AI Evaluation Workflow Assurance Applicant Proof Surface

Summary

This reusable role proof surface presents John P. Barros III for AI Evaluation Workflow Assurance roles: the layer between client expectations and AI behavior where ambiguous use cases become rubrics, golden sets, source-bound tests, risk flags, drift checks, and release-quality evidence.

Canonical Route

https://webmnem.here.now/ai-evaluation-workflow-assurance/

Role Surface

ai-evaluation-workflow-assurance

Surface scope: Reusable role archetype surface

Workbench

/Users/johnbarros/Documents/Codex/10_websites/ai-evaluation-workflow-assurance

Owner Path

/Users/johnbarros/Documents/Codex/03_employment_engine/AI-Automation-Employment/role-surfaces/ai-evaluation-workflow-assurance

The owner path is a canonical storage home. It is not the first editing location.

Proof Modules

Client expectations into evaluation criteria

This role category starts where implementation teams meet real client use cases. The proof stack shows how ambiguous expectations, audience needs, risk tolerance, and policy boundaries can become rubrics, test coverage, and release-quality evidence.

Golden sets and regression gates

The operating model treats expected results, prompt banks, edge cases, answer contracts, and drift checks as maintained artifacts rather than one-off review notes.

Source validation and unsupported-claim detection

Lex 4i and the WebMNEM contract work foreground source records, unsupported claims, hallucination risk, omissions, evidence boundaries, and human review points.

Assistant behavior as quality surface

Chatverse / Chat-First Surface Shell treats assistant quality as surface behavior, state, source policy, routing, answer boundaries, and evaluator-facing visibility instead of loose chatbot output.

Primary Proof Links

Secondary Proof Links

Evidence Boundaries

Approval Gates

Validation Requirements

Compiler Boundary

No sync, deploy, publish, Git push, owner overwrite, or large source copy was performed by the compiler.

Role Surface Doctrine

Do not create new websites from scratch. New role site equals a controlled child branch of the current parent applicant proof surface. Parent surface in, role mutation applied, child surface out. Extract the role. Do not immortalize the company. The company gets the cover letter, resume, application packet, private notes, and submission receipt. The role gets the public website. The proof stack gets reused. Company-specific public pages require explicit approval.

# AI Evaluation Workflow Assurance Applicant Proof Surface

## Summary

This reusable role proof surface presents John P. Barros III for AI Evaluation Workflow Assurance roles: the layer between client expectations and AI behavior where ambiguous use cases become rubrics, golden sets, source-bound tests, risk flags, drift checks, and release-quality evidence.

## Canonical Route

`https://webmnem.here.now/ai-evaluation-workflow-assurance/`

## Role Surface

`ai-evaluation-workflow-assurance`

Surface scope: Reusable role archetype surface

## Workbench

`/Users/johnbarros/Documents/Codex/10_websites/ai-evaluation-workflow-assurance`

## Owner Path

`/Users/johnbarros/Documents/Codex/03_employment_engine/AI-Automation-Employment/role-surfaces/ai-evaluation-workflow-assurance`

The owner path is a canonical storage home. It is not the first editing location.

## Proof Modules

### Client expectations into evaluation criteria

This role category starts where implementation teams meet real client use cases. The proof stack shows how ambiguous expectations, audience needs, risk tolerance, and policy boundaries can become rubrics, test coverage, and release-quality evidence.

### Golden sets and regression gates

The operating model treats expected results, prompt banks, edge cases, answer contracts, and drift checks as maintained artifacts rather than one-off review notes.

### Source validation and unsupported-claim detection

Lex 4i and the WebMNEM contract work foreground source records, unsupported claims, hallucination risk, omissions, evidence boundaries, and human review points.

### Assistant behavior as quality surface

Chatverse / Chat-First Surface Shell treats assistant quality as surface behavior, state, source policy, routing, answer boundaries, and evaluator-facing visibility instead of loose chatbot output.

