Everyone talks about "LinkedIn automation" like it's one thing — but the difference between getting banned in 2 weeks and running safely for months is HOW you automate. I spent the last year building a system that doesn't trigger LinkedIn's risk detection. Here's what I learned: ✅ Browser identity matters more than proxy rotation LinkedIn doesn't just check your IP — it fingerprints your entire browser. Same device, same timezone, same language every session. A random headless Chrome in a datacenter screams "bot." ✅ Speed is the #1 red flag Humans don't type at 1000 characters per second. They don't send 50 connection requests back to back. Delays between actions (1-3 seconds) and typing with human-like pacing make the difference. ✅ Spread actions across multiple time windows Sending everything at 9 AM = pattern. Sending in 6+ small batches throughout the day = human. LinkedIn's algorithms notice the shape of your activity, not just the volume. ✅ Conservative limits protect your account Just because LinkedIn ALLOWS 100+ connections/day doesn't mean your account should do it. Staying well under the hard limits keeps your account off their radar. The tools that ignore these things are the reason people think "LinkedIn automation = banned." It doesn't have to be that way. I ended up baking all these principles into inboundy.app — not pitching, just sharing what 12 months of trial and error taught me.

Most LinkedIn content problems aren’t writing problems — they’re systems problems. The bottleneck lives in the loop between research, writing, and publishing. Fix the loop and the writing gets easier on its own. Worked with a health & wellness company recently. Their team was spending a full day every week on LinkedIn — research, drafting, scheduling, the whole thing. They were good at it. They just had no time. So we stopped treating content as a creative task and started treating it like a system you could improve. Here’s what I learned: ✅ Research is its own phase, not a pre-task. Most teams skip it or rush through it. Treating research as a separate step changed everything downstream. ✅ Match the model to the task. Don’t burn an expensive call on summarizing an article. Cheaper models handle research just fine — the cost difference adds up fast. ✅ Decouple writing from publishing. Most teams rewrite because they have to schedule. Separate draft from schedule from publish, and you can review, batch, and adapt without throwing work away. ✅ Close the loop. The system should learn what topics get replies, not just what gets posted. That signal feeds the next research cycle, and the content gets sharper on its own. The CEO put it like this: “We save 8 hours per week on content creation alone. It’s like having a marketing assistant that never sleeps.” The part that surprised me wasn’t the time savings — it was the consistency. The posts just kept showing up, on brand, every week. If you’re doing this manually right now, the fix probably isn’t “hire another writer.” It’s build a loop. What part of your content workflow is the worst right now — research, writing, or distribution?

First post! How do you guys manage linking files/folders together so that the AI agent isnt reading stuff that isn't relevant to the prompt/project at hand? I'm wasting too many tokens and getting weird output. Is there a methodology yall follow? Happy Wednesday!

Let’s be honest: most of us here want to spend our time building core systems, tweaking workflows, and handling clients—not staring at a blank screen trying to figure out what to post on LinkedIn. But organic visibility brings in clients. To solve my own frustration, I built a tool that takes over the heavy lifting. Instead of just spinning out generic, robotic templates, the AI behind it actually maps out context to craft human-sounding posts and coordinates everything in the background. In this quick 58-second video, I walk you through exactly how it handles the generation and how easily you can iterate on both the copy and the image prompts until it fits your exact branding. If you want to play around with it and save yourself some time, you can try it out for free here: https://inboundy.app/?utm_source=skool Let me know what you think of the generation quality or if you have any feature requests!

I see things are upgrading day by day. Although I'm learning, getting distracted some how by knowing that the technology is upgrading giving me a confusion of whether am I on the right path or need to make some changes Can anyone suggest me wheather to continue in learning n8n gives me better future opportunities or shall I switch my learning journey into something else???