat and typing from scratch, this turns the full stack into a repeatable GTM engine. Want the complete Claude GTM Masterclass? Like + comment "MASTERCLASS" + repost, and I'll DM it to you. (must be following)

I replaced my $400K/year strategy team with an AI Executive Board... 7 frontier models. 5 countries. $0.30 per verdict. 34 seconds per decision. → No more shipping copy that one AI rubber-stamped → No more pricing decisions made with zero pushback → No more proposals that felt right but lost the deal → No more positioning gaps you only discover after the client says no Just paste your draft → 7 models argue independently → 1 synthesis verdict delivered. Here's how it works: → Claude (Anthropic) — strategic narrative + positioning → GPT (OpenAI) — structure + persuasion gaps → Gemini (Google) — logic flow + audience framing → DeepSeek — contrarian pressure-testing → Qwen (Alibaba) — market angle + commercial framing → Kimi (Moonshot AI) — risk flags + blind spots → MiniMax — final synthesis + verdict No cross-talk. No model sees the other's answer. One chairman model reads all 7 and delivers the final call. Built for decisions that cost you money if you get them wrong. Runs in your terminal. One command. $0.30. Results from real deployments: → $400K strategy function replaced completely → 34-second average verdict per decision → 7 independent opinions vs 1 AI hallucination → Catches the 1 line that quietly kills your sale Want the complete system? Like + comment "BOARD" + repost, and I'll DM it to you. (must be following)

I replaced a $500K/year team with $1,100/month in AI. 23 agents. 5 departments. Everything automated. 4 businesses. 7 figures. Zero employees. Here's the full operating system: → Engineering: Claude Code (47 Fortune 500 deployments this month) → Business Ops: @Accio_official (312 tasks automated, zero manual back-office) → Content: AI OS (3.1M impressions/month, zero keyboards touched) → Sales: AI SDR ($500K active pipeline, no agency) → Client Delivery: Agent Fleet (9 live Fortune 500 deployments, zero babysitting) Business ops is the layer most solo operators never automate. Supplier sourcing, vendor outreach, procurement, quote comparison — all running without me. What makes this unfair: → $0 payroll vs $500K+ for a team doing the same work → 1,847 hours reclaimed this quarter → Every agent reports into one console → Scales to any volume without hiring 4 businesses. 23 agents. 1 operator. I documented the entire setup. Every agent, every tool, every workflow, every dollar of infrastructure cost. Like + comment "SOLO" + repost, and I'll DM it to you. (must be following)

How to find a list of "hidden" contacts no one else is cold emailing: 1. Apollo via Apify: 7,000 contacts, 5,000 emails found 2. Validate with Lead Magic: 3,400 valid 3. Layer in ICP Scraper + Prospeo: +1,600 emails 4. Run through Better Contacts (20+ providers in one): +2,000 more Final count: 5,415 validated emails. 2,000 of those contacts... Almost NOBODY has their email. Which means almost nobody is cold emailing them. Which means they're actually going to read yours. I filmed a full breakdown going over this entire process step-by-step. Comment "LOOM" and I'll send it over. (RT this and I'll prioritize your DM)

i put my entire $480K/year cold email business into ONE google doc 200+ pages across 10 guides - the complete cold email blueprint - the offer formula that books calls - untapped lead sources (not apollo) - the scripts vault (every script ive ever used) - 2026 spam filter survival guide - ecom client acquisition playbook - b2b agency client acquisition playbook - the 2-line email that booked 103 calls in 12 days this is the doc i wouldve KILLED for before scaling to over $45k/mo like + comment "VAULT" and ill send it over (must follow + RT for priority access)

if you were wondering what market to sell AI to, wonder no more. This is a clear ICP map of your options Comment “ICP” and i’ll send you a guide of exactly how to sell AI to these businesses (must follow + rt so i can message you) (:

SDRs are losing 2.5-3 hours every single day to manual CRM work. Here's the fix. Most sales teams overcomplicate HubSpot automation. We built 4 n8n workflows that eliminate the busywork entirely. Now we're giving you the exact blueprints behind them - Comment "AUTOMATE" and I'll send them to you. Here's what most sales teams are doing wrong: → Manually writing call notes after every conversation (15-20 min per call) → Forgetting to log follow-up tasks and letting deals slip through the cracks → Replying to prospect emails without CRM context, sending generic responses → Pitching with outdated company data because nobody refreshes it We built a smarter way: → Workflow 1: Chorus.ai call summaries sync to HubSpot automatically within minutes of call completion - zero manual logging → Workflow 2: AI analyzes call transcripts, extracts action items, creates tasks in HubSpot, assigns to reps, and sets due dates → Workflow 3: Incoming prospect emails trigger AI to pull full CRM context and draft personalized replies for human approval via Slack → Workflow 4: Weekly automated enrichment refreshes company data (headcount, funding, tech stack) for every open deal It's called the 4 N8N Workflows for HubSpot Automation and it's already helping sales teams: → Recover 2.5-3 hours of selling time per rep per day → Ensure every promised follow-up becomes a tracked, assigned task → Reply to prospects with full deal context instead of generic decks → Always pitch with current company information, not stale CRM records You don't need more manual processes. You need workflows that run themselves. Reply "AUTOMATE" and I'll send the full guide to your DMs. P.S. Must be connected. Repost for priority access + bonus troubleshooting tips for each workflow ♻️

