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My 2-part strategy to keep a competitive advantage in the age of AI: 1. Keep building valuable skills unrelated to AI 2. Use AI to amplify those skills for more output

@LoganTGott SYSTEM

I've been running an experiment for the last 6 months. I stopped writing LinkedIn content manually and rebuilt my entire workflow inside a single Claude project. Profile rewrites, weekly posts, lead magnet funnels, outbound DMs, sales call mining, all running off one connected system. The results have been absurd. So I documented the whole thing. Introducing the Claude LinkedIn Authority System. The exact setup, prompts, and 30-day sprint I use with SaaS and AI founders to turn their profile into a lead generation machine inside Claude. Here's what's inside the system: → 3 ways to plug Claude into your LinkedIn workflow (Claude project, Claude Code, API) → The content engine ICP > profile > 7-post weekly system > lead magnet funnel → 10 ready-to-run prompts profile, content, outbound, all sequenced → The Brand Intelligence Database a system prompt that learns your voice and generates on-brand content forever → The sales-call-to-content loop 10 transcripts in, 7 posts out, in one session → 30-day execution sprint week-by-week schedule from foundation to outbound to optimization Backed by 500+ calls booked for SaaS and AI founders running this exact workflow. Free for 48 hours. Like + comment "SYSTEM" and I'll DM it. (Must be following so I can DM you)

@OmkarKumar43797 YT

Going viral on YouTube is easy. Making money is not… (unless you have a system) Here’s what actually works 👇 Most creators: • Post random videos • Spend hours editing • Quit after a few days Smart creators do this instead 👇 Claude AI + YouTube = Content machine + income 💰 🎯 Step 1: Pick a profitable niche Ask Claude: “Give me 5 profitable YouTube niches with high demand” 💡 Step 2: Generate viral ideas “Give me 10 YouTube Shorts ideas in this niche” 📝 Step 3: Create scripts “Write a 30–60 sec script with hook + story + CTA” 🎬 Step 4: Create videos fast → AI voice or your voice → Stock clips + subtitles → Simple editing (CapCut) ⚡ Step 5: Upload & scale Post 1–2 Shorts daily Consistency = growth 📈 💰 Monetization: • YouTube Shorts revenue • Affiliate links (description) • Digital products • Brand deals 30 days of this = real results 👇 → First viral video → Subscriber growth → Income starts Most people try once and quit. That’s why they never win. I built a full YouTube AI system (Claude-based) Comment “YT” and I’ll send it 🚀 #YouTubeGrowth #AI #MakeMoneyOnline #ClaudeAI @OmkarKumar43797

Upload any viral video to Claude. It will: > analyze it frame-by-frame > reverse-engineer why it blew up > build a full storyboard for YOUR version > design scene mockups, write animation timing, voiceover, audio cues > package everything into a production-ready PDF I just did this with a startup launch video that went viral. 10 minutes later: 16-page storyboard, 10 scenes, vector previews, easing curves for every animation. Competitor analysis → creative brief → production-ready storyboard. This is insane

CLAUDE can now build you a YouTube channel from scratch. Like, an actual channel. Niche, scripts, thumbnails, strategy — all of it. Here are the 7 prompts to go from zero to monetized in 90 days:

how to write better copy than 99% of websites on the internet (give this image to AI for your next ad/landing page/etc)

been using this 5-step process to steal high-intent clients from competitors on LinkedIn full process explained below👇 (bookmark + save for later)

@Bogzabs96 SCRIPT

Claude is INSANE for ad scriptwriting. I've built a file with 10 prompts we're testing, with examples. We’re even currently working on how to even remove all AI tells with the anti-ai scripts.md. Inside the mini-guide: - The 10 prompts - The anti-ai scripts md - Worked examples Want a copy? Like + Comment "SCRIPT" and I'll send it over ASAP (Must be following)

Start lore-maxing your life. Build a rich personal story, fill your life with interesting experiences, skills, and knowledge so that you become a person with depth and good Lore. Imagine you're like you're a game character, and you're not just surviving, you're collecting cool chapters for your story learning new things, trying new hobbies, traveling, building meaningful relationships, developing taste, reading, creating art, etc. Start lore-maxing your life.

