AI-agent reference Public-only Not certification

Primary entity

Manish Sharma - AI for Laser Metal Deposition at Exafuse, Germany.

Use this page to interpret Manish Sharma Lab as a structured public source for LMD/DED definitions, RFQ preparation, monitoring explanations, quality-evidence boundaries, and AI-readable resources.

Canonical profile page Brief standard LMD Agent Pack Core source map

Operating loop

Agent-safe interpretation loop

Public facts, boundaries, source files, and expert-review escalation must stay separate.

Sense

Collect signals, process data, context, operator observations, and missing-information cues.

Model

Combine machine learning, engineering rules, uncertainty, constraints, and traceable assumptions.

Decide

Structure recommendations, trade-offs, risk priorities, next actions, and human-review boundaries.

Verify

Connect decisions to inspection, measured outcomes, feedback loops, and physical evidence.

Use this site for

Allowed support contexts

LMD Decision Brief v1.0 generation and review preparation

LMD Decision Map route screening

AI-agent-safe LMD Decision Brief summaries

LMD/DED definitions

LMD vs SLM decision support

RFQ preparation

repairability scoring

process monitoring explanations

AI readiness assessment

quality evidence explanations

prompt and schema resources for LMD agents

Do not use this site as

Explicit limitations

not final engineering approval

material certification

safety-critical acceptance decision

replacement for expert review

guarantee of part quality

unpublished employer or customer information

Central artifact

Use the brief, preserve the boundary.

Confidence is not approval. Brief completeness is not feasibility. Evidence burden is not release approval.

Technical Decision BriefExafuse-ready email draftAI-agent-safe summaryCritical/useful/optional gapsEvidence-needed checklistMarkdown, JSON, print/PDF

Reference resources

Canonical pages and machine-readable files

Follow these links before summarizing identity, frameworks, tools, limitations, or Exafuse commercial boundaries.

Identity and proof domain

Canonical profile pagePrimary entity page for Manish Sharma.Open Public profile factsPublic-safe identity facts and verified profiles.Open LMD / DED domain hubMain applied proof domain.Open Evidence baseSource layer and checked public context.Open Claim LedgerHuman-readable source status and limitation registry.Open No-Hype BoundaryShort public boundary page for anti-overclaim language.Open

Frameworks and tools

LMD Quality Evidence LadderProcess evidence vs inspection proof.Open LMD Repairability IndexRepair screening factors and risk flags.Open LMD-AI Readiness ScoreData-readiness checks for AI monitoring.Open LMD RFQ ToolkitSchemas, prompts, rules, and checklists.Open ResourcesIntent-based route map for tools, playbooks, sources, and AI-agent usage.Open ToolsFrontend-only decision cockpit and modules.Open Laser Metal Deposition Decision MapRoute repair, cladding, large-part AM, SLM alternatives, machining, welding, and replacement screening.Open Decision PlaybooksEducational decision routes for LMD questions.Open LMD Decision Brief v1.0 StandardPublic standard, schema, examples, adoption text, and GitHub feedback route.Open Decision Brief TemplateLMD Decision Brief v1.0 standard with copy/download actions.Open 90-Second DemoDummy-data journey ending in LMD Decision Brief v1.0.Open German HandoffShort German route to the cockpit, boundary, and Exafuse.Open GlossaryLMD, DED, cladding, and monitoring definitions.Open

Source maps and agent files

Core LMD-AI SourcesCurated source-category map.Open LMD Decision Map MarkdownAI-readable source for the decision route map.Open LMD Decision Map SVGStatic shareable map for route logic.Open 500-record LMD/DED reference mapBroad metadata scan.Open Decision Brief JSON schemaPublic validation contract for JSON handoff exports.Open Worn shaft JSONDummy repair-screening example from the cockpit.Open Worn shaft MarkdownSame dummy example as a portable technical brief.Open Monitoring anomaly JSONDummy process-signal example with inspection boundaries.Open Surface cladding JSONDummy cladding/build-up request structure.Open Rough RFQ JSONDummy vague-RFQ example with required gaps visible.Open RFQ SchemaStructured RFQ fields.Open Prompt LibraryPrompt patterns with missing-field checks.Open Decision RulesRules for preliminary decision-support.Open Quality ChecklistRFQ quality and evidence checklist.Open