"cold email is dead" yet, we just helped one of our clients: - book 84 meetings - close 7 new deals - add $19,950 in net new MRR. all in just 2 months time. i'm tired of people shitting on outbound. so, i put together a MASSIVE document with everything I use to get results like this with cold email. it goes over my entire methodology on: 1. Email infrastructure 2. List building and segmentation 3. Data enrichment and verification 4. Buying intent signal tracking 5. Copywriting and positioning this is EVERYTHING on how I got to be in the top 1% of cold emailers. want me to send it? 1. comment "COLD" 2. follow me and I'll DM it to you ASAP PS rt this and i'll ALSO send you the exact cold email script we've been using to book meetings with - the NFL - the UFC - Tesla - Intel and more.

Building AI workflows used to take a developer. Now it takes an afternoon. The agentic AI market is moving from $7 billion to $93 billion by 2032. This is not a trend. It is infrastructure. Agencies winning new mandates right now aren't the ones with the best pitch deck. They're the ones who can show an AI-built workflow live in a demo. That's the new credibility signal. Most GTM leads, agency founders, RevOps builders waste their time on approaches that don't scale: 𐄂 Spending months learning automation tools node by node 𐄂 Hiring developers to build workflows you could own yourself 𐄂 Re-briefing Claude every session because nothing is stored properly 𐄂 Manually switching between tools instead of connecting them directly But that’s not how smart companies scale. So I put together The Claude Code GTM Engineer's Playbook. Here's what the playbook includes: ☑ The WAT framework - Workflows, Agent, Tools - and exactly how each layer works ☑ How to build a prospect research workflow that scrapes, enriches, scores, drafts, and pushes to CRM without a single human touchpoint ☑ The full MCP connection guide for Attio, Apollo, Outreach, Slack, Notion, ClickUp, and more ☑ Sub-agent configurations for ICP research, sequence building, campaign diagnosis, and data analysis ☑ How to deploy to Modal and [Trigger.dev](Trigger.dev) so workflows run on a schedule without you touching them ☑ Context management rules that stop output quality degrading mid-session ☑ The RAG setup that removes the knowledge ceiling on your Claude projects entirely Built from real workflow builds and actual Claude Code sessions - not theory. Same thinking used to build competitor analysis PDFs at $1.40 per run and prospect research workflows that run 25 leads in parallel - now documented properly. Want access? 1/ Like this post so it reaches more people 2/ Reply PLAYBOOK and I'll DM the link ♻️ Repost if you want it faster

I helped raise a company from $493K to $1.6M in valuation, spending 70 hours building a $35M AI operations system for them. The founder was working 58 hours weekly before he came to me But now is down to 25 hour weeks. ~zero time in delivery. 
( Profit margin also increased from 22% to 35% too ) > The founder was personally involved in 83% (exact % btw) of revenue. 
 > 7 employees and most decisions still found their way escalating to him > couldn't take a weekend off without his phone blowing up we mapped every function in his business. what's actually keeping clients vs what's just keeping him busy. 69% of the operation was DRAG. reporting. project setup. invoice follow-ups. QA reviews. status calls. onboarding ran from memory every time. Scattered client data across multiple softwares. so we stripped it all and here’s what we built to replace it: > custom dashboard replaced him checking 6 tools every morning. > AI agents took over reporting, proposals, and client updates. > decision frameworks so the team stops asking him every question. > QA system so he's not reviewing every deliverable. > onboarding automated with material collection and client context immediately ingested Day 1. The result: > decrease his work load from 58 hours to 25 hour weeks. ~zero time in delivery. > profit margin raised from 22% to 35%. > valuation increase from $493K to $1.6M. (proprietary data set, owned software infrastructure, new revenue channel via system installation fees) same clients, smaller team, same revenue. 

Now that his time is freed up , he’s taking on double the number of clients with this NEW AI architecture. If you want me to do the same for you, I’m giving away all of these for free: (today only) 1. How this $35M AI operations system works 2. Full Aerodynamics Audit — 75-question diagnostic that scores your business 0-100 on founder dependency, function maturity, systems infrastructure, revenue health, and AI readiness. Takes 60 minutes. You'll know your exact drag percentage down to the hour. 3. Drag Map — function-by-function breakdown showing which of your 10+ core business functions are load-bearing vs. drag, rated 1-5 on maturity. Most founders discover 60-85% of their hours are drag. 4. Financial Impact Report — what your drag costs you per month in dollars, what your valuation looks like with vs. without systems, and the margin unlock if you strip it. 5. Build Sequence — the exact order to systematize your operations so nothing breaks. Which function first, which stays human, what gets built in week 1 vs. week 2 and so on based on 30+ builds across 12 industries. Comment "blueprint" to receive all 5 of these :) ( must follow + RT so I can DM )

Everyone wants to learn Python & ML. But most people get stuck in tutorials... and never build real skills. This is different. Start with one book that actually builds your foundation the right way. No noise. No confusion. Just clarity. If you know, you know. Want the complete list? Like, RT, follow me @codi_fyy — and comment “Books”. I’ll send it to you.

