Candidates negotiate for 'AI compute' resources.

Engineers interviewing at AI-focused companies now want to know how much GPU and inference capacity they will have. This shift treats AI compute as personal working capital and influences how companies think about talent acquisition, productivity, and budgets. The amount of inference compute available to an engineer increasingly determines software productivity, according to OpenAI President Greg Brockman. Inside labs like OpenAI and Anthropic, compute allocation is now treated almost like budget approval. Theory Ventures partner Tomasz Tunguz predicts engineers will soon negotiate "token budgets" alongside pay. Peter Gostev, who leads AI capability at Arena, has proposed job listings that advertise not only salary ranges but also token budgets. Hyperscalers are competing fiercely, offering six-figure credit bundles to secure fledgling ecosystems. Google for Startups headlines the movement with tiered credits reaching $350,000 for AI ventures. The scarcity of AI compute is creating a hierarchy of access within technical organizations. Teams with access to GPUs or high-performance inference budgets move faster and ship more than those left waiting in the queue.