Building Reliable AI Agents for Network Engineering Automation
Hi, Lindy team — I really appreciate the work you’re doing. I see Lindy as a platform that can truly scale into reliable and proactive AI Agents, which is exactly what I want to focus on in the next 6 months. My goal is to build AI Agents and workflows that automate daily tasks in Network Engineering so I can show my boss real solutions that make our team more proactive instead of reactive. For example, I’m working on automating:
Extracting upgrade and change data from Outlook emails and updating our SharePoint spreadsheets automatically.
Building agents to troubleshoot and document Cisco switch issues (like port errors or stack failures) in real-time.
Creating workflows to map switch configurations and update cutsheets without manual intervention.
At the same time, I’m aiming to build a Network Engineer AI Agent — one that deeply understands everything our team does, can propose viable solutions, help us troubleshoot issues faster, provide insights into what areas need improvement, and guide us without cutting corners. That’s why stability is so important for me. Right now, a few issues keep slowing me down:
Flows sometimes overwrite parent versions or skip steps when copied.
Triggers (Google Sheets, Gmail) don’t always fire reliably.
Some agents loop endlessly and burn through credits.
Sharing/exporting agents is inconsistent, making collaboration harder.
I completely understand this is still early-stage, and I say this not as criticism but as encouragement. I want to learn and grow with Lindy as my platform of choice — but I also need enough reliability to make it viable for my career path. Thanks for all the work you’re doing. I’d love to keep building my future here.
