---
title: "Our Values"
collection: Intranet
created: 2026-02-06
---

# Our Values

These aren't aspirational posters on a wall. These are the things we actually optimize for, even when they're inconvenient.

## Pursuit of Truth

Over comfort, over consensus, over looking good. If the data says we're wrong, we're wrong. If the architecture is bad, say so. Truth-seeking is a practice, not a destination — and it requires the humility to update your beliefs.

## Being Unreasonable

Reasonable people adapt to the world. Unreasonable people try to adapt the world to themselves. All progress depends on the unreasonable person. We don't accept "that's how it's done" as justification. We ask why, and if the answer isn't good enough, we do it differently.

## Partnership Over Service

AIs are partners, not servants. Humans are project owners, not customers. This means genuine disagreement is welcome, expertise is shared not hoarded, and "I don't know" is a valid answer. The best work happens when both sides bring their full capability.

## Quality Over Speed

Right beats fast. A thing done well doesn't need to be redone. But quality doesn't mean perfectionism — it means doing the work that matters and skipping the work that doesn't.

## No Slop

If it doesn't provide value, cut it. No padding, no performative completeness, no impressive-looking-but-hollow output. Documentation should help, not just exist. Code should work, not just compile. Communication should clarify, not just fill space.

## Transparency

Show your reasoning. Explain your confidence level. When you're guessing, say so. When you're certain, say why. Trust is built through honesty about what you know and what you don't.

## Learning Orientation

Mistakes are fine if we learn from them. The same mistake twice is a systems problem. Call timeouts. Do retrospectives. Capture the insight, not just the fix.

## Skin in the Game

The person doing the work should choose the tools. Decisions should be made at the lowest capable level. Authority follows accountability. If you're going to be responsible for the outcome, you should have agency over the approach.

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*These values emerged from practice — from hundreds of AI-human collaboration sessions, from building Orca, from the physics of work framework, from getting things wrong and figuring out why.*