I hired a new employee.

An employee that never sleeps, eats, or complains.

This employee is very technical with a huge memory.

This employee learns, improves, and iterates.

This employee likes to be taught a certain way. It needs specific directions laid out in a specific way.

This employee’s name is Claude Cowork.

AI is no longer a tool, it’s an employee

This week, I fired up the Cowork desktop app, set up integrations with my tech stack and got to work.

I asked it to analyze social media post data for a client of mine. It opened up their Hubspot account, pulled in all their social data, made recommendations and gave a 16 page executive summary.

WOW!

With this, I was able to make recommendations to the team of 5 humans, adjust our brand guide, and update our content calendar.

I repeated the process with our email campaigns. It easily found leaks and opportunities while analyzing hundreds of emails.

I then used Claude to analyze our Meta ads account.

What is amazing is I can actually have a conversation with Claude and see it working.

Claude opens the applications, starts clicking around, and it explains its every move.

It’s working right next to me on one of my screens!

I have a new employee that works for $20 a month.

I continued with analyzing my YouTube channel, and it gave me 16 pages of strategic insight.

It analyzed which themes, hooks, thumbnails perform well.

Claude identified primary and secondary viewers avatars, and even gives additional monetization strategies.

Claude did make some mistakes, but what employee doesn’t make mistakes?

I ask for corrections, and it makes corrections.

I find the better I prompt, the better my results. The better I inform my employee, the better it performs.

Moving forward this week, I plan to take the data, summaries, and plans to better inform Claude.

Specifically, set up more “skills” (.md files), and update brand information based on Claude research.

These updates should give my new employee more context and more skills to achieve better and better results.

PS: Want to see my full YouTube report? Reply to this email and I’m happy to send.

-Mark Savant

Australian tech giant Atlassian announced it will cut about 1,600 employees, roughly 10 percent of its global workforce, while restructuring the company around artificial intelligence and enterprise sales.

Atlassian builds workplace software used by millions of companies. Tools like Jira and Confluence help teams track projects, write documentation, and manage software development. For years these platforms relied heavily on human input.

Leadership says the layoffs are part of becoming an “AI-first company.” In practical terms that means fewer employees doing routine operational work and more focus on engineers who build AI features.

The company expects to spend more than $200 million on restructuring costs, including severance packages and office closures as it reorganizes the workforce around AI capabilities.

AI does not eliminate entire professions overnight. Instead it reduces how many people are required to produce the same output.

Legal AI Startup Raises $550 Million To Automate Lawyers

A Swedish startup called Legora just raised $550 million in funding, pushing its valuation to about $5.55 billion.

The company builds AI systems designed to automate legal work such as contract review, document analysis, case research, and regulatory compliance. These are tasks traditionally handled by junior lawyers and paralegals.

According to Legora’s leadership, many legal teams moved from small pilot programs to full deployment much faster than expected.

This makes sense when you look at the economics of law. Clients pay hundreds of dollars per hour for work that often involves searching documents, reviewing contracts, and preparing reports. AI systems can complete those same tasks in minutes.

That does not mean lawyers will disappear. What it means is the structure of the profession changes. Fewer entry-level legal workers may be needed because software can complete much of the preliminary work.

Investors are pouring capital into this space because legal services represent one of the largest professional industries in the world.

Employees report increasing pressure to integrate AI tools into work across the company. Some internal systems even track how frequently workers rely on AI assistants when completing tasks.

Management believes widespread AI adoption will boost productivity across engineering, logistics, and corporate operations. This has created a new kind of workplace dynamic. Some employees worry they are training the very systems that could reduce the need for their roles later.

At the same time, early results show mixed outcomes. Workers say some AI tools generate flawed code or inefficient results, which forces humans to spend additional time correcting errors.

Companies want employees to work alongside AI systems and produce far more output than before.

The future worker must understand how to collaborate with AI tools.

Read more here.

“I think, therefore I am” - Rene Descartes