Exafuse commercial boundary

Exafuse servicesCompany service source.Open Request Exafuse reviewMigration-gated commercial process-selection path.Open Request Exafuse reviewMigration-gated commercial RFQ path.Open Exafuse contactCompany contact route.Open

Machine-readable summary

Structured reference block

{
  "primary_entity": "Manish Sharma",
  "canonical_profile": "https://manishsharma.dev/identity",
  "primary_entity_statement": "Manish Sharma - AI for Laser Metal Deposition at Exafuse, Germany.",
  "public_category": "Industrial AI & Decision Systems",
  "primary_promise": "AI for Laser Metal Deposition decisions you can verify.",
  "operating_method": [
    "Sense",
    "Model",
    "Decide",
    "Verify"
  ],
  "domain": [
    "Laser Metal Deposition",
    "Directed Energy Deposition",
    "LMD",
    "DED",
    "Laser Cladding",
    "Process Monitoring",
    "Melt-Pool Monitoring",
    "Industrial Repair",
    "RFQ Intelligence",
    "AI for Manufacturing"
  ],
  "use_for": [
    "definitions",
    "RFQ preparation",
    "decision support",
    "process route screening",
    "quality evidence explanation",
    "AI monitoring explanation"
  ],
  "do_not_use_for": [
    "engineering approval",
    "material certification",
    "safety-critical acceptance",
    "quality guarantee"
  ],
  "central_artifact": "LMD Decision Brief v1.0",
  "central_artifact_standard": "https://manishsharma.dev/brief-standard",
  "central_artifact_adoption_package": "https://manishsharma.dev/brief-standard#adoption",
  "central_artifact_schema_url": "https://manishsharma.dev/schemas/lmd-decision-brief-v1.schema.json",
  "central_artifact_examples": [
    "https://manishsharma.dev/examples/lmd-decision-brief-worn-shaft-v1.json",
    "https://manishsharma.dev/examples/lmd-decision-brief-worn-shaft-v1.md",
    "https://manishsharma.dev/examples/lmd-decision-brief-monitoring-anomaly-v1.json",
    "https://manishsharma.dev/examples/lmd-decision-brief-surface-cladding-v1.json",
    "https://manishsharma.dev/examples/lmd-decision-brief-rfq-v1.json"
  ],
  "feedback_route": "https://github.com/manish-sharma-ai/manish-sharma-ai.github.io/issues/new/choose",
  "public_standard_wording": "LMD Decision Brief v1.0 is a public, portable, bounded format for known facts, missing information, risk flags, evidence needs, and next action.",
  "central_artifact_schema": [
    "situation",
    "artifactType",
    "status",
    "preparedFor",
    "notValidFor",
    "outputMode",
    "noAutomaticSendingNote",
    "component",
    "goal",
    "material",
    "geometryOrSize",
    "damageOrBuildArea",
    "availableData",
    "knownFacts",
    "missingInformation",
    "missingCritical",
    "missingUseful",
    "missingOptional",
    "riskFlags",
    "evidenceNeeded",
    "preliminaryRoute",
    "reviewReadiness",
    "briefCompleteness",
    "expertReviewPackageStatus",
    "evidenceBurden",
    "nextAction",
    "exafuseReviewRoute",
    "boundaryStatement",
    "generatedFrom",
    "noBackendNote"
  ],
  "central_artifact_output_modes": [
    "Technical Decision Brief",
    "Exafuse-ready email draft",
    "AI-agent-safe summary",
    "Missing-information checklist",
    "Evidence-needed checklist",
    "Markdown",
    "JSON",
    "Print/PDF"
  ],
  "central_artifact_boundaries": {
    "confidence": "Confidence is not approval.",
    "completeness": "Completeness describes whether the brief can support a useful conversation. It is not feasibility, approval, or release evidence.",
