Why 2026 Belongs to Agentic AI (And How to Build Your First Local Agent)
The article discusses the shift from traditional chatbots to agentic AI, emphasizing the advantages of active collaboration over passive interaction. It outlines the architecture of a stateful local agent and its components, including memory and planning capabilities. The author provides a tutorial for developers to build their own local agent using Python.
- ▪The developer community is moving towards agentic AI as the novelty of traditional chatbots fades.
- ▪Agentic AI acts as an active collaborator, executing multi-step plans autonomously rather than just responding to prompts.
- ▪The article includes a tutorial on building a stateful local agent in Python, highlighting its core components.
Opening excerpt (first ~120 words) tap to expand
try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3947269) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Aditya Dwi Nugroho Posted on May 25 Why 2026 Belongs to Agentic AI (And How to Build Your First Local Agent) #python #programming #ai #opensource Beyond the Chatbox: Why 2026 Belongs to Agentic AI (And How to Build Your First Local Agent) For the past few years, the developer community has been flooded with conversational AI. We built chatbots, integrated LLM APIs into our side projects, and got used to typing prompt after prompt to copy-paste snippets of code.
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