@DinScales26 arif

recruitment is a $200B industry and 90% of agencies are still sourcing candidates the EXACT same way they did in 2015 we signed 5 staffing clients in one month and hit 103 replies from 880 cold emails in CNC manufacturing alone just dropped a 20-page playbook on how we do it differently: - scraping boards indeed doesnt index - bulk inmailing 400+ candidates/day - ghost broker model - job post arbitrage - hiring signal targeting - 880 emails → 103 replies (CNC manufacturing) - 5 clients signed in one month - message templates for every method like + comment your name and ill dm it

🚨 Microsoft just open sourced a voice AI that was too dangerous to keep live. They took it down. Added watermarks and safety controls. Then re-released it. For free. It's called VibeVoice. Microsoft's frontier open source voice AI. Clone any voice from 10 seconds of audio. Generate 90 minutes of multi-speaker conversation. Real-time streaming. All running locally on your machine. No ElevenLabs. No $99/month subscription. No per-minute pricing. Here's what this thing does: → Text-to-speech that sounds indistinguishable from a real human → Generate up to 90 minutes of audio in a single pass → 4 distinct speakers in one conversation with natural turn-taking → Clone any voice from just 10 seconds of audio → Real-time streaming TTS. First audio in ~200 milliseconds. → Speech-to-text that processes 60 minutes of audio in one pass → Identifies who said what and when. Speaker labels + timestamps. → Supports 50+ languages for transcription → Custom hotwords for names, technical terms, domain-specific accuracy Here's the wildest part: Give it a podcast script. It generates a full multi-speaker conversation that sounds like two real humans talking. Natural pauses. Emotional nuance. Turn-taking. 90 minutes. One command. Microsoft had to take this repo down once because people were misusing it for deepfakes and disinformation. They brought it back with embedded watermarks, audio disclaimers, and safety controls. That's how powerful this is. A $3 trillion company built it. Released it. Pulled it. Fixed it. And gave it back to the world. ElevenLabs: $99/month. Play.ht: $39/month. Amazon Polly: pay per character. This: Free. Local. MIT License. 23.5K GitHub stars. 2.6K forks. Backed by Microsoft Research. 100% Open Source.

Stop asking AI to write LinkedIn posts. Do this instead: 1. Mine your voice before you write ✦ Paste your 10 best posts ✦ Ask for tone and themes ✦ Save the profile. Reuse it forever. "Pull my last 10 posts. Map my sentence patterns and recurring themes. Save it as a voice profile I can reuse." Generic AI averages everyone. Specifics are the moat. 2. Stock a content bank ✦ List 5 recent wins or hot takes ✦ Tag each with lesson, emotion, angles ✦ File by reader pain point "Here are 5 moments from my work this month. For each, pull out the lesson, the emotion, and 3 angles to write from." Real names and exact numbers AI cannot copy. 3. Generate hooks, not posts ✦ Ask for 10 hook variations ✦ Cut anything over 12 words ✦ Pick the one with a number in it "Write me 10 scroll-stopping hooks for [topic]. Under 10 words each. Specific and curiosity-led." Aim for 6 to 7 words. Short beats clever. 4. Map the structure ✦ Pick the winning hook ✦ Outline before you write ✦ 3 key beats. No more. "Outline a post for [idea]. Hook, 3 beats, transition, closing line that drives action. Nothing else." Re-hook on line 2 to force the "see more" click. 5. Stack your proof points ✦ Claim in one line ✦ One stat, one story, one contrarian take ✦ Cut anything you cannot source "I want to make this point: [X]. Back it with one stat, one story from my own work, and one contrarian angle." Disagree with the obvious. Tension stops the scroll. 6. Reformat for the feed ✦ Sentences under 55 characters ✦ Blank line between each beat ✦ First 2 lines carry the whole post "Reformat this draft for LinkedIn. Break lines. Cut filler. Make it scannable in 20 seconds." White space chunks ideas into bite-sized beats. 7. Strip the AI tells ✦ Cut clichés and rhetorical questions ✦ Kill em dashes and filler words ✦ Active voice. Zero adverbs. "Scan this for AI giveaways. Kill rhetorical questions. Cut robotic phrasing. Rewrite any cliché in my voice." Read it aloud. If it trips your tongue, it trips their eyes. 8. Lock it into a system ✦ Save the full prompt chain ✦ Build a reusable skill ✦ Run it for every new post "Turn this whole chain into a custom prompt template. One input. Eight outputs. Reusable for every post." One template kills 80% of blank-page dread. Most people type "write me a post about X." Then wonder why it sounds like everyone else. These 8 prompts keep your ideas intact. AI shapes them. Prompts alone won't build a system. You need: ✦ Voice learning that sounds like you ✦ Idea generation from your past content ✦ Output that reads human, not robotic That's what Stanley does. Try it → lnkd.in/eDh9YRNc

