{ "schema": "longtermcapabilities-evidence/v2", "version": "1.48.0", "releaseId": "lts-1.48.0-first-run-admin-bootstrap", "generated": "2026-07-25T13:00:00Z", "evidenceTypes": [ { "id": "verified-client-case-study", "name": "Verified client case study", "definition": "Client work approved for public attribution and factual outcome reporting.", "publicBoundary": "Names, outcomes, and metrics appear only with verified approval." }, { "id": "approved-anonymized-case-study", "name": "Approved anonymized case study", "definition": "Client work approved for public discussion without identifying the client.", "publicBoundary": "Context is generalized and unsupported metrics are omitted." }, { "id": "key-personnel-past-performance", "name": "Key-personnel past performance", "definition": "Relevant work performed by the principal before or outside the current entity.", "publicBoundary": "It is not presented as LongTermCapabilities corporate or federal-prime past performance." }, { "id": "corporate-past-performance", "name": "Corporate past performance", "definition": "Verified work contracted and delivered by the current business entity.", "publicBoundary": "Published only when contract and disclosure authority are verified." }, { "id": "method-demonstration", "name": "Method demonstration", "definition": "A controlled example showing how a method, interface, or evidence pattern works.", "publicBoundary": "It is not a customer outcome and may use synthetic data." }, { "id": "technical-reference-architecture", "name": "Technical reference architecture", "definition": "A public architecture pattern intended to support technical review and discussion.", "publicBoundary": "It is not proof that a specific client system is secure or production-ready." }, { "id": "public-rd-project", "name": "Public R&D project", "definition": "A public research or experimental system used to explore methods and constraints.", "publicBoundary": "Research behavior is not represented as commercial deployment performance." }, { "id": "publication-research-note", "name": "Publication or research note", "definition": "Original technical analysis supported by named sources and limitations.", "publicBoundary": "It is informative, not legal, audit, or certification advice." } ], "evidenceRecords": [ { "id": "key-personnel-enterprise-systems", "title": "Enterprise Microsoft systems delivery across rule-heavy domains", "path": "/evidence/key-personnel-enterprise-systems/", "evidenceType": "Key-personnel past performance", "verificationStatus": "Publicly documented key-personnel background", "sector": [ "Insurance and benefits technology", "Logistics and transportation", "Financial and tax workflows", "Public-sector applications" ], "capabilities": [ "legacy-modernization", "business-logic-preservation", "application-data-integration" ], "context": "Mike Kappel has more than two decades of public professional history delivering and modernizing Microsoft-based enterprise systems across commercial and public-sector contexts.", "problem": "Long-lived systems accumulated hidden rules, SQL-heavy behavior, integration constraints, reporting dependencies, and operational continuity requirements.", "constraints": [ "Client-specific details and outcomes are not published without approval", "Experience spans work performed before and outside the current LongTermCapabilities entity", "No corporate federal prime past performance is asserted" ], "role": "Senior software engineer, software architect, technical lead, mentor, and consultant depending on the engagement.", "scope": [ ".NET and SQL Server application delivery", "Legacy Web Forms, Classic ASP, MVC, Web API, and modern .NET transitions", "Stored-procedure and reporting workflows", "Integration, testing, parity validation, and team guidance" ], "technologies": [ "C#", ".NET / ASP.NET", "SQL Server / T-SQL", "TypeScript / Angular", "Web API", "Azure and AWS-connected systems" ], "method": [ "Trace behavior before replacement", "Create testable service and data seams", "Use comparison and characterization evidence", "Document architecture and decisions", "Retain direct technical review" ], "artifacts": [ "Architecture maps", "Behavior and parity tests", "Integration contracts", "Technical specifications", "Decision records", "Operational support documentation" ], "outcome": "The public record demonstrates sustained key-personnel capability in business-critical Microsoft systems; client-specific performance metrics are intentionally not claimed