AI Agents: machine that builds the machine

Build the machine that builds the machine | LinkedIn
Paul Dix
Cofounder and CTO at InfluxDB, series editor on Addison Wesley's "Data & Analytics

Building the machine that builds the machine with Paul Dix, Co-founder & CTO at InfluxDB (Changelog Interviews #676)

Paul Dix joins us to discuss the InfluxDB co-founder’s journey adapting to an agentic world. Paul sent his AI coding agents on various real-world side quests and shares all his findings: what’s going to prod, what’s not, and why he’s (at least for a bit) back to coding by hand.
Update: He’s back to letting the AIs write code, but with a lot more oversight. For now

Paul Dix on X: "2026: The Great Engineering Divergence" / X

Message from InfluxDB

AI tool: SmolAgents by Hugging Face

 Understanding AI Agents and Agentic AI: Concepts, Tools, and Implementation with SmolAgents @CodeMag

Today, there are numerous frameworks available for building AI agents, each offering its own philosophy and strengths. Popular options include SmolAgents by Hugging Face, LangChain, LangGraph (both by LangChain, Inc.), and Microsoft’s AutoGen. Although all of them support agent development, they differ in complexity, flexibility, and intended use cases.
In this article... focus on building agents using SmolAgents, a lightweight and developer-friendly Python framework.

huggingface/smolagents: 🤗 smolagents: a barebones library for agents that think in code. @GitHub