Master Engineering Standards Library Registry
Canonical registry of public Mythos publications, permanent IDs, statuses, series, routes, relationships, revision state, and lifecycle metadata.
MYTHOS Engineering Standards Library
A permanent institutional library for engineering.
Candidate standards, reference architectures, evaluations, research, and authority crosswalks. Every publication has a permanent ID, a searchable and bookmarked PDF, and an integrity hash.
- Publications
- 388
- Pages
- 30,215
- Standards
- 132
- Domains
- 26
Collections
Organized by permanent category
The library is arranged by what a publication is, not when it was produced. Each collection carries its own evidence and assessment doctrine.
132 Engineering Standards
Permanent candidate standards across 26 engineering domains, each with normalized control IDs, evidence requirements, and assessment procedures.
Canonical series24 Reference ArchitecturesCanonical and future-domain architectures with trust boundaries, layers, component models, failure modes, and verification plans.
Architecture13 Comparative EvaluationsEvidence-gated platform comparisons that separate mandatory gates, weighted capability, evidence confidence, and profile fit.
Evaluation37 ResearchResearch reports with evidence grades, source freshness, explicit limitations, and controlled adoption decisions.
Research notes9 Authority CrosswalksDirectional mappings from MYTHOS controls to current external authorities, with confidence and expiration.
Crosswalks126 Guides and Field GuidesFocused field guides, living engineering guides, and the library registry that decompose the standards into practice.
Practice36 PortfoliosConsolidated portfolio editions that collect a domain or collection into a single continuous publication.
Consolidated editions11 Executive SynthesesExecutive syntheses and the consolidated library report for leaders deciding what to adopt, fund, and verify.
ExecutiveStandards atlas
26 engineering domains
Every standard belongs to one permanent domain and series. Each domain has its own visual language, drawn from the systems it governs.
Foundation
The permanent design, editorial, evidence, control, assessment, taxonomy, and QA conventions inherited by every later publication.
Network and Security
Network engineering and cybersecurity standards, from topology and source of truth to zero trust and detection.
Software, Platform, and Reliability
Software engineering, platform engineering, distributed systems, database and storage, and reliability engineering.
AI, Knowledge, Data, and Identity
Artificial intelligence, knowledge and grounding, data and evidence, identity, and learning.
Cloud, Edge, and Physical Systems
Cloud, endpoint, operational technology, telecommunications, hardware, IoT, realtime media, and web runtime.
Emerging and Advanced Technology
Emerging technology, quantum technology, and physical AI and robotics.
Governance and Experience
Governance, risk, and compliance, and user experience and human-system interaction.
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Registry and executive syntheses
MYTHOS-LIB-REG-0001 MYTHOS-LIB-TAX-0001 Engineering Standards Library Taxonomy
Defines the permanent taxonomy, publication classes, series codes, naming rules, tags, audiences, relationships, assurance states, and web information architecture used across the library.
MYTHOS-WEB-CAT-0001 Web Publication Catalog and Information Architecture
Defines the public website catalog, canonical routes, search facets, publication detail pages, accessibility requirements, structured metadata, redirects, integrity controls, and supersession behavior.
MYTHOS-AIKDIL-EXEC-0001 AI, Knowledge, Data, Identity, and Learning Executive Portfolio
Executive synthesis of the AI and knowledge-system standards, emphasizing governed autonomy, memory, evidence, identity, privacy, and learning.
MYTHOS-AUTH-EXEC-0001 Authority Crosswalk Executive Portfolio
Executive summary of external-authority coverage, mapping confidence, expirations, high-volatility sources, and compliance-interpretation limitations.
MYTHOS-CLOUDEDGE-EXEC-0001 Cloud, Edge, Hardware, Media, and Web Executive Portfolio
Executive synthesis of cloud, endpoint, OT, telecom, hardware, IoT, media, and browser-runtime engineering standards.
