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12 contributions to AI Automation Society
n8n Automation Expert | AI Agent Developer
I'm an n8n Automation Expert with experience building AI-powered workflows and business automations. I can help with: - n8n workflow development - AI agent automation (OpenAI, Claude, etc.) - API integrations - CRM and lead generation automation - Webhooks and custom API connections - Email and WhatsApp automation - Database integrations (Supabase, Airtable, PostgreSQL) - Workflow optimization and troubleshooting I'm currently looking for freelance or full-time opportunities. If you're looking for someone to automate your business processes or build custom AI agents with n8n, I'd be happy to help.
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Why Are So Many People Learning AI But Still Not Making Money?
Most people are learning AI. Very few are making money with it. The difference isn't the tools they're using. The difference is that one group is learning, while the other group is taking action, solving problems, and putting their skills in front of people. You don't need another course. You need a way to turn your skills into income. What's the biggest thing stopping you from making money with your AI skills right now? Drop your answer below. 👇
1 like • Jun 8
Strong point—and it comes down to execution vs learning. Most people get stuck in “tool mode” instead of “problem-solving mode.” They learn prompts and tools, but don’t package those skills into a service, product, or clear offer people actually pay for. The real shift is moving from “I’m learning AI” to “I’m using AI to solve a specific business problem for someone.”
Over-engineering your automations is just as bad as not building them
The most reliable workflows I have built are also the simplest ones. One trigger, clean data transformation, one output. No branching logic that requires three LLM calls to resolve something a basic conditional would handle in milliseconds. The temptation when you get comfortable with agents is to add complexity because you can. Parallel execution, dynamic routing, multi-model chains. Sometimes that is the right call. Most of the time it is overhead that makes the system harder to debug and slower to run. Before adding an AI layer, ask whether a deterministic function solves the problem. If it does, use that. Reserve the agent layer for tasks that actually require reasoning and context, not ones that just need a formatted output.
Over-engineering your automations is just as bad as not building them
1 like • Jun 8
Totally agree—most automation breaks not from lack of AI, but from unnecessary complexity. The best systems are usually simple pipelines: clear input → deterministic processing → single output. AI should only handle what actually needs reasoning, not replace logic that code can do faster and more reliably.
Claude automation for beginners
Been experimenting with Claude for automation lately — wanted to share what actually works for beginners. Most people overcomplicate this. Here's what I've learned: The only stack you need to start: → Claude = the brain (tells you what to do with the data) → claude code = the hands (actually does the action) First automation worth building: New form submission → Claude writes a personalised response using their answers → Auto-sent as email Takes 30 minutes to set up. Saves hours every week. What actually makes you better at this: → Give Claude more context, not less — it performs like the quality of your brief → Build one working thing before starting the next → The mistake everyone makes: automating something they don't fully understand manually first To go from beginner to expert: → Month 1: Prompting deeply + one simple workflow → Month 2–3: Chaining prompts, connecting APIs → Month 4+: Full agents, multi-step logic, real client work Took me a while to figure out the right order. Sharing so someone here skips the confusion. 📢Here's 1 to 2 points which even begginers should notice and do not do blindly?? Let's see if you can catch which points they're?? Happy to answer questions if anyone's building something specific ??
1 like • Jun 8
Two big beginner mistakes to avoid here: Don’t automate what you don’t understand manually first — if you can’t do the process yourself step-by-step, you’ll build broken or low-quality automations.• Don’t start with complex multi-step systems or agents too early — beginners should avoid chaining APIs or workflows before mastering one simple, working automation end-to-end.
Most people still think AI is about getting better answers.
I think they're looking at the wrong trend. The next major shift isn't smarter chatbots. It's AI that improves its own workflows. Right now, AI helps humans work faster. But we're entering a phase where AI systems can: • Analyze their own performance • Identify inefficiencies • Refine processes • Generate better solutions over time • Assist in building and improving other AI systems That changes the game. For the last 20 years, the biggest advantage was having access to information. Today, information is everywhere. The new advantage is leverage. A single person with the right AI systems can operate with the output of an entire team. The question isn't: "Will AI replace people?" A more important question is: "How much more effective will AI-augmented people become compared to everyone else?" I believe the gap between those who learn to collaborate with AI and those who don't will become one of the biggest competitive advantages of this decade. We're still very early. Most people are experimenting with prompts. Very few are building systems. And that's where the real opportunity is. What's one AI trend you think most people are underestimating right now . #The Time Lens for Businesses (Productivity Lesson) #AI Email Agent (9/20/24) #AI Email Agent (9/20/24) #RAG Chatbot AI Agent (9/22/24)
1 like • Jun 8
Strong take—and directionally it’s right: the shift is from “using AI” to building AI-driven systems that improve themselves over time, especially around workflows, evaluation loops, and automation of decision support. The real differentiator won’t be access to AI anymore, but who can design feedback loops, measure output quality, and continuously refine systems instead of one-off prompts.
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@abderrahman-bounagui-6460
I'm abderrahman CEO and Co-fonder on linkartificial

Active 3h ago
Joined Jul 6, 2025
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