here.", "quantifiedMetrics": [], "limitations": "This is key-personnel experience, not LongTermCapabilities corporate government past performance. It does not identify confidential clients or claim unverified metrics.", "confidentialityStatus": "Public summary derived from approved professional history", "relatedServices": [ "dotnet-sql-modernization", "architecture-reliability-office", "joint-discovery-workshop" ], "lastReviewed": "2026-07-25", "slug": "key-personnel-enterprise-systems", "evidenceTypeId": "key-personnel-past-performance", "summary": "Mike Kappel has more than two decades of public professional history delivering and modernizing Microsoft-based enterprise systems across commercial and public-sector contexts.", "publicStatus": "public", "audiences": [ "enterprise", "government", "partner" ], "problemOrClaim": "Long-lived systems accumulated hidden rules, SQL-heavy behavior, integration constraints, reporting dependencies, and operational continuity requirements.", "systemContext": "Mike Kappel has more than two decades of public professional history delivering and modernizing Microsoft-based enterprise systems across commercial and public-sector contexts.", "inputsSourceState": [ "Client-specific details and outcomes are not published without approval", "Experience spans work performed before and outside the current LongTermCapabilities entity", "No corporate federal prime past performance is asserted" ], "representativeCases": [ ".NET and SQL Server application delivery", "Legacy Web Forms, Classic ASP, MVC, Web API, and modern .NET transitions", "Stored-procedure and reporting workflows", "Integration, testing, parity validation, and team guidance" ], "observedResult": "The public record demonstrates sustained key-personnel capability in business-critical Microsoft systems; client-specific performance metrics are intentionally not claimed here.", "namedReviewRole": "Senior software engineer, software architect, technical lead, mentor, and consultant depending on the engagement.", "decisionSupported": "The public record demonstrates sustained key-personnel capability in business-critical Microsoft systems; client-specific performance metrics are intentionally not claimed here.", "artifactsRetained": [ "Architecture maps", "Behavior and parity tests", "Integration contracts", "Technical specifications", "Decision records", "Operational support documentation" ], "boundaryStatement": "This is key-personnel experience, not LongTermCapabilities corporate government past performance. It does not identify confidential clients or claim unverified metrics.", "relatedResources": [ "modernization-risk-review", "legacy-modernization-evidence-inventory" ], "relatedInsights": [ "modernize-dotnet-sql-without-business-logic-drift" ], "publishedDate": "2026-07-21", "contentOwner": "Mike Kappel", "status": "published" }, { "id": "legacy-modernization-without-behavioral-drift", "title": "Legacy modernization without behavioral drift", "path": "/evidence/legacy-modernization-without-behavioral-drift/", "evidenceType": "Method demonstration", "verificationStatus": "Public method demonstration", "sector": [ "Cross-sector" ], "capabilities": [ "legacy-modernization", "business-logic-preservation" ], "context": "A business-critical .NET and SQL system carries behavior across code, stored procedures, forms, reports, jobs, integrations, and operational workarounds.", "problem": "A rewrite can silently change calculations, approvals, permissions, reports, or exception handling before the organization notices.", "constraints": [ "No client data", "No invented metrics", "Unknown and disputed behavior remain explicit" ], "role": "Demonstrates the architecture and evidence method used to frame a modernization decision.", "scope": [ "Inventory system surfaces", "Capture representative scenarios", "Add characterization tests", "Identify reversible seams", "Compare old and new outputs", "Sequence bounded releases" ], "technologies": [ ".NET", "SQL Server", "Stored procedures", "Web applications", "Integration and reporting" ], "method": [ "Source tracing", "Characterization testing", "Parity scenario catalog", "Old-versus-new comparison", "Domain-owner review" ], "artifacts": [ "Current-state architecture", "Business-rule map", "Stored-procedure inventory", "Parity catalog", "Comparison report", "Sequenced roadmap" ], "outcome": "Shows how a modernization decision can be made with inspectable behavior evidence rather than rewrite