Notes
How it works
Hindsight sits between me and my agents. My preferences live in Hindsight instead of inside the agents, so the check stays independent.
- It stores what my time and risk are worth.
- It keeps rules for what it can undo, which limit bends first, and when to wake me.
- It asks only when my answer would change the pick by a lot.
- A checker with a fresh context compares each claim to a record.
Constraints I designed around
| I'm asleep for 8 hours | Rules I set at bedtime make the calls, and anything costly waits for me. |
|---|---|
| A fare expires in 20 minutes | The 24-hour rule makes the booking free to undo, so Hindsight books it and flags it. |
| The agent makes mistakes | Hindsight checks each claim against a record, and I can change any pick with one tap. |
| Instinct has no API | Change sends the redirect through the chat. |
| iMessage renders very little | The audit opens from a link card. |
| Refundability is unknown | Hindsight treats it as non-refundable, and the card says so. |
| The cheap bed might sell out | Hindsight books a refundable bed if one fits my 30%. If none fits, it books nothing and the card says what waiting could cost. A hostel rarely holds a bed, so Hindsight never claims one is held. |
Assumptions
The trip is booked 7 or more days out, directly with the airline, so the 24-hour rule applies. Hindsight can read booking emails and card charges. Prices are in CAD for one traveller.
Alternatives I rejected
| A simulated version of me | Digital twins predicted new money choices poorly (r = 0.20, Park et al. 2024). |
|---|---|
| A long interview at setup | People skip it, and personal questions feel invasive. |
| Agents debating each other | Two agents can agree on a wrong fare, so I check against records instead. |
What's real and what's simulated
The agents' options, prices and quotes come from my Instinct and Muse chats on Sep 27, 2026. Hindsight's messages, bookings and checks are simulated from those options, and nothing was bought. The founder and saver rows, the 3 AM routing and the examples under What comes next are illustrative.
Sources
- Jason Yuan's Mercury OS, for fading steps you aren't reading.
- Dot at New Computer, for showing memory as short stories.
- Hivemind's own site, for the type scale and hairlines.
- NASA flight rules, for making decisions ahead of time instead of mid-emergency.
- FAA alert colors (14 CFR 25.1322), for orange and red.
- SBAR handoffs, for the single 3 AM message. A structured handoff program cut medical errors by 23% (Starmer et al. 2014).
- Flighty, for times and terminals.
- Malle et al. 2015. People blame a robot for not acting almost as much as for acting.
- Dietvorst et al. 2018. Letting people adjust an algorithm raised its use from 32% to 73%.
- Park et al. 2024. Simulated people predicted money choices poorly.
- Shalowitz et al. 2006. Proxies guessed a patient's choice right 68% of the time.
- Liu et al. People kept 78.7% of the settings from a few questions asked up front.
- US DOT 14 CFR 259.5(b)(4), the 24-hour rule.