In this episode, Fraser McGruer, Nick Hare, Peter Coghill and Chris Wragg explore one of the most enduring pieces of technical advice: have you tried turning it off and on again?
What begins with a glitchy video call and a reluctant router reboot quickly develops into a wide-ranging discussion about systems, states and the surprisingly deep logic behind rebooting—not just in computers, but in societies, economies and even our own lives.
The team unpack what actually happens when you power cycle a device, from memory leaks and zombie processes to cosmic rays flipping bits in memory. From there, they build a broader framework: what counts as a “state”, what a “good state” might be, and when a system can—or cannot—be reset.
Peter introduces a theory of rebootability, with criteria including whether a system has an external reference point, whether it depends on consensus, and whether it can be restarted from outside itself. These ideas are applied to everything from national constitutions and financial systems to climate change and rainforest collapse.
Along the way, the conversation touches on revolutions, failed societal resets, post-war reconstruction, and the limits of trying to “go back” to a supposedly better past. The episode closes with personal reflections on resets—from Covid lockdowns to life-changing career shifts and the everyday reboot of sleep.
In this episode:
Why turning something off and on again actually works
What a “state” is (and why it matters)
The concept of a “known good state”
Peter’s theory of rebootability
Systems that can’t be reset (climate, ecosystems, global economy)
The role of consensus in rebooting social systems
Why revolutions and resets often fail
The appeal of starting over—from software to psychology
Personal and societal examples of “reboots”
Key ideas and concepts:
State: The internal condition of a system that determines how it responds to inputs
Known good state: A reliable baseline you can return to
Rebootability: Whether a system can be reset to a functioning state
Bootstrap problem: A system often needs something external to restart it
Path dependency / hysteresis: How the past shapes what’s possible now
Consensus vs reality: Some systems only work if people agree they work
Tipping points: States from which recovery is difficult or impossible
Examples discussed:
Routers, computers and memory leaks
Chess, board games and “soft locks”
The climate and rainforest collapse
Written constitutions as “system blueprints”
Currency resets (e.g. post-war Germany)
The French Revolution and failed systemic resets
Post-war Germany and Japan vs Iraq and Afghanistan
Religious and mythological “reboots” (e.g. the Flood narrative)
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