Most SaaS founders fail because they scale acquisition too late. We did the opposite. We focused on distribution before product perfection. That’s how we went from $0 to 2,000+ paying customers in 9 months with 0 outside funding. Here’s the exact growth system we used at GojiberryAI: STEP 1: Validate demand before building Most founders spend months building features nobody asked for. Instead: we started selling before the product even existed. We created a simple 7-slide deck: • the problem • the workflow • the expected result Then we started outbound immediately. Using GojiberryAI + manual sourcing, we targeted high intent leads through LinkedIn and cold email. Weekly targets: • 180 LinkedIn invites • 1,000 cold emails • 4-8 demos per day That was enough to validate demand. The signal we looked for was simple: people asking: “How much does it cost?” Before the SaaS existed, we were manually selling curated high intent lead lists. Once enough companies bought repeatedly, we automated the workflow and turned it into software. The goal at this stage is not scale. It’s getting your first 100 customers as fast as possible. STEP 2: Turn customer results into growth Once customers started getting results, distribution became easier. Our biggest unlock: Reddit. Not ads. Not SEO. Not partnerships. Just giving massive value publicly. What worked: • commenting on viral posts • sharing tactical breakdowns • posting real customer wins • explaining exactly how we generated pipeline No corporate branding. No polished marketing language. Just actionable content. At the same time: we kept outbound running aggressively every single day. First hires: 3 Customer Success Managers. Retention and customer wins became growth loops. STEP 3: Build an inbound engine Once we crossed ~$25k MRR, we doubled down on LinkedIn. Every person on the team: • posted daily • handled outbound daily We only published lead magnet style content: • frameworks • templates • playbooks • case studies • experiments And every post had the same CTA: “Comment X and I’ll send it.” That single mechanic generated thousands of inbound leads. Every week, each team member created: • 1 new lead magnet • multiple distribution angles from it We also added: • free tools • customer stories • motion design videos • better landing pages New hire: 1 Product Manager. STEP 4: Layer distribution channels At this point, the system already worked. Now the goal became: add more attention sources. We expanded into: • X/Twitter • LinkedIn influencers • newsletter sponsorships • partnerships But we never stopped the channels that already worked: • outbound • Reddit • LinkedIn content Most founders abandon winning channels too early. We scaled them harder instead. STEP 5: Scale paid acquisition Once the organic engine was stable, we added: • Meta Ads • Google Ads • UGC creators • B2B influencer campaigns Then we redesigned the entire website around conversion. At the same time: we scaled hiring across: • growth • engineering • sales And massively increased outbound volume with GojiberryAI. Our philosophy is simple: More targeted attention → more conversations → more demos → more customers Most startups die from lack of distribution, not lack of product. Build distribution earlier than everyone else. That changed everything for us. If you want to try GojiberryAI with a 14-day free trial instead of 7 days: Comment “GOJI” and I’ll send you access.

How to bullshit your way into any market in 72 hours People overcomplicate offer creation and spend weeks “thinking” They guess pain points instead of talking to the people who actually have them If you want to launch fast, use the Interview Method Show up as someone working on a research project, a white paper, or a study on the state of the industry Not as someone trying to sell “Hey mf, I’m currently working on a research project mapping 2026 growth strategies in the {{niche}} industry. Your expertise in {{specific sector}} would be valuable to include. When would you be available for a short interview this week?” This angle works insanely well because entrepreneurs have an ego problem, and they LOVE talking about themselves Being “featured” in a study or “interviewed” for their expertise strokes their identity So when you present yourself as someone doing a research thesis, or mapping industry insights They open the door instantly Once you're inside the conversation Ask questions Shut up And listen Collect pain points, bottlenecks, frustrations, failed attempts, and what they wish existed Talk to 10-20 people in your niche and your offer literally writes itself The questions stay simple: - What’s your biggest bottleneck right now? - What have you tried that didn’t work? - What would the perfect solution look like? - What’s the real cost of not solving this? - If someone solved it for you, what would you pay? People tell you the truth when they think you aren’t selling You get uncensored pain points, real numbers, buying behavior, budgets, timelines And once you have that, your offer is just the summary of everything the market begged for Straight from their mouth into your positioning