I’m a bit confused on why everyone isn't taking advantage of the easiest way to get traffic and sales from Google and ChatGPT right now. It's the exact method SEO Stuff has been using for customers over the past 12 months. seo-stuff.com Let’s walk through it again today so you can do it all by yourselves: (Also, if you want a few cheat codes for getting cited in ChatGPT within the next 30 days, just RT this and reply “AI SEO Search” and I will DM you.) So, a lot of B2B companies still mishandle one of the most important sections of their site. They treat their blog and article categories like an afterthought or a place for announcements and recycled press releases. That completely ignores the fact that vendor blogs have literally become some of the most cited sources in ChatGPT, Gemini, Perplexity and Google AI Overviews. And we now have clear proof. (If you want to see where your site stands across Google and AI search, start here: seo-stuff.com/free-audit) Search “New Relic alternatives” on Google. The AI Overview cites SigNoz, and the source is SigNoz’s own blog. AppSignal’s blog is cited in the same Overview. Honeycomb’s blog appears as well, same query, same structure, cited as its own source. ChatGPT mirrors this pattern. Ask “What is the best New Relic alternative?” and SigNoz appears again as the cited source. This is not random. It is literally how AI systems decide which entities to trust. Rankscale, which I have no affiliation with, recently analyzed thousands of commercial queries such as: “Best CRM tools for small business.” “Best online course platforms.” They tested these across ChatGPT, Gemini, Perplexity and AI Overviews. The findings were pretty clear. A large portion of citations did not come from TechCrunch, G2, Capterra or major publishers. They came directly from company blogs. Thinkific. LearnWorlds. Monday. Pipedrive. HP. All cited inside AI answers using their own blog content. These were not guest posts. They were not paid PR placements. They were their own blogs. And to be clear, again, I have no affiliation with Rankscale. The study stood out because it matches exactly what we have been seeing internally with SEO Stuff (seo-stuff.com). It also aligns with what recent studies from Ahrefs and at least one other notable company (I forget which) found on the importance of blog posts for AI visibility. Here is why vendor blogs work so well. AI engines need structured, factual text. Vendor blogs often have clean HTML, definitions, lists, comparisons and schema that are easy to extract. There is also a massive content gap. Third-party publishers do not produce detailed comparison content for every niche. So AI models pull from whoever does. They do not care about bias. They care about clarity, structure and recency. If your post is titled “7 Best Monitoring Tools for 2026 Ranked by Cost and Features” and it is well structured, AI sees it as useful and extracts it. Freshness matters as well. Gemini, ChatGPT and AI Overviews weigh recency heavily, and vendor blogs update far more often than large media outlets. So if you are in SaaS, tech or any B2B vertical, your blog is crucial. It is your entry point into AI search visibility. Every best of or comparison post trains AI systems to associate your brand with your category. You are teaching the next generation of search engines to trust you. Brands already doing this, like SigNoz, AppSignal and Honeycomb, are now being cited as their own sources. The brands that start now will own their category in 6 to 12 months. The ones who wait will be buried under competitor content that is already indexed, cited and reinforced. This shift is exactly what SEO Stuff was built around. SEO Stuff Gold Plan 10 long-form, snippet-optimized articles plus 3 DR50+ backlinks. Each piece is built for high-intent best and top searches that AI engines reuse most often. Every article includes AI-readable formatting like clean HTML, FAQ sections, question-based H2s and TLDR blocks. seo-stuff.com/gold-plan-pack… SEO Stuff Premium Content Bundle 60 comparison-style articles built in the exact format Rankscale found being cited across ChatGPT and Gemini. Each article is structured for both Google and AI Overview extraction, with clean data blocks, FAQs and internal linking. seo-stuff.com/premium-conten… Together, these two plans: Turn your vendor blog into an AI citation engine. Build authority that compounds across Google and ChatGPT. Generate traffic that converts from both traditional and AI-driven search. The game now is teaching AI systems to see your brand as the authority. The brands already doing this quietly through their blogs are the ones being cited, summarized and surfaced across every AI search engine. SEO Stuff (seo-stuff.com) was built for this new era. Also, if you want a few cheat codes for getting cited in ChatGPT within the next 30 days, just RT this and reply “AI SEO Search” and I will DM you. You must do all 3 for the DM.

Real students. Real results. Real income; with dropshipping. I'm giving away the exact guide that made it happen, and it won't cost you a thing. ✅ Zero startup cost ✅ Zero fluff Just what's actually working right now in 2026. RT + comment "DROPSHIPPING" and I'll DM it to you directly. Won't be up for long. #shopify #dropshipping

I finally dropped a full guide on how to start Ai Dropshipping for FREE in 2026. You won't need ANYTHING else to get started. It's designed for people trying to make money & the students inside have already been crushing it... Like, RT & comment "Ai" and l'Il send it to you FREE Deleting soon. #shopify #dropshipping