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Agents have rapidly emerged in recent months as one of the most promising modalities for harnessing the power of AI to perform day-to-day tasks. Their growing popularity comes with a nontrivial amount of confusion, though—from what they actually are (the anthropomorphic term itself doesn’t help in that regard) to how and in what contexts they can be used effectively.
This week, we’ve put together a strong lineup of recent articles that will help beginners and experienced practitioners alike to find their bearings around this topic and to make informed decisions about adopting agents in their own workflows. From their core traits to broader questions on reasoning and alignment, these posts cover agents from a technical and practical perspective, while placing them in the context of AI’s growing footprint in our daily lives. Let’s dive in!
- What Makes a True AI Agent? Rethinking the Pursuit of Autonomy
“Even if we could build fully autonomous AI agents, how often would they be the best thing for users?” Julia Winn explores the fundamental traits of agents, adds much-needed nuance to our understanding of what they are—and what they aren’t, and proposes a spectrum of agentic behavior as a framework to assess their suitability for specific tasks. - Exploring the AI Alignment Problem with Gridworlds
Where do agents fit within the ongoing debates surrounding AI safety? What does it take to ensure the outcomes they produce are aligned with their creators’ goals? Tarik Dzekman opens up a thoughtful conversation on a thorny topic: “how hard it is to build a AI agents capable of solving a problem without also encouraging it to make make decisions that we wouldn’t like.”
- AI Agents: The Intersection of Tool Calling and Reasoning in Generative AI
One of the main benefits of AI agents is their ability to bridge the gaps between disparate tools and workflows in a streamlined, automated, and (ideally) predictable way. Tula Masterman’s lucid overview focuses on how reasoning is expressed through tool calling, explores some of the challenges agents face with tool use, and covers common ways to evaluate their tool-calling ability. - The AI Developer’s Dilemma: Proprietary AI vs. Open Source Ecosystem
If you’re in the process of implementing agents (and other AI-powered solutions) in your projects, one of the key questions you’ll have to answer sooner rather than later is whether to rely on proprietary or open-source products to get you there. Gadi Singer shares a detailed breakdown of the advantages and limitations of each approach.