Contribute
Respond to a defined mission with case structures, decision criteria, failure patterns, demonstrations or evaluation cases.
Expert network
Turn judgement into operating knowledge.
Experts complete focused missions, verify one another’s contributions and create traceable knowledge assets used to build and evaluate specialised AI workers.
The question
How does specialist judgement become a reliable part of the worker?
01
Procedure captured
02
Exceptions identified
03
Quality rubrics defined
04
Evaluation cases reviewed
Operational knowledge
The intelligence that resolves difficult cases rarely fits inside the formal procedure.
01Experienced practitioners know which evidence matters, how common explanations fail, when an exception is material, which tool to use next and where their own authority ends.
02Focused missions turn that judgement into procedure decomposition, case patterns, corrected outputs, preference data and hidden evaluations. Independent verification, contributor lineage and permitted use remain attached as those assets enter production.
Contribution path
Review expert knowledge before it influences a worker.
The process records origin, review, permission and version state.
Qualify
Confirm relevant operating experience and contribution scope.
Capture
Document procedures, exceptions, evidence rules and rubrics.
Review
Validate the contribution with appropriate peers or customer experts.
Evaluate
Test the resulting worker behaviour on representative cases.
Version
Record approved changes, permissions and release use.
The expert foundry
Convert hard-won practitioner judgement into verified operational intelligence.
Experts do not upload vague advice. They complete focused missions that capture how work is decomposed, which evidence matters, how exceptions are investigated and where authority must stop.
Verify
Independent practitioners and consistency checks test the contribution before it enters a production knowledge asset.
Trace and reward
Contributor lineage, permitted use, validity and value participation remain attached as the intelligence is deployed and improved.
The network turns fragmented expertise into reusable infrastructure while preserving provenance, review and economic alignment.
Knowledge control
Contribution requires explicit permission, review and confidentiality boundaries.
Expert input supplements, not overrides, the customer’s approved procedures and accountable roles.
Worker responsibility
Turn practical judgement into reviewable operating artefacts.
Participation depends on the process, confidentiality requirements and available qualified practitioners.
Procedure sequences
Describe the real stages, handoffs and completion criteria.
Evidence requirements
Identify acceptable sources, gaps and signals of reliability.
Exceptions and escalation
Define edge cases, severity and when authorised review is required.
Evaluation cases
Create representative scenarios, rubrics and expected review outcomes.
Accountable role
Human judgement and approval
Decisions with material, regulated or professional consequences stay with the named accountable role.
Relevant experience and scope checks
Confidentiality requirements
Attribution and permission records
Customer procedure approval
Peer or customer-expert review
Versioned use in evaluations and releases
Contribution quality
Evaluate the knowledge by how it improves worker behaviour.
The network should be judged on reviewed operating artefacts and evaluation coverage, not the number of names listed.
- 01Cases contributed
- 02Exception coverage
- 03Review agreement
- 04Rubric completeness
- 05Corrections identified
- 06Approved versions
Work with experts
Define the practical knowledge your worker needs to capture and test.
We can discuss customer expert participation and, where available, relevant practitioner contribution.