Ruslan Galba

Gamified funnel for Halloween 🎃 RYZE is launching a bunch of AI-made games as full funnels for Halloween. - shop.ryzesuperfoods.com/brid… And low key this is EXACTLY where you should land your warm traffic. - Email subscribers - Retargeting These people already know the product. They just need a fun reason to come back and a better deal. This is where DTC is heading imo. At some point you just gotta get more creative. What would I do? Push these HARD through email not Ads Tbh this could become one of your best performing campaigns lmaoo Because you’re not only doing hard work with emails. You’re improving what happens AFTER the click. Better destination = more revenue. Steal it for your brand.

Grok @Bot can now call someone or a business for you, make a request on your behalf, take notes on the response and send you a note summarizing the conversation!

There is literally so much to learn about marketing from sluts on the internet A top 0.1% OnlyFans girl making $300,000 a month gives away 95% of her photos for free to 100,000 broke horny guys... just so the algorithm pushes her onto the screen of 15 lonely millionaires She knows the broke guys pay her in reach & the 15 whales pay her $20,000 each in private DMs Meanwhile look at how normal businesses try to sell stuff online: They hide everything behind a paywall or a "book a call" link, make dry content aimed only at rich CEOs, get 200 views, and wonder why they're making $0... You cannot reach rich buyers on the internet without using the general public as your free megaphone!!! Why? Because algorithms don't know who has $50,000 sitting in their bank account They only know what makes human beings stop scrolling, argue in the comments & hit save When you look behind the curtain of a $300k/mo OF page, it's the cleanest 4-step marketing funnel on earth (and it works even better when you apply it to a normal business): Step 1: Bait the masses for free reach You open your content with a broad, controversial human truth that gets 100,000 everyday people fighting in the replies. You don't make a dime from those 100,000 people... their only job is forcing the algorithm to shove your name onto the phone of the 150 quiet millionaires lurking in that crowd Step 2: Put the "Whale Filter" in the second half Halfway through, you switch from the broad story into a breakdown so specific that broke tourists scroll past it... while the guy with real $$$ goes "wait, this mf actually knows what he's doing" & clicks your profile Step 3: Make the front door free Amateur OF girls put a $25 paywall on their bio & starve. Smart ones make entry free just to get the guy off the public feed and into a private room. In normal marketing, you do the exact same thing with a free 5-minute written VSL, webinar, or diagnostic tool that pulls the serious buyers off the feed Step 4: Separate the tourists from the whales in 3 DMs A trained chatter asks 2 casual questions in the DMs to spot the 1% with real budget, then moves only those whales onto a custom call where they close at 10x the price This is the exact same shit we do on X for high-ticket businesses... we use this whale funnel to get our clients $0.25 webinar opt-ins, $5 to $50 booked calls & a 60% close rate Feel free to check out yegor. com if you have a $5k+ offer & want us to build and run the whole machine for you

This is the most serious 48 hours in cybersecurity history. "Black October" they're calling it It seems every *hour* there's a new incident, that in a typical year, would be one of the biggest incidents of the *entire year* SUMMARY OF THE LAST 48 HOURS: YEAR-LEVEL INCIDENTS (In a typical year, these would be among the biggest incidents of the year): 1. PHP2Shell: a hole in the software behind ~70% of websites. Governments took sites offline. 2. eMudhra: the master keys that prove websites are real were cracked. One was the number 4. 3. California: data on every public school student since 2023 stolen, including disability status 4. Railway: hackers stole customers' secret keys from a hosting platform used by millions of developers 5. Zeabur: 321,810 accounts breached. The company is shutting down. 6. LiteLLM: an AI tool downloaded 3.4 million times a day was poisoned with a password stealer 7. GitLab: a 10-out-of-10 severity hole in every version since 2014 8. Cairn: criminals used an AI hacking tool to break into 100+ companies 9. Ahold Delhaize: hackers knocked the owner of Food Lion and Stop & Shop offline 10. Onamae: malware planted on up to 26,739 customer servers in Japan MONTH-LEVEL INCIDENTS (In a typical month, these would be among the biggest incidents): 11. Signal: a bug could leave your mic and camera on after you hang up 12. NGINX: 3 critical holes in software running ~1/3 of websites 13. HTTP/3: a single connection can crash 7 of the 10 web server types tested 14. Plex: hackers breaking into home media servers 15. SafePay ransomware: FBI warns it has hit 600+ critical infrastructure organizations 16. Palo Alto: ransomware gangs breaking in through company firewalls 17. Bullhorn: platform used by 10,000+ companies knocked offline 18. Medi-Cal: 970,000 patients' data stolen 19. WordPress: hackers stole a plugin maker's keys and used them to plant backdoors on websites 20. AOMEI: backup software's update server handed out a backdoor 21. Meta Muse: Meta's AI agent exposed users' personal and business secrets 22. Tor: 333 relays hijacked to steal logins 23. TiDB Cloud: database company's cloud breached Also serious: 24. State Bank of India: India's biggest bank confirms a data breach 25. OVHcloud: hackers slipped a password stealer into a cloud company's official tool 26. Siemens: a software hole being used to spread malware 27. North Korea: state hackers launch a new attack campaign on South Korea

