Are the complex automation flows promoted by creators practical and maintainable, or are they just for views?
The vast majority of those elaborate AI‑agent flows you see online are just for views—they don’t actually make money because the agents aren’t reliable enough to do real work. Businesses don’t want a model that can answer in a million different ways; they want a highly constrained output—maybe just five or six possible answers—so they can control most of the content. What they really want is for you to scrape a resource, run it through an LLM API to get a few rephrased versions (like icebreakers or paraphrased job titles), and then slot those into a templated email or document. The LLM fills in only the small, variable pieces while the rest stays fixed, giving them control and reducing unpredictability. In short, treat LLMs as APIs rather than autonomous agents; that’s where the money is right now.
The biggest pain point is content ideas. AI can help by researching what others are doing, finding unique angles, and creating a summary bot that compiles summaries into a Google Sheet, saving you daily research. It can also generate titles based on high‑performing templates, though you should still add your own human touch because titles and thumbnails are the highest‑leverage elements for virality. Another major pain point is repurposing. Repurposing long‑form content into short‑form, text, and distributing across platforms is valuable, especially when you take content from creators in adjacent niches — like video editors or personal trainers — who use AI terms. By scraping their reels, you get domain‑specific experts recommending AI tools, letting you create content that funnels their audience into your automation niche. Finally, AI can help generate outlines for content using deep research, allowing you to produce large amounts of content quickly.
I think marketing agencies are great; I niche down with them and make more money than most with an equivalent service. Whether you need to differentiate depends on your goals—if you aim to be the Uber of automation agencies selling to marketing agencies at $100M/year, you'll need more differentiation than just 'marketing agency'; if you want a tiny niche, you can target whatever you want, especially if you have experience to stand out. As for assets to send to marketing or creative agencies that aren't just AI‑generated: you can build them whole HTML websites (customized with context) and host them; generate newsletters from templates; create PPC ad creatives based on trending ad‑library content; produce high‑quality proposal templates; make slide decks; essentially any day‑to‑day marketing agency deliverable can be generated with AI, but the biggest impact is the customized HTML template because clients are impressed by receiving a full website.
Yeah, it's probably your ability to verbalize that—your skill at explaining AI's value is what's lacking. These systems save time and money, but you can't just tell that to somebody; you need to first understand their specific problem, paraphrase it in your own words to show you get it, then expand on how that problem costs them time and money. After that, you present your system as a solution, estimating ROI based on past clients, maybe mentioning a big‑name client you built it for, and ask if it matches what they were looking for. Then you give a brief demo, showing what you can tweak. In doing so, you show how AI saves them time or money, rather than just stating it. Everybody knows AI helps, but you demonstrate it for their specific case. Automation means reducing labor cost; you show how to achieve that for their problem. You also mentioned your most profitable system is your cold outreach system. To break it down: there's a manual way and an automatic way. Manual: go to Apollo.com, create a search URL (e.g., for creative agencies), copy it, go to appi.com, type Apollo, pick the popular scraper ($120 per thousand leads), paste the URL, pay per thousand leads—you get output with names, emails, etc., export as CSV, feed into AI (using Make.com or Nad), generate personalized icebreakers via a message model, format as JSON, then upload to Instantly.ai or Smartlead. You handle copywriting yourself. The automatic way: set up a Google Drive watch folder with webhooks; when a lead sheet is uploaded, it triggers the same process automatically—scraping leads via Appify, adding them to Instantly in an automatic campaign, managing everything behind the scenes. This lets you incorporate multiple lead sources (conferences, Apollo, Zoom Info, LinkedIn, VA‑assembled leads). You also added lead nurturing: an autoresponder that replies instantly to instant‑email responses (e.g., between 6 pm and 7 am), giving the perception of attentiveness and buying time, which boosts response rates.
value communicationsales processcold outreachlead nurturing
The laws governing automation in the EU are essentially the same as those in Canada, the US, Australia and other British Commonwealth nations; there’s no major fundamental difference. The issue is that the laws are written vaguely, and people tend to apply that vagueness to themselves. When you automate systems you inevitably connect APIs, scrape web pages, and do other things that violate the terms of service of the websites and businesses you work with—scrapers are generally disliked, and while agents are changing things a bit, the basic reality remains. It’s similar to jaywalking: if you examined every law in your jurisdiction you’d likely find you’re breaking some rule somewhere. I’m not telling anyone to break the law, and I’m not a lawyer, so I can’t give legal advice. All I can share is my own experience, which has always been a risk‑to‑reward calculation.