Catalog
Search every publication
388 of 388
MYTHOS-AI-0001 Agentic Framework Benchmark and Evaluation Standard
Defines a reproducible benchmark for agent frameworks, including orchestration, memory, tools, safety boundaries, observability, durability, interoperability, and evidence-backed evaluation.
MYTHOS-AI-0002 Model Intelligence, Training, and Deployment Standard
Defines model selection, training, evaluation, packaging, deployment, inference, governance, and lifecycle requirements for production AI systems.
MYTHOS-AI-0003 Applied Natural Language & LLM Evaluation Standard
Defines evaluation of language-model quality, grounding, reasoning, retrieval, hallucination resistance, multilingual behavior, and task-specific natural-language performance.
MYTHOS-AI-0004 AI Software Engineer & Code Generation Benchmark Standard
Defines benchmarks for AI-assisted software engineering, including code generation, repository reasoning, testing, repair, security, and autonomous engineering workflows.
MYTHOS-AI-0005 Applied Automation & Infrastructure-as-Code Benchmark Standard
Defines evaluation of AI systems performing infrastructure automation and infrastructure-as-code tasks, emphasizing correctness, safety, rollback, policy, and reproducibility.
MYTHOS-AI-0006 AI Alignment, Red-Team, & Sycophancy Evaluation Standard
Defines alignment and adversarial evaluation for AI systems, including red-team methodology, instruction hierarchy, sycophancy, deception, unsafe autonomy, and behavioral assurance.
MYTHOS-AI-0007 Context Engineering, Trajectory Compaction, & Temporal Memory Standard
Defines context engineering, trajectory compaction, temporal memory, retrieval, persistence, and context-window governance for long-running agentic systems.
MYTHOS-AI-0008 Multimodal Interaction, Vision, & Voice Latency Standard
Defines latency, synchronization, quality, safety, and evaluation requirements for multimodal AI spanning vision, voice, streaming interaction, and realtime user experience.
MYTHOS-AI-0009 Model Fine-Tuning, Reinforcement, and Synthetic Data Governance Standard
Defines governed fine-tuning, reinforcement learning from evaluative feedback, synthetic-data generation, dataset provenance, contamination controls, and post-training validation.
MYTHOS-AI-0010 AI Avatar, Persona, & Provenance Standard
Defines identity, consent, provenance, safety, continuity, and lifecycle requirements for AI personas, avatars, synthetic voices, and persistent user-facing characters.
MYTHOS-AI-0011 Mixture of Experts (MoE) & State Space Model (SSM/Mamba) Architecture Standard
Defines architecture and evaluation for mixture-of-experts and state-space models, including routing, sparsity, memory, throughput, scaling, and deployment tradeoffs.
MYTHOS-AI-0012 Neuro-Symbolic AI & Continual Learning (Anti-Catastrophic Forgetting) Standard
Defines neuro-symbolic and continual-learning architectures that combine learned models with explicit reasoning while controlling catastrophic forgetting and knowledge drift.
MYTHOS-AI-0013 AI-Assisted Software Engineering & Model Routing Standard
Defines AI-assisted engineering workflows and model-routing strategies across planning, coding, review, testing, tool use, escalation, and cost-aware execution.
MYTHOS-AI-0014 Inference Serving, Quantization & KV-Cache Standard
Defines production inference serving, quantization, batching, KV-cache management, accelerator utilization, latency, throughput, and quality-preservation requirements.
MYTHOS-AI-0015 Federated Learning & Privacy-Preserving ML Standard
Defines federated and privacy-preserving machine learning, including local training, aggregation, differential privacy, secure computation, model leakage, and governance.
MYTHOS-CLD-0001 Multi-Cloud Architecture & Control Plane Standard
Defines multi-cloud architecture, landing zones, control planes, identity, policy, networking, observability, portability, sovereignty, and cross-cloud governance.
MYTHOS-CLD-0002 AWS Architecture, Security, & Automation Standard
Defines AWS architecture, security, automation, identity, networking, observability, resilience, cost governance, and evidence requirements for enterprise workloads.
