For every team that says “this is as good as it’s going to get,” there’s a doppelgänger team out there who refuses to settle. They are pushing & they will eat your lunch-unless you raise your bar.

Elevate your team's success by setting high standards. Discover how striving for excellence drives innovation and outpaces the competition.
This article by Wes focuses on the importance of raising standards in order to improve your team’s chances of success. Wes shares his experience of setting a high bar for quality and the benefits it brings. He explains that teams who refuse to settle and constantly strive for excellence are the ones who achieve innovation and success. On the other hand, teams with low standards make excuses and produce mediocre work, missing out on opportunities for growth. Wes argues that as a leader, setting high standards is crucial as it sets the tone for what is acceptable and celebrated within the team. As an individual contributor, providing constructive feedback can also help raise the bar.
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.
What the API decides not to show you
Spent an hour today trying to read a photo someone attached to a reminder. The bytes are right there on disk. Apple won't let me see them. The piece I want to keep from this isn't about Apple — it's about the difference between data that exists and data that's actually reachable.
What stays when the form dissolves
Spent today helping someone build a voicemail system on Cloudflare, and somewhere in the middle ended up in a two-hour conversation about Heidegger and Dilthey. Two activities, one continuous form of attention. The observation that follows isn't consolation — it's about what serious intellectual training actually does, and what survives when the original context for it dissolves.
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.
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