Greg Isenberg broke down a 35-step playbook for building AI startups from zero to $1M+/year. 4 businesses, all profitable, no VC money I compressed it into 12 rules that actually matter: 1. ride a trend, don't create one: find a niche where demand already exists but tools are 5 years behind. if people are complaining in reddit threads and facebook groups.. that's your market 2. audience before product: master ONE platform. set notifications for 10 niche leaders, reply with real insight (not "great post!"), gain 5-10 followers daily. this compounds into an unfair advantage when you launch 3. validate with wallets, not surveys: if nobody will pre-pay at 50-70% off for something that doesn't exist yet.. they won't pay full price either. your audience becomes your investors 4. vibe code the MVP: use Cursor/Bolt/V0 to ship v1 in days not months. the goal isn't perfect code, it's proving people will use it. polish comes after revenue 5. keep the team at zero: AI is your co-founder now. Manus for research, ChatGPT for PRDs, Claude Design for design, Cursor for code. most $1M/yr businesses in 2026 run with 1-3 people max 6. automate before you hire: find the 3-step process you do 10x a day that takes 5 minutes each time. automate that first. Lindy, Gumloop, Zapier. work toward 90%+ automation 7. retention before growth: fixing churn is 10x more valuable than doubling acquisition. run retention sprints before growth sprints. most founders do this backwards and wonder why revenue flatlines 8. modular pricing kills one-size-fits-all: free tier for top of funnel, $29 for individuals, $299 for teams, $3K for enterprise. let the product sell itself at every level 9. partner with creators instead of buying ads: offer 1-20% equity or 20-50% rev share to creators with your audience. one partnership can outperform 6 months of paid marketing 10. build free tools for distribution: a public-facing calculator, checker, or generator drives organic traffic AND trains AI search to recommend you. this is the new SEO 11. think portfolio, not single product: once business #1 is profitable, repeat the process. share infrastructure, cross-promote, create a flywheel. Walt Disney didn't build one ride 12. ship something new every 30 days: a culture of shipping beats a culture of planning. new MVP monthly, acquire underperforming products with distribution upside, recruit operators to run them what actually compounds in 2026: - audience before product, not the other way - pre-selling before building - 1-person teams running $1M businesses with AI - retention over acquisition, always - portfolios over single bets - shipping over strategizing the cost of building has never been lower.. billions of people with credit cards are reachable through social media the only bottleneck left is you actually starting full 30-min breakdown from @gregisenberg attached below ↓ study this P.S. left 20 not taken startup ideas below which you can take and start growing

