AI was supposed to save time. So why does it feel like it is making us work more?

In Episode 17 of Not Brothers, Mark and Ryan unpack the AI efficiency paradox: the strange pressure to keep agents running around the clock, maximize every subscription, and constantly wonder whether someone else has built a better workflow that is leaving you behind.

Ryan talks about the practical bottleneck created when AI agents move faster than humans can review their work. Code, tasks, and deliverables can stack up in parallel—but somebody still has to verify that the output is correct, useful, and worth keeping. More production does not automatically mean more progress.

They connect AI FOMO to the older workplace obsession with being busy. If the goal is meaningful impact, then free time, strategic thinking, and the ability to step away may be better signs of success than a dashboard full of running agents.

The conversation also gets into token leaderboards, lines-of-code metrics, false productivity, AI-generated rework, and why companies will struggle to measure the economics of AI usage. Mark and Ryan argue that AI works best as an augmentation layer: remove repetitive work, improve the quality of the outcome, and free humans to do the thinking that actually matters.

The bottom line: use AI where it produces real value. Stop using it just because it is available—and do not be afraid to shut the agents down and walk away.

Chapters:

00:00 — The AI efficiency paradox

00:34 — Why faster AI can make us work longer

01:25 — AI FOMO and the pressure to run agents 24/7

02:18 — When agent output outruns human review

03:07 — Letting agents work while you step away

03:49 — AI and the new work-life integration problem

05:23 — Being busy is not the achievement

06:31 — Downtime, tinkering, and technology burnout

07:38 — Why technologists fantasize about going off-grid

09:18 — Token usage is not productivity

10:50 — Broken metrics: lines of code and AI leaderboards

13:08 — The coming economics of token efficiency

13:57 — When using AI takes longer than doing it yourself

14:46 — AI FOMO and fear of being replaced

15:46 — AI should remove busywork, not people

17:12 — A practical AI win: website content migration

18:19 — What clients actually want from agency AI use

20:25 — The cost-cutting trap and losing human expertise

21:54 — Most people are not running 15-agent companies

22:58 — Experimenting without worshipping the workflow

24:20 — Know when to stop the loop and walk away

25:11 — Wrap-up