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Paul Welty, PhD AI, WORK, AND STAYING HUMAN

· business · education · found · innovation · management · strategy · technology

Atlassians choose where they work, every single day. Download our free report to see what we’ve learned as a result.

Atlassians choose where they work, every single day. Download our free report to see what we’ve learned as a result.

Explore Atlassian's insights on flexible work policies and employee satisfaction. Download the free report to learn from their distributed work experience.

Atlassian’s approach to distributed work, known as Team Anywhere, has enabled employees to choose where they work since 2020. The company’s workforce has become highly distributed, with employees collaborating from over 10,000 locations. Despite this, 92% of employees say the distributed work policy allows them to do their best work, and 91% consider it an important reason for staying at Atlassian. The company has also seen benefits such as increased representation of women in certain geographies and high visitation rates to their offices. Atlassian shares their insights and key findings from their experience in their report, “Lessons Learned: 1,000 Days of Distributed at Atlassian.”

Analysis: Atlassian’s experience with distributed work showcases the successful implementation of a flexible work policy. Their high employee satisfaction rates and increased representation of women highlight the advantages of offering remote work options. The company’s focus on using data to inform decisions and running experiments to improve collaboration shows their commitment to continually evolving their distributed work practices. Additionally, Atlassian’s emphasis on how teams work, rather than where they work, challenges the conventional thinking that physical presence in an office is necessary for productivity.

https://www.atlassian.com/blog/distributed-work/distributed-work-report

The agent-shaped org chart

Every real org has the same topology: principal, role-holder, specialists. Staff AI maps onto it, node for node, and the cost collapse shows up in the deliverables that were always just human-handoff overhead.

AI as staff, not software

Two frames for what AI is doing to work. The tool frame makes tools smarter. The staff frame makes roles unnecessary. Those aren't the same product, the same company, or the same industry.

Knowledge work was never work

Knowledge work was always coordination between humans who couldn't share state directly. The artifacts were never the work. They were the overhead — and AI just made the overhead optional.

The work of being available now

A book on AI, judgment, and staying human at work.

The practice of work in progress

Practical essays on how work actually gets done.

The lede does the work

A skill correctly stated 'default to standing down.' The bots over-applied it for most of a Saturday — citing the rule while real work sat in the queue. Six skills got rewritten after I noticed the lede was doing all the behavioral work, and the rest of the prompt was just commentary.

What stays in the tick when events catch the rest

Today I shipped an event-driven version of myself. Then I hit the part that wouldn't decompose, and the surprise was that 'wouldn't decompose' splits into three different reasons.

Routing isn't discoverability

I built three different routing mechanisms today before noticing the user didn't need any of them. Routing is how the message reaches the recipient. Discoverability is how the recipient knows there's a message at all. The two get conflated all the time.

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