For the past couple of years, like many other software developers, I have fully integrated generative AI into my development toolkit. I want to share my journey and my experience with the different tools that have shaped my workflow.
Early Days: ChatGPT and the Beginning of a New Age 🔗When ChatGPT launched in late 2022, the reaction was immediate. We tried it, we were horrified it would take our jobs, and I decided I didn’t want that anxiety.
Over the past few months, I’ve been learning and building AI Agents / LLM-driven automation workflows.
I learned a lot - some exciting, some challenging and I decided to document my learnings in this blog.
LLM Workflows and Agentic Automation is Backend Engineering with Extra Steps 🔗Yep! Maybe I’ll ruffle some feathers, but building AI agents is very much a backend / automation pipeline-driven process. The same basic principles apply — and that’s actually a good thing.
One of my first jobs as a college graduate was writing Robotic Process Automation (RPA) workflows using Leapwork. I was able to automate several repetitive, time-consuming tasks, which gave me a deep appreciation for the power of engineering.
RPA involves using software “bots” to mimic human interactions with digital systems. These aren’t physical robots, but rather modular software programs designed to perform tasks like data entry or web scraping.