scenario: Vendor demo agent: marketing claims vs operations

agent_type: generic demo agent

interpretation: The canonical worked example: a '90% autonomous' agent is a 61.6% PAA agent. Marketing reports the first factor; operations lives with the product of all four.

formula: PAA = P(A) x P(C|A) x P(R|A,C) x P(T|A,C,R)

concept_by: Michał Piszczek


scenario: Coding agent with CI + deterministic tests

agent_type: software engineering agent

interpretation: Strong evidence pipeline (diffs, test runs, CI logs) keeps the gap small: raw 85% vs PAA ~72%. Deterministic tests are the cheapest independent validator.


scenario: Coding agent, no tests, self-review only

interpretation: Same autonomy, no independent validation: PAA collapses to ~19%. The agent grading its own homework does not count as R.


scenario: Customer support bot with human escalation

agent_type: support agent

interpretation: Escalation lowers P(A) but the evidence trail (transcripts, resolution codes) keeps the rest of the pipeline honest: PAA ~53%.


scenario: Invoice-processing RPA+LLM hybrid

agent_type: document processing agent

interpretation: Narrow domain, structured outputs, replayable decisions: PAA ~80% — the highest realistic band today.


scenario: Autonomous research agent, unverifiable claims

agent_type: research agent

interpretation: Runs alone happily but its citations rarely survive independent checking: PAA ~13%. High raw autonomy with low proof is risk, not productivity.


scenario: Agent output verified after deployment

agent_type: batch pipeline agent

interpretation: Validation exists but lands after the decision window: T gate crushes PAA to ~21%. Proof after the deploy is a post-mortem, not a safeguard.


scenario: Regulated-industry agent with audit trail

agent_type: compliance agent

interpretation: Lower autonomy by design, near-perfect evidence: PAA ~52% and every accepted unit is defensible in an audit.


scenario: Fleet at scale: 1000 tasks/day, Proof Debt dynamics

agent_type: mixed fleet

interpretation: PAA ~45%: of 880 autonomous tasks daily, only ~449 arrive proven. The remainder accrues as Proof Debt: ProofDebt(t+1) = max(0, ProofDebt(t) + Generated - Proven - Rejected).


scenario: Agent with different-model-family cross-check

agent_type: content generation agent

interpretation: Validation by a different model family counts as independent R (unlike self-consistency): PAA ~56%.


scenario: Human-in-the-loop at irreversible boundaries only

agent_type: operations agent

interpretation: Humans gate only irreversible actions; everything else ships with evidence: PAA ~62% — the pragmatic frontier of 2026 deployments.


scenario: Perfect gates (theoretical ceiling)

agent_type: reference

interpretation: PAA = 100% requires every unit of work autonomous, evidenced, independently validated and on time. A ceiling, not a target: sustainable autonomy cannot exceed proof capacity.