The latest articles on DEV Community by sujith857 (@sujith857). https://dev.to/sujith857 https://media2.dev.to/dynamic/image/width=90,height=90,fit=cover,gravity=auto,format=auto/https:%2F%2Fdev-to-uploads.s3.us-east-2.amazonaws.com%2Fuploads%2Fuser%2Fprofile_image%2F212603%2F6625958b-874c-4ca9-8e6e-8349ea08642c.png https://dev.to/sujith857 en sujith857 Mon, 08 Dec 2025 04:50:00 +0000 https://dev.to/sujith857/just-finished-the-ai-agents-intensive-ai-agents-buildinpublic-techtrends-2p98 https://dev.to/sujith857/just-finished-the-ai-agents-intensive-ai-agents-buildinpublic-techtrends-2p98 <p>Reflecting on the last few weeks, here are my core takeaways from the code trenches:</p> <p>Stochastic vs. Deterministic: Writing code for agents requires a mindset shift. You are essentially managing probabilistic behavior within deterministic control flows. Handling that randomness is an art form.</p> <p>Tool Use: The moment you see an LLM autonomously decide to query a database or run a Python script to answer a question, the paradigm shifts.</p> <p>State Management: Standard chatbots are stateless. Agents require memory—short-term for the current task context, and long-term for personalization.</p> <p>The shift from standard LLMs to Agentic Workflows is massive. We are no longer just "talking" to AI; we are designing systems where AI can plan, execute, and use tools to solve complex problems autonomously.</p> <p>The biggest unlock? Realizing that an Agent is just an LLM with a loop, a memory, and a toolkit.</p> <p>Can't wait to ship what I’ve been building. 🤖✨</p>