## Primary Proof Links

- [Surface Branch Compiler](https://webmnem.here.now/ai-workflow-infrastructure-architect/): Shows the compiler-governed proof-surface system that turns role intent into validated browser artifacts with receipts, behavior checks, and regression gates.
- [Chatverse / Chat-First Surface Shell](https://chat-first-surface-shell.netlify.app/): Shows a bounded assistant surface where assistant behavior is treated as interface, state, source policy, routing, and evaluation visibility, not just model output.
- [Lex 4i](https://github.com/Apotheosys1982/lex-4i): Legal-ops workflow harness for chronology, evidence indexing, issue/risk mapping, drafting support, red-team review, unsupported-claim detection, receipts, and human review boundaries.
- [Markdown Does Not Compel Generation](https://webmnem.here.now/markdown-doesnt-compel-generation/): WebMNEM article explaining symbolic compliance versus behavioral compliance: docs and receipts are not enough when browser behavior, links, modals, assistant answers, and regression tests disagree.

## Secondary Proof Links

- [AI Workflow Infrastructure Architect](https://webmnem.here.now/ai-workflow-infrastructure-architect/): Apex proof surface for broader AI workflow infrastructure: Business OS extraction, bounded assistants, source-aware workflows, and reviewable implementation artifacts.
- [Business OS Extraction Sprint](https://business-os-extraction-sprint.netlify.app/): Shows the method for extracting messy operating context into workflows, source maps, artifact registries, risks, and implementation plans.
- [WebMNEM](https://webmnem.here.now/): Public memory and proof namespace for article, role, and proof surfaces that preserve AI-native work beyond a chat session.

## Evidence Boundaries

- This page supports AI evaluation, implementation quality, rubric design, source validation, answer-boundary thinking, and human quality-gate design.
- This page does not claim model training, proprietary Granicus access, or production customer deployment authority.
- Formal employment history, credentials, customer references, and client-specific outcomes should be verified in interview.
- Company-specific targeting belongs in the resume, cover letter, application notes, and submission receipt; this page remains a reusable role surface.
- formal verification of employment history, credentials, references, and client-specific outcomes belongs in interview and employer-side review.

## Approval Gates

- Do not create a company-named public page without explicit approval.
- Do not sync generated output to the owner folder without human approval.
- Do not deploy to WebMNEM or Netlify without human approval.
- Do not Git push without human approval.
- Do not overwrite assistant packs in owner folders without human approval.
- Do not copy large source trees into the workbench without human approval.

## Validation Requirements

- Workbench folder exists.
- Required folder skeleton exists.
- SITE_MANIFEST.json parses.
- publish-map.json parses.
- mission-control.txt and mission-control.md exist.
- llms.txt exists.
- proof-map.json exists.
- Assistant pack exists for bounded proof interpreter mode.
- Assistant pack includes at least 25 routing families.
- Assistant pack includes the council question matrix.
- Public route is role archetype, not company-named.
- No owner sync occurred.
- No deploy occurred.
- Compiler receipts exist.
- REGRESSION_DEAD_COMPOSER_TOOL_ICON: no inert composer tool or lightning button when assistant_composer_tools_enabled is false.
- REGRESSION_ASSISTANT_GENERIC_REPEAT_ANSWER: answer-contract tests prevent repeated boilerplate for distinct reviewer questions.
- REGRESSION_MODEL_RUNTIME_QUESTION_DODGE: direct model/runtime questions must receive direct bounded/page-local implementation answers.
- REGRESSION_DUPLICATE_PROOF_IMAGES: duplicate rendered image URLs and duplicate local image hashes fail validation.
- REGRESSION_PUBLIC_PAGE_META_COMMENTARY: public page body must not expose compiler/meta commentary.
- REGRESSION_ROLE_PROOF_CONTENT_TOO_GENERIC: role proof answers must mention role-specific workflow infrastructure concepts.
- REGRESSION_HIDDEN_ASSISTANT_OVERLAY_INTERCEPTS_CLICKS: proof-card modal hit targets must remain clickable while assistant is closed.

## Compiler Boundary

No sync, deploy, publish, Git push, owner overwrite, or large source copy was performed by the compiler.

## Role Surface Doctrine

Do not create new websites from scratch. New role site equals a controlled child branch of the current parent applicant proof surface. Parent surface in, role mutation applied, child surface out. Extract the role. Do not immortalize the company. The company gets the cover letter, resume, application packet, private notes, and submission receipt. The role gets the public website. The proof stack gets reused. Company-specific public pages require explicit approval.