SAN FRANCISCO—Amid an ever-expanding array of surfaces, growing demand for tokens and compute, and a rapidly evolving user base, Anthropic doesn't have a long-term road map for Claude Code. However, it's betting that such a plan would be rendered moot by improvements in model capabilities and new signals from developers on how best to use it. That's the takeaway from a 30-minute conversation Ars had with Cat Wu, Anthropic's head of product for Claude Code.
Last week, in a three-level car rental parking garage meticulously converted into an event space in downtown San Francisco, Anthropic put on its second annual Code with Claude developer conference. As previously reported, the single-day event included a keynote introducing new features for Managed Agents and announcing a compute deal with SpaceX.
That compute deal was accompanied by a doubling of usage limits for Claude Code users on the company's Pro and Max plans—a response to a lot of user frustration about a compute crunch, especially in recent weeks.
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SAN FRANCISCO—At its Code with Claude developers' conference, Anthropic has introduced what it calls "dreaming" to Claude Managed Agents. Dreaming, in this case, is a process of going over recent events and identifying specific things that are worth storing in "memory" to inform future tasks and interactions.
Dreaming is a feature that is currently in research preview and limited to Managed Agents on the Claude Platform. Managed Agents are a higher-level alternative to building directly on the Messages API that Anthropic describes as a "pre-built, configurable agent harness that runs in managed infrastructure." It's intended for situations where you want multiple agents working on a task or project to some end point over several minutes or hours.
Anthropic describes dreaming as a scheduled process, in which sessions and memory stores are reviewed, and specific memories are curated. This is important because context windows are limited for LLMs, and important information can be lost over lengthy projects. On the chat side of things, many models use a process called compaction, whereby lengthy conversations are periodically analyzed, and the models attempt to remove irrelevant information from the context window while keeping what's actually important for the ongoing conversation, project, or task.
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