I’m Tanja. I lead design at Flero.ai, a workflow automation tool. I’m looking for AI automation builders to test our tool. On a 20-minute video call, I will give you access to the tool, ask you a few questions, and you will build a workflow that you choose, and tell me what was unclear and what we can do better. Nothing to prepare. You will get 3 months free access to Flero, and I’ll send a £20 Amazon voucher after the call. Please book a call here: https://aice.flero.ai/forms/public/86325e009d2405348491161ab4518390

Just a bit of info for those looking to infiltrate the mining sector.

Implementing AI into industrial automation shifts factories from rigid, rule-based tasks to adaptive, predictive operations. Here is the quick breakdown of the Do’s and Don’ts for a successful rollout: 🛠️ THE DO'S: - Fix your data first: Clean, standardized sensor data is the bedrock of any working AI model [amd]. - Keep steps atomic: Don't automate a whole line at once; start with tight, specific tasks like visual quality checks [dac]. - Keep humans in the loop: Use AI to predict failures and surface recommendations, but leave final control to operators. - Deploy at the Edge: Run real-time models locally for low latency; use the cloud just for heavy training. ❌ THE DON'TS: - Don't touch core logic: Never replace deterministic safety interlocks or basic machine control loops with AI. - Don't share proprietary data: Ensure vendors process manufacturing data transiently so your IP stays secure. - Don't ignore the workforce: Frame AI as a tool that reduces tedious monitoring, not a threat to technicians. - Don't accept "black boxes": Maintain explicit, timestamped audit trails for every AI-driven process adjustment.

I’ve been thinking about how to build more complete systems beyond individual AI workflows, especially in areas like: - 📱 Social media management and content workflows - ⚙️ Business process automation - 🎯 Outreach and lead generation - ✍️ Personalized communication at scale I’m curious how other builders approach these projects from the beginning. Do you start by mapping the business process, choosing the tools, or designing the system architecture first? And how do you connect everything together while keeping the system reliable, personalized, and easy to maintain as it grows? I’d love to hear how you approach these systems and any lessons you’ve learned along the way. 👇

Completed My Portfolio — Now How Do I Land My First Paying Client? Hey everyone! 👋 I've finally completed my portfolio, showcasing my work in AI automation and business solutions. Now I'm moving on to the next challenge: landing my first paying client. I'm looking for practical advice from people who have already gone through this stage. A few things I'd love your input on: - Where did you find your first paying client? - Is cold email, LinkedIn outreach, Instagram, or direct messaging business owners the best place to start? - How do you approach potential clients without sounding too salesy? - Should I offer a free demo, a small paid project, or a discounted first project to build trust? - How many people should I reach out to daily to get my first result? My goal is to stop overthinking, take consistent action, and land my first client. If you've been in this position before, I'd really appreciate your advice, lessons learned, or mistakes I should avoid. Thanks in advance! 🚀