assumptions.", "quantifiedMetrics": [], "limitations": "This is not a named client case study and does not claim that all legacy behavior can be discovered or preserved perfectly.", "confidentialityStatus": "Public-safe synthetic method demonstration", "relatedServices": [ "dotnet-sql-modernization" ], "lastReviewed": "2026-07-25", "slug": "legacy-modernization-without-behavioral-drift", "evidenceTypeId": "method-demonstration", "summary": "A business-critical .NET and SQL system carries behavior across code, stored procedures, forms, reports, jobs, integrations, and operational workarounds.", "publicStatus": "public", "audiences": [ "enterprise", "government", "partner" ], "problemOrClaim": "A rewrite can silently change calculations, approvals, permissions, reports, or exception handling before the organization notices.", "systemContext": "A business-critical .NET and SQL system carries behavior across code, stored procedures, forms, reports, jobs, integrations, and operational workarounds.", "inputsSourceState": [ "No client data", "No invented metrics", "Unknown and disputed behavior remain explicit" ], "representativeCases": [ "Inventory system surfaces", "Capture representative scenarios", "Add characterization tests", "Identify reversible seams", "Compare old and new outputs", "Sequence bounded releases" ], "observedResult": "Shows how a modernization decision can be made with inspectable behavior evidence rather than rewrite assumptions.", "namedReviewRole": "Demonstrates the architecture and evidence method used to frame a modernization decision.", "decisionSupported": "Shows how a modernization decision can be made with inspectable behavior evidence rather than rewrite assumptions.", "artifactsRetained": [ "Current-state architecture", "Business-rule map", "Stored-procedure inventory", "Parity catalog", "Comparison report", "Sequenced roadmap" ], "boundaryStatement": "This is not a named client case study and does not claim that all legacy behavior can be discovered or preserved perfectly.", "relatedResources": [ "modernization-risk-review", "legacy-modernization-evidence-inventory" ], "relatedInsights": [ "modernize-dotnet-sql-without-business-logic-drift" ], "publishedDate": "2026-07-21", "contentOwner": "Mike Kappel", "status": "published" }, { "id": "ai-evaluation-blocked-action", "title": "AI evaluation and blocked-action program", "path": "/evidence/ai-evaluation-blocked-action/", "evidenceType": "Method demonstration", "verificationStatus": "Public method demonstration", "sector": [ "B2B software", "Document and case workflows" ], "capabilities": [ "ai-production-evaluation", "human-reviewed-ai" ], "context": "An AI reviewer, copilot, or agent produces useful demonstrations, but acceptable failure, human review, and prohibited downstream actions remain undefined.", "problem": "Unsupported, ambiguous, or access-violating output may reach users or downstream systems without adequate measurement or authority.", "constraints": [ "No production customer data", "No safety certification", "No claim of error elimination" ], "role": "Demonstrates a release-evidence and human-authority pattern.", "scope": [ "Define task and risk categories", "Build representative cases", "Separate failure types", "Calibrate automated measures against human review", "Set release and rollback thresholds", "Log blocked actions and overrides" ], "technologies": [ "RAG", "Language models", "Evaluation harnesses", "Human-review interfaces", "Versioned test data" ], "method": [ "Golden and adversarial cases", "Failure taxonomy", "Reviewer calibration", "Blocked-action controls", "Release scorecards" ], "artifacts": [ "Evaluation dataset", "Failure taxonomy", "Calibration report", "Reviewer worksheet", "Release scorecard", "Operational runbook" ], "outcome": "Shows how an AI pilot can be converted into an inspectable proceed, narrow, remediate, or stop decision.", "quantifiedMetrics": [], "limitations": "This is an evaluation pattern, not a formal audit, safety certification, or guarantee that a system will be error-free.", "confidentialityStatus": "Public-safe synthetic method demonstration", "relatedServices": [ "ai-production-readiness", "ai-evaluation-release-gates" ], "lastReviewed": "2026-07-25", "slug": "ai-evaluation-blocked-action", "evidenceTypeId": "method-demonstration", "summary": "An AI reviewer, copilot, or agent produces useful demonstrations, but acceptable failure, human review, and prohibited downstream actions remain undefined.", "publicStatus": "public", "audiences": [ "enterprise", "government", "partner" ], "problemOrClaim": "Unsupported, ambiguous, or access-violating output may reach users or downstream systems without adequate measurement or authority.", "systemContext": "An AI reviewer, copilot, or agent produces useful demonstrations, but acceptable failure, human review, and prohibited downstream actions remain undefined.", "inputsSourceState": [ "No production customer data", "No safety certification", "No claim of error elimination" ], "representativeCases": [ "Define task and risk categories", "Build representative cases", "Separate failure types", "Calibrate automated measures against human review", "Set release and rollback thresholds", "Log blocked actions and overrides" ], "observedResult": "Shows how an AI pilot can be converted into an inspectable proceed, narrow, remediate, or stop decision.", "namedReviewRole": "Demonstrates a release-evidence and human-authority pattern.", "decisionSupported": "Shows how an AI pilot can be converted into an inspectable proceed, narrow, remediate, or stop decision.", "artifactsRetained": [ "Evaluation dataset", "Failure taxonomy", "Calibration report", "Reviewer worksheet", "Release scorecard", "Operational runbook" ], "boundaryStatement": "This is an evaluation pattern, not a formal audit, safety certification, or guarantee that a system will be error-free.", "relatedResources": [ "ai-production-readiness-evidence-pack", "enterprise-ai-procurement-evidence-checklist" ], "relatedInsights": [ "ai-demo-to-defensible-release-decision", "durable-ai-systems-memory-state-retries-evidence" ], "publishedDate": "2026-07-21", "contentOwner": "Mike Kappel", "status": "published" }, { "id": "governed-knowledge-system", "title": "Governed knowledge system for internal teams", "path": "/evidence/governed-knowledge-system/", "evidenceType": "Technical reference architecture", "verificationStatus": "Public reference architecture", "sector": [ "Knowledge and document workflows" ], "capabilities": [ "application-data-integration", "ai-production-evaluation", "human-reviewed-ai" ], "context": "Policies, SOPs, support notes, tickets, and technical knowledge are fragmented across systems with inconsistent ownership and freshness.", "problem": "Generic retrieval can mix unapproved drafts with authoritative content and produce answers that are difficult to audit or refuse appropriately.", "constraints": [ "No client corpus", "No claim that retrieval eliminates hallucinations", "Access policy remains client-owned" ], "role": "Demonstrates source governance, retrieval boundaries, citation, refusal, and escalation architecture.", "scope": [ "Inventory sources and owners", "Assign trust and lifecycle states", "Preserve role and tenant boundaries", "Index provenance metadata", "Require citations and refusal", "Escalate conflicting answers" ], "technologies": [ "RAG", "Semantic search", "Metadata", "Access control", "Document review" ], "method": [ "Source registry", "Trust-state model", "Access-boundary design", "Retrieval tests", "Citation and refusal rubric" ], "artifacts": [ "Source registry", "Trust-state model", "Access-boundary diagram", "Retrieval test set", "Citation rubric", "Content-review queue" ], "outcome": "Shows how internal retrieval can remain tied to source authority, access boundaries, and named human escalation.", "quantifiedMetrics": [], "limitations": "This reference architecture does not claim legal certainty, automatic conflict resolution, or universal suitability.", "confidentialityStatus": "Public-safe reference architecture", "relatedServices": [ "ai-production-readiness", "ai-evaluation-release-gates" ], "lastReviewed": "2026-07-25", "slug": "governed-knowledge-system", "evidenceTypeId": "technical-reference-architecture", "summary": "Policies, SOPs, support notes, tickets, and technical knowledge are fragmented across systems with inconsistent ownership and freshness.", "publicStatus": "public", "audiences": [ "enterprise", "government", "partner" ], "problemOrClaim": "Generic retrieval can mix unapproved drafts with authoritative content and produce answers that are difficult to audit or refuse appropriately.", "systemContext": "Policies, SOPs, support notes, tickets, and technical knowledge are fragmented across systems with inconsistent ownership and freshness.", "inputsSourceState": [ "No client corpus", "No claim that retrieval eliminates hallucinations", "Access policy remains client-owned" ], "representativeCases": [ "Inventory sources and