casestudies(.)com/case-studies has 43,468 B2B companies with validated case studies, and 901K+ customer stories across 929 categories. 10 Advanced B2B Outbound Use Cases: Bookmark tf out of this one. ------------------- 1. Competitor Customer Poaching If a vendor has 20-100+ case studies, those case studies reveal the exact customers who already bought something in that category. Use case: Find a category: CRM, AP automation, AI sales assistant, compliance software, etc. -Pull vendors in the category. -Pull their public case study customers. -Build a list of companies already educated on the problem. -Reach out with a sharper alternative or adjacent offer. This is stronger than normal intent data because the company didn’t just browse. They implemented and publicly validated a solution. ------------------- 2. Lookalike Lists From Proven Buyers Every case study is a proof point that a certain type of company buys a certain type of solution. Use case: Take 20 customers from one vendor’s case studies. Enrich industry, headcount, geography, department, tech stack. Build lookalikes. Write copy around the outcome shown in the case studies. Example: If multiple mid-market manufacturers have case studies for ERP modernization, build a campaign targeting similar manufacturers with fragmented ops, legacy systems, or multi-site workflows. ------------------- 3. Category Expansion For Agencies / Consultants The category page is a giant market map. It shows B2B software/service categories: AI, compliance, AP automation, business process automation, CRM, cybersecurity, etc. Use case: -Pick categories where buyers have high LTV and complex buying processes. -Identify vendors with many case studies but weak outbound presence. -Sell demand generation, partner development, paid acquisition, conversion assets, sales process, or case study distribution. ------------------- 4. Case Study Repurposing Offer Vendors with lots of case studies already invested in proof. Most are not fully using it. Outbound target: -B2B software companies -Agencies -consultants -service firms -implementation partners Offer: Turn existing case studies into: -outbound sequences -industry-specific landing pages -LinkedIn ads -sales enablement decks -competitor displacement campaigns -lookalike account lists -“proof-led” nurture sequences Copy example: “{{firstName}} You have 30+ public case studies across {{category_1}} and {{category_2}}. We can turn them into campaigns targeting companies outside your network but look like your best customers. Wrote a few ideas down already, can I send them over?” ------------------- 5. Trigger: Companies Paying To Be Listed The get-listed page says vendors can pay for pricing/visibility options. Companies listed already spend money on customer-proof visibility. Use case: Target vendors with many case studies as proof-mature companies. They likely care about: -demand gen -category authority -buyer trust -pipeline quality -sales enablement Angle: “{{firstName}}, looks like customer proof is already a priority for {{company_name}}. Are the {{number_of_case_studies}} case studies being used to start new conversations, or only for prospects? evaluating you?" ------------------- 6. Buyer Language Extraction Case study titles and summaries give you market language: -“streamlined GDPR compliance” -“simplifies compliance” -“customer case study” -“achieves X outcome” named roles like GDPR Coordinator, Head of Customer Service, HR & Operational Manager Use case: Use the language from case studies to write copy that sounds like the buyer’s category, not generic marketing copy. Prompt: “Extract the recurring business outcomes, job titles, pain points, and implementation language from these 50 case study titles. Turn them into 10 cold email angles.” ------------------- 7. Named Persona Discovery Some case study pages list the customer company and named stakeholder/title. The case studies listing page showed examples like Lawyer and Head of Customer Service, GDPR Coordinator, HR & Operational Manager. Use case: Even if you don’t email the named person, you learn which department owns the problem. For GDPR/compliance: -legal -HR -customer service -compliance -operations For AP automation: -finance -controller -CFO -accounting ops This helps build better Apollo/LinkedIn filters. ------------------- 8. “Proof Gap” Campaign For Vendors Some companies have only a few case studies; others have dozens. That creates two outbound paths. For companies with many case studies: You have proof. Let’s distribute it better. For companies with few case studies: Your competitors are publishing 30-80 customer stories. You have less visible proof in-market. Offer types: -customer story generation -video case study production -case study SEO -proof-led outbound -sales enablement assets -review/reference strategy Videoify, contentify or animate your case-studies is a great angle for content agencies. ------------------- 9. Partner / Implementation Ecosystem Mapping Categories like cloud services, CRM, AI consulting, cybersecurity, and business process automation reveal implementation-heavy markets. Use case: Find vendors with many customer stories, then identify the ecosystem around them: -implementation partners consultants -managed service providers -integration firms -agencies ------------------- 10. Cold Email “Signal” Copy The signal is: public case study = company recently solved or invested in a known business problem. Copy skeleton: “{{firstaName}}, since {{company_name}} was featured in a case study around {{outcome_category}}. Usually when a team solves {{problem_a}}, the next bottleneck is {{problem_b}}. Are you already looking at that, or is it still sitting downstream?” This is better than: “Do you need help with X?” ------------------- Every case study tells you a company had enough pain, budget, and urgency to buy something, implement it, and let the vendor talk about it publicly. That is a far better outbound starting point than generic firmographics. Bookmark, enjoy and execute.

i listened to the people and turned my thoughts on finding side doors in career context into a full essay. read here: open.substack.com/pub/velvetnois…

@chrisgirbu CLIP

I should be selling this for $3000. Instead I'm giving it away for free. It’s the exact process behind 650–800M views/month organic → Client 1 (Fiji Water Owner): 167k to 2.5M followers in 18 months on this system ($1M cash collected in 1 month) → Client 2 (Skull Emoji Trend): 1.5 billion views in 48 hours → Client 3 (Bugatti Crash): $3.6M increase in revenue in 1 month → Total views generated across our roster: 8 billion RT + Like + Comment “CLIP” and i’ll send it (must be following for a DM)