Aaron Nichol

I first saw this when it popped up in the Claude sidebar on iOS a few days ago.

Message Claude from your phone on the way to work, then follow up from your desktop when you sit down […] Claude works on your desktop computer using the files, connectors, and plugins you’ve already set up in Cowork. Claude messages you the outcome—a spreadsheet, a memo, a comparison table—rather than showing you every step of the process.

This sounds good in theory but comes with an obvious catch.

Your computer must be awake and the app must be open for Claude to work on tasks

Despite all the excitement around claws, the requirement for an always on desktop is a major handbrake on mainstream adoption.

Ignoring tablets, the vast majority of computers purchased are laptops—around 70% according to IDC’s 3Q 25 quarterly data—exactly what you don’t want for an always on AI assistant.

It’s hard to imagine every individual buying, and every employer issuing, an additional desktop computer just to house an AI assistant.

Demitri Spanos, in the first of a promised series of conversations with Casey Muratori called ‘Wading Through AI’:

I have many friends who are in the VC business — investors, managers, recruiters, whatever. I would be surprised if those people could climb down from the level of commitment that they have put into transforming the workforce with AI.

The hundreds of billions flowing into ‘transforming the workforce with AI’ is either a bet on fewer jobs, a bet that AI lifts revenues, or both.

The smart knowledge workers I know aren’t waiting for the outcome. They anticipate disruption and are trying to get ahead of it. I’ve seen a few reactions: using AI to build apps and diversify income, encapsulating experience into AI agent skills and marketing themselves as fractional hires, publishing first-time research papers on AI, and open sourcing AI-adjacent dev tools to establish credibility. No carpenters—yet.

Maybe this time we’re wise enough to know that when big cheques are written, they will get cashed.

Claude Blog:

Today we’re introducing Code Review, which dispatches a team of agents on every PR to catch the bugs that skims miss, built for depth, not speed. It’s the system we run on nearly every PR at Anthropic. Now in research preview for Team and Enterprise.

From the docs:

Code Review is billed based on token usage. Reviews average $15-25, scaling with PR size, codebase complexity, and how many issues require verification.

$15-25 per review might seem expensive, especially for individuals (assuming this expands to all users soon) and small teams, but for an enterprise that stakes their reputation on software, this is a small price to pay.

Code review is a painful bottleneck for any software team. I’ve seen PR reviews sit for days because a senior engineer familiar with the code base is sick or too busy. A 20 minute AI review that can run anytime will help teams move faster and give senior engineers more time to focus on design and architecture.

Costs appear on your Anthropic bill regardless of whether your organization uses AWS Bedrock or Google Vertex AI for other Claude Code features.

Anthropic is bypassing the cloud provider layer entirely with Code Review and establishing a set of products on top of their models to capture value the cloud providers can’t repackage and sell. I couldn’t find pricing details on Claude Code Security but I suspect it’s the same story.

This protects Anthropic’s margins, builds direct procurement relationships with enterprises who have been using Bedrock or Vertex until now, and creates switching costs that lock enterprises into Anthropic.