Set AI adoption/spending policy: pace over cost, fund passion project tokens

February 20, 2026 at 12:31 AMstrategymedium

Situation

Codified org-wide AI tool policy: pace is priority over cost, high token spend signals productivity. CIQ will fund tokens for passion projects (learning) but not work-hour time for non-core work. Work-hour AI projects must align with core responsibilities.

Reasoning

Reframed Ryan's cost concern as a positive signal - spending on AI tools means productive use. Drew clear line between work projects (full support) and passion projects (tokens funded, not hours). Belief that AI adoption should be driven by enthusiasm and experimentation, not mandates. Right incentive structure makes adoption happen naturally.

Additional Context

Ryan raised high token costs from Cursor/VS Code context bloating. Chris Wolford simultaneously demonstrating AI acceleration (Azure/GCP prototypes in days). Nathan's team discussing 'expeditious' as the right word for velocity. AI adoption accelerating across the org.

Observed Evidence

Fathom meeting summary captured explicit policy statements: pace > cost, fund passion tokens not work-hour time, work projects must be Category 1/2.

Confidence Breakdown

30/35
Evidence
15/30
Pattern
19/20
Source
7/15
Corroboration

Reasoning Depth Analysis

Org Signal:Tells entire org that AI spending is encouraged, not scrutinized - removes adoption barrier
Who Affected:All engineers - sets company-wide AI spending policy
Precedent:First formal articulation of AI token spending policy with work/passion distinction
Consequences:Removes cost fear as barrier to AI adoption; passion project funding encourages experimentation
Timing:AI adoption accelerating across org - Chris multi-cloud prototyping, Nathan expeditious discussion

People Involved

Ryan Smith

Source

reflection

AI Confidence

78%

Related Context

🎥
Ryan <> Peter Weekly 1:1

fathom

Peter affirmed that pace is the priority over cost. High token spend is a sign of productivity, not a concern, unless it becomes extreme.

Outcome

No outcome recorded yet.

Decision ID: 19a16507-5e24-4f1e-98da-873bba074400