From Data Scientist to AI Agents - the roadmap 😃 Many Data Scientists are yet reaching out for the same! (After working on production-level AI Agents) Investing in these areas will help you in the long run. If I have missed something please add in the comments so its helpful for other people 🙂 Investing in the below areas will help you in the long run: ↳ Extend your 𝗣𝘆𝘁𝗵𝗼𝗻 𝗰𝗮𝗽𝗮𝗯𝗶𝗹𝗶𝘁𝗶𝗲𝘀 - go beyond traditional scripting. ↳ Understand 𝗥𝗔𝗚 (𝗥𝗲𝘁𝗿𝗶𝗲𝘃𝗮𝗹-𝗔𝘂𝗴𝗺𝗲𝗻𝘁𝗲𝗱 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝗼𝗻) and its key components. ↳ Work hands-on with 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁 𝗳𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸𝘀 and tools to get practical experience. (LangGraph is preferred - my opinion) ↳ Learn how 𝗺𝗼𝗻𝗶𝘁𝗼𝗿𝗶𝗻𝗴 works to ensure reliable performance. ↳ Don’t miss out on 𝗣𝗿𝗼𝗺𝗽𝘁 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 – it’s extremely important right now. ↳ Know how to 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁 𝘁𝗵𝗲 𝘀𝘆𝘀𝘁𝗲𝗺𝘀 and 𝗱𝗲𝗽𝗹𝗼𝘆 the entire workflow on the Cloud, ensuring scalability and reliability. ↳ Also understand which LLM to choose - cost vs performance is an important factor. If you’re serious about getting into AI Agents, this roadmap will help you focus on what truly matters. What do you think? Can you relate to this? -- ♻️ Repost if you found it helpful 🤗 ➕ Follow me - Shantanu for Production AI - ML - MLOps content and Career tips! | 50 comments on LinkedIn