Agents are the hottest thing in tech right now. Top firms from Google DeepMind to OpenAI to Anthropic are racing to augment large language models with the ability to carry out tasks by themselves. Known as agentic AI in industry jargon, such systems have fast become the new target of Silicon Valley buzz. Everyone from Nvidia to Salesforce is talking about how they are going to upend the industry. We believe that, in 2025, we may see the first AI agents join the workforce and materially change the output of companies, Sam Altman claimed in a blog post last week. In the broadest sense, an agent is a software system that goes off and does something, often with minimal to zero supervision. The more complex that thing is, the smarter the agent needs to be. For many, large language models are now smart enough to power agents that can do a whole range of useful tasks for us, such as filling out forms, looking up a recipe and adding the ingredients to an online grocery basket, or using a search engine to do last-minute research before a meeting and producing a quick bullet-point summary. In October, Anthropic showed off one of the most advanced agents yet: an extension of its Claude large language model called computer use. As the name suggests, it lets you direct Claude to use a computer much as a person would, by moving a cursor, clicking buttons, and typing text. Instead of simply having a conversation with Claude, you can now ask it to carry out on-screen tasks for you. Anthropic notes that the feature is still cumbersome and error-prone. But it is alreadyavailable to a handful of testers, including third-party developers at companies such as DoorDash, Canva, and Asana. Computer use is a glimpse of whats to come for agents. To learn whats coming next, MIT Technology Review talked to Anthropics cofounder and chief scientist Jared Kaplan. Here are five ways that agents are going to get even better in 2025. (Kaplans answers have been lightly edited for length and clarity.) 1/ Agents will get better at using tools I think there are two axes for thinking about what AI is capable of. One is a question of how complex the task is that a system can do. And as AI systems get smarter, theyre getting better in that direction. But another direction thats very relevant is what kinds of environments or tools the AI can use. So, like, if you go back almost 10 years now to [DeepMinds Go-playing model] AlphaGo, we had AI systems that were superhuman in terms of how well they could play board games. But if all you can work with is a board game, then thats a very restrictive environment. Its not actually useful, even if its very smart. With text models, and then multimodal models, and now computer useand perhaps in the future with roboticsyoure moving toward bringing AI into different situations and tasks, and making it useful. We were excited about computer use basically for that reason. Until recently, with large language models, its been necessary to give them a very specific prompt, give them very specific tools, and then theyre restricted to a specific kind of environment. What I see is that computer use will probably improve quickly in terms of how well models can do different tasks and more complex tasks. And also to realize when theyve made mistakes, or realize when theres a high-stakes question and it needs to ask the user for feedback. 2/ Agents will understand context Claude needs to learn enough about your particular situation and the constraints that you operate under to be useful. Things like what particular role youre in, what styles of writing or what needs you and your organization have. ANTHROPIC I think that well see improvements there where Claude will be able to search through things like your documents, your Slack, etc., and really learn whats useful for you. Thats underemphasized a bit with agents. Its necessary for systems to be not only useful but also safe, doing what you expected. Another thing is that a lot of tasks wont require Claude to do much reasoning. You dont need to sit and think for hours before opening Google Docs or something. And so I think that a lot of what well see is not just more reasoning but the application of reasoning when its really useful and important, but also not wasting time when its not necessary. 3/ Agents will make coding assistants better We wanted to get a very initial beta of computer use out to developers to get feedback while the system was relatively primitive. But as these systems get better, they might be more widely used and really collaborate with you on different activities. I think DoorDash, the Browser Company, and Canva are all experimenting with, like, different kinds of browser interactions and designing them with the help of AI. My expectation is that well also see further improvements to coding assistants. Thats something thats been very exciting for developers. Theres just a ton of interest in using Claude 3.5 for coding, where its not just autocomplete like it was a couple of years ago. Its really understanding whats wrong with code, debugging itrunning the code, seeing what happens, and fixing it. 4/ Agents will need to be made safe We founded Anthropic because we expected AI to progress very quickly and [thought] that, inevitably, safety concerns were going to be relevant. And I think thats just going to become more and more visceral this year, because I think these agents are going to become more and more integrated into the work we do. We need to be ready for the challenges, like prompt injection. [Prompt injection is an attack in which a malicious prompt is passed to a large language model in ways that its developers did not foresee or intend. One way to do this is to add the prompt to websites that models might visit.] Prompt injection is probably one of the No.1 things were thinking about in terms of, like, broader usage of agents. I think its especially important for computer use, and its something were working on very actively, because if computer use is deployed at large scale, then there could be, like, pernicious websites or something that try to convince Claude to do something that it shouldnt do. And with more advanced models, theres just more risk. We have a robust scaling policy where, as AI systems become sufficiently capable, we feel like we need to be able to really prevent them from being misused. For example, if they could help terroriststhat kind of thing. So Im really excited about how AI will be usefulits actually also accelerating us a lot internally at Anthropic, with people using Claude in all kinds of ways, especially with coding. But, yeah, therell be a lot of challenges as well. Itll be an interesting year.