Blended Efficiency
The metric comparing total cost of a hybrid human-agent team against the cost of an equivalent fully-human team delivering the same output.
Definition
Blended Efficiency compares the total cost of a hybrid human-agent team against the cost of an equivalent fully-human team delivering the same output. It is calculated as:
Total agentic team cost / Estimated cost of equivalent human-only team
The numerator includes all costs of the agentic approach: human salaries (across all Hybrid Squad roles), AI compute spend (API tokens, model inference costs), and infrastructure costs (sandboxed environments, evaluation pipelines, monitoring tooling). The denominator is the estimated fully-loaded cost of a traditional team delivering the same scope — typically calculated from historical project data or industry benchmarks for equivalent team size and output.
A Blended Efficiency below 1.0 means the agentic team costs less than the human-only equivalent. A ratio above 1.0 means the agentic approach is more expensive.
Interpretation depends on maturity stage:
- Initial adoption (months 1 to 3) — ratios above 1.0 are expected. Teams are investing in infrastructure, building Eval Harnesses, curating Golden Samples, and learning new workflows. The setup cost amortizes over subsequent months.
- Stabilization (months 3 to 6) — the ratio should trend toward 1.0 as the team builds reusable context assets, improves spec quality, and increases the Operator Leverage Ratio. Persistent ratios above 1.2 during this phase indicate process issues worth investigating.
- At scale (beyond 6 months) — the target is below 1.0. If the ratio remains above 1.0 after six months of operation, the team should re-evaluate whether the work profile is well-suited to agentic execution. Not all software development work benefits from agent delegation — highly novel, research-heavy, or deeply ambiguous work may cost more to specify and validate than to implement directly.
Blended Efficiency is reviewed during the monthly FinOps Review alongside Token Budget trends and Cost per Feature breakdowns. Together, these metrics provide a complete economic picture: Token Budget tracks raw compute spend, Cost per Feature tracks unit economics, and Blended Efficiency tracks the aggregate business case.