𝗘𝘅𝗲𝗰𝘂𝘁𝗶𝘃𝗲 𝘁𝗼 𝗔𝗜 𝗗𝗲𝘃
I spent six months trying to build AI agents using my executive experience.
I learned that 40% of my old skills did not work in this new field. As a Deputy CEO, I knew strategy and team management. I did not know how to build multi-agent systems.
Some skills still helped me. I used project management to lead my agent development. I prioritized tasks and managed resources. I optimized my agents on Oracle Cloud. This reduced my costs by 25% through autoscaling and free tier usage.
Technical work was hard. I struggled to integrate Groq and Claude into my systems. One Oracle Cloud error took three weeks to fix. I had to learn how to debug code and read documentation to solve problems.
My non-traditional path is now a strength. I do not have a standard AI education. This forces me to think differently. I built a system to route Telegram and WhatsApp messages through AI agents using machine learning.
Real-world constraints are the biggest hurdle. I must optimize agents to run on small resources. I use model pruning and knowledge distillation to save memory. I also manage data privacy and security rules.
I made one mistake. I tried to hide my lack of technical knowledge. I should have asked for help sooner. If I start again, I will build a network of mentors and ask questions immediately.
How did you switch from a non-technical role to a technical one?
What technical problems did you face when building AI?
How do you handle resource limits when deploying systems?
What advice do you have for people changing careers?
Source: https://dev.to/elenarevicheva/executive-to-ai-dev-4ole
Optional learning community: https://t.me/GyaanSetuAi