The mechanism
More workers can expose parallelism, but they can also repeat work, disagree about ownership or share the same wrong premise. A useful comparison holds the task, available evidence and evaluation contract fixed. It measures elapsed dependency time separately from aggregate work and communication. A join that requires both subresults inherits both failure risks; a vote does not automatically make correlated evidence independent. The source of each result matters more than the number of participants repeating it. A fixed parallel decomposition and a dynamically delegated workflow are therefore different execution designs, not guaranteed quality levels. The incident engine currently has one worker; the examples here derive coordination consequences without claiming an executing multi-agent system or a measured model reliability improvement.
- The shared task is decomposed into subresults with explicit ownership and a defined join condition.
- Independent work can overlap, but joins, coordination and conflicts add latency or repeated effort.
- Repeated-run evaluation uses the same final task oracle for single-worker and multi-worker designs.
- Reliability calculations state any independence assumption; common sources or shared failure causes can invalidate it.
Science and assumptions
Coordination can add work · explicit relationship
The chance that both required subchecks succeed equals the first success probability times the second conditioned on it.
Symbols and units
- A, B
- Success events for the two required subchecks
events
- P(A)
- Probability of success for the first subcheck
0–1
- P(B|A)
- Conditional success probability for the second
0–1
Two independent checks take 6 s and 9 s. A required 2 s merge gives ideal parallel elapsed time 11 s, while summed work is 17 s. If both checks are necessary and each succeeds with probability 0.9 independently, joint success is 0.81. If their failures are perfectly correlated, their joint success is 0.9 instead, and agreement supplies no additional independent evidence. These are hypothetical probabilities, not measured agents. Adding a worker can shorten a critical path without improving the probability that the completed task is correct.
Assumptions The product P(A)P(B) is valid only under independence. The lesson’s probabilities and durations are synthetic; no actual agent trials are reported.
Engineering example
Two independent checks take 6 s and 9 s. A required 2 s merge gives ideal parallel elapsed time 11 s, while summed work is 17 s. If both checks are necessary and each succeeds with probability 0.9 independently, joint success is 0.81. If their failures are perfectly correlated, their joint success is 0.9 instead, and agreement supplies no additional independent evidence. These are hypothetical probabilities, not measured agents. Adding a worker can shorten a critical path without improving the probability that the completed task is correct.
Distinctions and tradeoffs
Two agreeing workers are not automatically two independent sources of evidence.
Coordination can reduce waiting on independent work while adding merge cost, duplicate effort and shared failure modes.
Agent teams are engineering systems whose benefits must be evaluated against the same task and resource boundary.
Specifications and interfaces
- Mechanism boundary
- When does another worker help or hurt?
The product P(A)P(B) is valid only under independence. The lesson’s probabilities and durations are synthetic; no actual agent trials are reported.
- Evidence type
- Authored worked example
Worked explanation with a bounded numeric or state example. This lesson does not claim an executing implementation of an external model or platform.
Interfaces
- Declared input and state Input
- The shared task is decomposed into subresults with explicit ownership and a defined join condition.
- Checked outcome Output
- Separate parallel latency, total work and dependence assumptions in a same-task worker comparison.
Check your understanding
Two required independent subchecks each succeed with probability 0.9. What is the probability both succeed?
- 0.99
- 0.9
- 0.81
Answer and reasoning
0.81
Under the explicitly stated independence assumption the probabilities multiply: 0.9 × 0.9.
Evidence and scope
This is a worked explanation, not an executing external platform, model or robot. The quantities and fixtures are authored. Source scope is recorded in the automation learning review manifest; no source benchmark or private system behavior is claimed. The product P(A)P(B) is valid only under independence. The lesson’s probabilities and durations are synthetic; no actual agent trials are reported.
The worked example explains this mechanism. General numerical labs are a reference; they do not execute this lesson’s full mechanism.