🌶️ Some kind of magic happens when you have these guys on the call @d_grimripper @iamgalba @KrsteKovaceski @andreilunev

I spent 48 hours in SF hanging out with billionaires, data labs and AI founders and execs running $1B to $100B companies. My observations: 1. Sooo MANY stories of data brokers making like $2M a WEEK selling company data to labs. I can't tell if it's the beginning or a bubble, and I kept wondering which niches are left. Digging into it actively. 2. At dinner, someone asked the table, "If a new model drops next month, does your company get better or worse?" HALF the table went quiet! I think that's the best question to ask about any AI startup right now. 3. The bar people talk about now is hitting $1B in revenue in 12 months (I guess that's the new unicorn?). What I didn't hear much about is retention. AI revenue can come in fast and leave fast, and I think we're going to see a lot of stories of AI companies with huge revenue and terrible retention. 4. It's pretty clear we're living through the reinvention of the computer. The model is the CPU, the harness is the operating system, and skills and plugins are the apps. Thinking about it that way makes it easier to see where the whitespace is. 5. We're maybe 12 months from an agent that can watch you work for a week and then do your job without any instructions. The screen recording plus agent memory plus local model combination makes this possible right now. 6. Agent harnesses feel like the new GPT wrappers, in a good way, especially vertical ones. The best teams I talked to treat the model as swappable. One founder walked me through routing different models to different jobs: one for taste and visuals, a cheaper one for the everyday stuff, another for text. They use prompts they can move across models over fine-tuning, and A/B test the output on what users actually do with it: do they edit it, export it, share it? A vertical harness is basically four things: the connectors for that industry's data, evals written by people who know the work, rules for what the agent can and can't touch, and a clean screen for a human to review. The model is maybe 20% of it. 7. There's a lot of reverse engineering going on/cloning going on more than I've ever seen. People are decompiling software and rebuilding it with agents, and someone showed a suite of like 10 apps that are worth $5B+ each all that he cloned open source. Me and everyone are still thinking through what it means when software gets this easy to copy. 8. My guess is the value moves to data. If the software can be rebuilt quickly, what's worth paying for in a legacy SaaS company is the years of customer data and workflows inside it. Some SaaS companies are secretly data companies. Gets me thinking about how do you truly value data for this saas companies? Like if we were buying these dying saas companies at 2x ARR before (as example), maybe there is a better metric. Idk, just thinking out loud here. 9. It feels like a good chunk of legacy software won't make it to the agentic era, especially anything built around people clicking through a lot of screens. 10. Every company I talked to wants to pipe its internal data into one place and expose it to agents through MCP. Then they look at the data and realize it's a mess: five versions of the same customer, old Slack channels, PDFs nobody can search. Cleaning that up feels like a big consulting opportunity! 11. A lot of founders are building the basic building blocks for agents: APIs, data layers and tools. Some of the companies I saw barely have a UI because the main user is an agent. I really believe the startups that build primitives to this agentic era will do extremely well. Building blocks is the best way to think about it. 12. Labs can get plenty of training data, but it's harder to get real examples of agents failing inside companies. Whoever has those logs has something valuable. 13. Someone running a big consumer company told me the next fight is over memory. The model that remembers the most about you wins, and the smartest model matters less than people think. 14. Physical AI came up a lot. Astra I think was the first model that got people into AI can actually do CAD, and I think a lot of people are thinking what does vibe manufacturing really look like. The line I keep thinking about came from a robotics founder: the hardest problems in AI are deployment problems now, not research problems. Their robots work on their own, call a human when they get stuck, and every one of those calls becomes training data. 15. Cybersecurity companies are having a moment and are actually cool companies to build now, especially the ones that clean up after a breach. Every agent with access to your systems is a new door into your company, and a lot of those doors were left open. 16. Some startups are worth more dead than alive now. A shutdown company with 5 years of Slack, email and code can get paid for licensing all of it. I wouldn't be surprised if founders start factoring that into when they shut down. 17. People are starting to talk about monetizing the agent web. It feels really early, but when the most popular user of the internet is an agent, what startups should you be building? 18. I think agent insurance is coming. Once an agent makes an expensive mistake, insurers will want audits before they cover anyone. 19. Several people said the hire they want most is someone with taste who can write evals. The models are getting good at generating ideas, so the hard part is judging which ones are good. 20. New trend I observed: startup raises VC, uses venture dollars to become a creator, startup fails, founder falls back on being a full-time creator and incubates other products bootstrapped. 21. Getting SIGNIFICANT distribution is HARD right now. Founders are sponsoring buses, buying billboards like crazy and throwing parties with famous DJs to get noticed. Kinda feels dotcom era in that sense. Attention is what's scarce! The growth guy going viral sharing his UGC strategy from Wispr Flow is a good example. It's the sauce everyone wants, and I truly believe there are probably only 50 people on the planet who know how to scale these types of businesses efficiently in this era. Always good to get that dose of SF. I felt sooo lucky to have such an incredible trip during such an incredible time in building businesses. Surreal in so many ways. Happy to be home and locked in. Until next time!