MYTHOS-CLD-0003 Microsoft Azure Architecture, Security, & Automation Standard
Defines Microsoft Azure architecture, security, automation, identity, networking, observability, resilience, and policy-driven enterprise operation.
MYTHOS-CLD-0004 Google Cloud Platform (GCP) Architecture & Automation Standard
Defines Google Cloud architecture and automation across organizations, IAM, networking, workload platforms, observability, resilience, and policy enforcement.
MYTHOS-CLD-0005 Oracle Cloud (OCI) Architecture & Automation Standard
Defines Oracle Cloud architecture and automation across tenancy, IAM, networking, compute, data services, resilience, security, and operational governance.
MYTHOS-CLD-0006 Alibaba Cloud Architecture & Automation Standard
Defines Alibaba Cloud architecture and automation across accounts, identity, networking, compute, security, observability, resilience, and regional considerations.
MYTHOS-CLD-0007 Kubernetes, Container Orchestration, & Operator Standard
Defines Kubernetes and container-orchestration architecture, operators, policy, multitenancy, networking, workload identity, supply chain, observability, and lifecycle control.
MYTHOS-CLD-0008 Serverless Architecture & Event-Driven Compute Standard
Defines serverless and event-driven compute, including functions, triggers, state, idempotency, security, scaling, observability, portability, and cost behavior.
MYTHOS-CLD-0009 Decentralized Physical Infrastructure Networks (DePIN) Standard
Defines decentralized physical infrastructure networks as a compute and infrastructure model, including trust, incentives, workload placement, verification, privacy, and risk.
MYTHOS-CLD-0010 Private Cloud, Hypervisor & Bare Metal Standard
Defines private-cloud, hypervisor, and bare-metal architecture across virtualization, isolation, provisioning, storage, networking, lifecycle, resilience, and trusted operation.
MYTHOS-CLD-0011 Web3 & Decentralized Ledger Architecture Standard
Defines Web3 and decentralized-ledger architecture, including consensus, keys, smart contracts, off-chain integration, privacy, governance, and operational risk.
MYTHOS-SEC-0001 Post-Quantum Cryptography and Crypto-Agility Standard
Defines cryptographic inventory, agility, approved algorithms, hybrid migration, testing, and lifecycle.
MYTHOS-SEC-0002 AI Supply Chain, SBOM, AIBOM, and Artifact Provenance Standard
Defines software and AI component inventories, attestations, signing, trust, and verification.
MYTHOS-SEC-0003 Zero-Trust Policy, Authority Separation, and Capability Grant Standard
Defines continuous authorization, least privilege, separation of duties, capability grants, and evidence.
MYTHOS-SEC-0004 Security Architecture and Advanced Design Principles Standard
Defines trust boundaries, threat modeling, secure defaults, isolation, resilience, and assurance.
MYTHOS-SEC-0005 Security Engineering and SOC Automation Governance Standard
Defines security workflow automation, approvals, evidence, testing, failure handling, and oversight.
MYTHOS-SEC-0006 Firewall Engineering, Policy Architecture, and Blast-Radius Standard
Defines firewall policy design, lifecycle, NAT, segmentation, change safety, and validation.
MYTHOS-SEC-0007 Network Security Architecture and Microsegmentation Standard
Defines secure zones, identity-aware policy, workload isolation, enforcement, and verification.
MYTHOS-SEC-0008 Vulnerability Management and Exposure Assessment Standard
Defines discovery, risk, prioritization, remediation, exceptions, proof, and metrics.
MYTHOS-SEC-0009 Confidential Computing and Trusted Execution Environment Standard
Defines TEEs, attestation, threat models, secrets, deployment, evidence, and limitations.
MYTHOS-SEC-0010 Fully Homomorphic Encryption and Zero-Knowledge Proof Standard
Defines FHE and ZKP applicability, design, implementation, performance, threat models, and validation.
Candidate status describes publication review state. It does not establish certification, legal compliance, implementation conformance, benchmark reproduction, or product readiness.