owners", "Assign trust and lifecycle states", "Preserve role and tenant boundaries", "Index provenance metadata", "Require citations and refusal", "Escalate conflicting answers" ], "observedResult": "Shows how internal retrieval can remain tied to source authority, access boundaries, and named human escalation.", "namedReviewRole": "Demonstrates source governance, retrieval boundaries, citation, refusal, and escalation architecture.", "decisionSupported": "Shows how internal retrieval can remain tied to source authority, access boundaries, and named human escalation.", "artifactsRetained": [ "Source registry", "Trust-state model", "Access-boundary diagram", "Retrieval test set", "Citation rubric", "Content-review queue" ], "boundaryStatement": "This reference architecture does not claim legal certainty, automatic conflict resolution, or universal suitability.", "relatedResources": [ "ai-production-readiness-evidence-pack", "enterprise-ai-procurement-evidence-checklist" ], "relatedInsights": [ "ai-demo-to-defensible-release-decision", "durable-ai-systems-memory-state-retries-evidence" ], "publishedDate": "2026-07-21", "contentOwner": "Mike Kappel", "status": "published" }, { "id": "ai-documentation-review", "title": "AI-assisted documentation review for legacy codebases", "path": "/evidence/ai-documentation-review/", "evidenceType": "Method demonstration", "verificationStatus": "Public method demonstration", "sector": [ "Software engineering" ], "capabilities": [ "ai-production-evaluation", "technical-evidence-procurement" ], "context": "A legacy codebase contains years of implementation knowledge but incomplete documentation, slowing modernization estimates and onboarding.", "problem": "Generated documentation can widen claims, miss edge cases, or become stale if it is treated as authoritative without source links and reviewer ownership.", "constraints": [ "Bounded repositories and file types", "Human review required", "Source state retained" ], "role": "Demonstrates an AI-assisted documentation workflow with source support and reviewer acceptance.", "scope": [ "Define typed outputs", "Require source references", "Generate bounded drafts", "Review against code and tests", "Record accepted, rejected, and unresolved claims", "Version output with source state" ], "technologies": [ ".NET and mixed codebases", "Language models", "Semantic search", "Markdown", "Review interfaces" ], "method": [ "Prompt contract", "Source-reference schema", "Reviewer worksheet", "Unsupported-claim log", "Versioned approval" ], "artifacts": [ "Prompt contract", "Draft documentation", "Reviewer worksheet", "Unsupported-claim log", "Approved documentation release" ], "outcome": "Shows how AI can accelerate draft documentation while human reviewers retain authority over approved technical claims.", "quantifiedMetrics": [], "limitations": "This method does not claim that AI fully understands a codebase or can replace accountable technical review.", "confidentialityStatus": "Public-safe method demonstration", "relatedServices": [ "ai-production-readiness", "ai-evaluation-release-gates" ], "lastReviewed": "2026-07-25", "slug": "ai-documentation-review", "evidenceTypeId": "method-demonstration", "summary": "A legacy codebase contains years of implementation knowledge but incomplete documentation, slowing modernization estimates and onboarding.", "publicStatus": "public", "audiences": [ "enterprise", "partner" ], "problemOrClaim": "Generated documentation can widen claims, miss edge cases, or become stale if it is treated as authoritative without source links and reviewer ownership.", "systemContext": "A legacy codebase contains years of implementation knowledge but incomplete documentation, slowing modernization estimates and onboarding.", "inputsSourceState": [ "Bounded repositories and file types", "Human review required", "Source state retained" ], "representativeCases": [ "Define typed outputs", "Require source references", "Generate bounded drafts", "Review against code and tests", "Record accepted, rejected, and unresolved claims", "Version output with source state" ], "observedResult": "Shows how AI can accelerate draft documentation while human reviewers retain authority over approved technical claims.", "namedReviewRole": "Demonstrates an AI-assisted documentation workflow with source support and reviewer acceptance.", "decisionSupported": "Shows how AI can accelerate draft documentation while human reviewers retain authority over approved technical claims.", "artifactsRetained": [ "Prompt contract", "Draft documentation", "Reviewer worksheet", "Unsupported-claim log", "Approved documentation release" ], "boundaryStatement": "This method does not claim that AI fully understands a codebase or can replace accountable technical review.", "relatedResources": [ "human-reviewed-ai-workflow-checklist" ], "relatedInsights": [ "human-reviewed-ai-proposal-approval-execution" ], "publishedDate": "2026-07-21", "contentOwner": "Mike Kappel", "status": "published" }, { "id": "public-rd-governed-handoff", "title": "Governed handoff and machine-readable evidence research", "path": "/evidence/public-rd-governed-handoff/", "evidenceType": "Public R&D project", "verificationStatus": "Publicly inspectable research artifacts", "sector": [ "AI-ready documentation and handoff" ], "capabilities": [ "technical-evidence-procurement", "human-reviewed-ai" ], "context": "Long-running software and AI-assisted work requires durable handoff records, source boundaries, review status, and public/private separation.", "problem": "Unstructured agent memory and undocumented handoffs can turn stale or unverified statements into apparent facts.", "constraints": [ "Public artifacts contain no credentials or private client data", "Machine-readable surfaces are read-only", "Human review is required before durable claims are promoted" ], "role": "Public R&D into versioned operating memory, evidence indexes, route manifests, source labels, and receiver startup packets.", "scope": [ "Typed memory files", "Source and trust labels", "Public/private separation", "Machine-readable route and service exports", "Validation and release manifests" ], "technologies": [ "Markdown", "JSON", "Static websites", "Python validation", "AI-assisted documentation workflows" ], "method": [ "Source-of-truth hierarchy", "Review gates", "Hash and mirror checks", "Public/private deployment separation", "Receiver-oriented read order" ], "artifacts": [ "UAI memory package", "Public route index", "Service and pricing exports", "Documentation index", "Release validation reports" ], "outcome": "Provides inspectable public examples of evidence-oriented documentation and machine-readable handoff practices.", "quantifiedMetrics": [], "limitations": "Public R&D is not a client engagement, certification, or proof of suitability for a specific regulated environment.", "confidentialityStatus": "Public R&D; private operating memory excluded from deployment", "relatedServices": [ "ai-production-readiness", "architecture-reliability-office", "joint-discovery-workshop" ], "lastReviewed": "2026-07-25", "slug": "public-rd-governed-handoff", "evidenceTypeId": "public-rd-project", "summary": "Long-running software and AI-assisted work requires durable handoff records, source boundaries, review status, and public/private separation.", "publicStatus": "public", "audiences": [ "enterprise", "government", "partner" ], "problemOrClaim": "Unstructured agent memory and undocumented handoffs can turn stale or unverified statements into apparent facts.", "systemContext": "Long-running software and AI-assisted work requires durable handoff records, source boundaries, review status, and public/private separation.", "inputsSourceState": [ "Public artifacts contain no credentials or private client data", "Machine-readable surfaces are read-only", "Human review is required before durable claims are promoted" ], "representativeCases": [ "Typed memory files", "Source and trust labels", "Public/private separation", "Machine-readable route and service exports", "Validation and release manifests" ], "observedResult": "Provides inspectable public examples of evidence-oriented documentation and machine-readable handoff practices.", "namedReviewRole": "Public R&D into versioned operating memory, evidence indexes, route manifests, source labels, and receiver startup packets.", "decisionSupported": "Provides inspectable public examples of evidence-oriented documentation and machine-readable handoff practices.", "artifactsRetained": [ "UAI memory package", "Public route index", "Service and pricing exports", "Documentation index", "Release validation reports" ], "boundaryStatement": "Public R&D is not a client engagement, certification, or proof of suitability for a specific regulated environment.", "relatedResources": [ "human-reviewed-ai-workflow-checklist" ], "relatedInsights": [ "human-reviewed-ai-proposal-approval-execution" ], "publishedDate": "2026-07-21", "contentOwner": "Mike Kappel", "status": "published" } ] }