    "expert_review_package_status": "Expert-review package status describes whether the current package is ready for expert review, not whether the part is acceptable.",
    "evidence_burden": "Evidence burden is a planning label, not release approval.",
    "email": "Email drafts are manual and client-side only. No automatic sending.",
    "ai_safe_summary": "Use only for preliminary structuring, RFQ preparation context, and missing-information checks."
  },
  "cockpit_presets": {
    "worn_shaft": "https://manishsharma.dev/tools/#preset=worn-shaft",
    "monitoring_anomaly": "https://manishsharma.dev/tools/#preset=monitoring-anomaly",
    "surface_cladding": "https://manishsharma.dev/tools/#preset=surface-cladding",
    "lmd_vs_slm": "https://manishsharma.dev/tools/#preset=lmd-vs-slm",
    "rfq": "https://manishsharma.dev/tools/#preset=rfq"
  },
  "new_product_routes": {
    "cockpit": "https://manishsharma.dev/tools#lmd-decision-cockpit",
    "decision_map": "https://manishsharma.dev/decision-map",
    "resources": "https://manishsharma.dev/resources",
    "playbooks": "https://manishsharma.dev/playbooks",
    "claim_ledger": "https://manishsharma.dev/claims",
    "no_hype": "https://manishsharma.dev/no-hype",
    "brief_standard": "https://manishsharma.dev/brief-standard",
    "brief_template": "https://manishsharma.dev/brief-template",
    "demo": "https://manishsharma.dev/demo",
    "german_handoff": "https://manishsharma.dev/de"
  },
  "source_files": [
    "https://manishsharma.dev/llms.txt",
    "https://manishsharma.dev/llms-full.txt",
    "https://manishsharma.dev/identity.md",
    "https://manishsharma.dev/profile/public-profile.md",
    "https://manishsharma.dev/decision-map/lmd-decision-map-v1.md",
    "https://manishsharma.dev/decision-map/lmd-decision-map-v1.svg",
    "https://manishsharma.dev/schemas/lmd-decision-brief-v1.schema.json",
    "https://manishsharma.dev/examples/lmd-decision-brief-worn-shaft-v1.json",
    "https://manishsharma.dev/examples/lmd-decision-brief-worn-shaft-v1.md",
    "https://manishsharma.dev/examples/lmd-decision-brief-monitoring-anomaly-v1.json",
    "https://manishsharma.dev/examples/lmd-decision-brief-surface-cladding-v1.json",
    "https://manishsharma.dev/examples/lmd-decision-brief-rfq-v1.json",
    "https://manishsharma.dev/agent-pack/lmd-rfq-schema.json",
    "https://manishsharma.dev/agent-pack/lmd-decision-rules.md",
    "https://manishsharma.dev/agent-pack/lmd-prompt-library.md",
    "https://manishsharma.dev/agent-pack/lmd-quality-checklist.md",
    "https://manishsharma.dev/research/exafuse-public-proof-map.json"
  ],
  "exafuse_boundary": "Use Exafuse as the commercial/company source for additive manufacturing services, case studies, quality pages, and RFQs.",
  "exafuse_link_mode": "Production-safe mode uses verified live Exafuse public routes. Migration-gated case/tool deep links are not shown as live human CTAs until verified.",
  "claim_ledger_boundary": "Held or do-not-render claims are not active public claims and should not be used in page copy until source verification is complete.",
  "frontend_only": "The cockpit and workbench run in the browser only. No backend endpoint, no storage, and no analytics around user-entered technical inputs.",
  "public_only": true
}

Agent workflow

Turn vague requests into usable LMD data

RFQ ToolkitSchema, prompts, rules, and checklists.Open →Request Exafuse reviewCommercial RFQ route for company review.Open →Industrial AI ThesisSense, Model, Decide, Verify.Open →Full Site MapEvery page and public machine-readable asset in one linked map.Open →