Teams
Compare teams on optimization headroom, verify a contracted workforce against evidence, and find exactly where enablement pays off.
Workforce
Optimization headroom
Recoverable tokens under your waste rules — the team where action pays off most, first
- ML Platform124M tokens15%
- 2Growth111M tokens17%
- 3Mobile111M tokens13%
- 4SRE Core108M tokens18%
- 5Analytics106M tokens17%
- 6Checkout93M tokens12%
- 7Cloud Foundations88M tokens16%
- 8API Platform88M tokens9%
- 9Developer Experience51M tokens7%
Product Engineering
Led by Priya Nair · 182 engineers
| Team | Manager | Adoption | Accept. | Tokens | Optimizable | Craft | Risks |
|---|---|---|---|---|---|---|---|
| Checkout | Ana Duarte | 91% | 71% | 775M tokens | 93M tokens(12%) | 78+4 | 4 |
| Growth | Ravi Menon | 82% | 63% | 650M tokens | 111M tokens(17%) | 69-2 | 1 |
| Mobile | Sara Kim | 88% | 69% | 850M tokens | 111M tokens(13%) | 76+6 | 2 |
Platform
Led by Marcus Feld · 121 engineers
| Team | Manager | Adoption | Accept. | Tokens | Optimizable | Craft | Risks |
|---|---|---|---|---|---|---|---|
| API Platform | Jonas Berg | 94% | 77% | 975M tokens | 88M tokens(9%) | 84+3 | 2 |
| Developer Experience | Lena Fischer | 97% | 81% | 725M tokens | 51M tokens(7%) | 88+2 | 1 |
Infrastructure & SRE
Led by Deepa Rao · 88 engineers
| Team | Manager | Adoption | Accept. | Tokens | Optimizable | Craft | Risks |
|---|---|---|---|---|---|---|---|
| SRE Core | Owen Clarke | 70% | 58% | 600M tokens | 108M tokens(18%) | 66-3 | 2 |
| Cloud Foundations | Mei Lin | 74% | 62% | 550M tokens | 88M tokens(16%) | 70+1 | — |
Data & ML
Led by Tom Weaver · 109 engineers
| Team | Manager | Adoption | Accept. | Tokens | Optimizable | Craft | Risks |
|---|---|---|---|---|---|---|---|
| ML Platform | Carlos Ruiz | 83% | 67% | 825M tokens | 124M tokens(15%) | 73+5 | 3 |
| Analytics | Nadia Hassan | 76% | 60% | 625M tokens | 106M tokens(17%) | 68+0 | — |