{
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    "topicCount": 25,
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        "Agent interoperability",
        "Autopoiesis",
        "Category definition",
        "Clean Architecture",
        "Closed-loop control",
        "Distributed systems patterns",
        "Durable execution",
        "Enaction",
        "Future architectures",
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        "Inference scheduling",
        "Inference serving",
        "Local-first systems",
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            "id": "friston-free-energy-2010",
            "title": "The free-energy principle: a unified brain theory?",
            "abstract": "Foundational source for the free-energy principle; cited as a distinct computational framework rather than a synonym for teleodynamics.",
            "topic": "Active inference",
            "sourceType": "Peer-reviewed review paper",
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            "lastReviewed": "2026-06-24",
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            "authors": "Karl Friston",
            "publisher": "Nature Reviews Neuroscience",
            "published": "2010",
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        {
            "id": "a2a-spec",
            "title": "A2A Protocol Specification",
            "abstract": "Primary project source for communication between independently developed agent systems.",
            "topic": "Agent interoperability",
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            "authors": "A2A Project",
            "publisher": "Linux Foundation",
            "published": "Current specification",
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        },
        {
            "id": "maturana-varela-autopoiesis-1980",
            "title": "Autopoiesis and Cognition: The Realization of the Living",
            "abstract": "Primary source for autopoiesis and organizational self-production; runtime translations remain analogical unless explicitly formalized.",
            "topic": "Autopoiesis",
            "sourceType": "Foundational book",
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            "year": "1980",
            "lastReviewed": "2026-06-24",
            "url": "https://link.springer.com/book/10.1007/978-94-009-8947-4",
            "primary": true,
            "authors": "Humberto R. Maturana and Francisco J. Varela",
            "publisher": "Springer",
            "published": "1980",
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            "id": "varela-maturana-uribe-autopoiesis-1974",
            "title": "Autopoiesis: the organization of living systems, its characterization and a model",
            "abstract": "Original formal characterization and model of autopoietic organization in living systems.",
            "topic": "Autopoiesis",
            "sourceType": "Peer-reviewed research paper",
            "status": "Foundational theory",
            "year": "1974",
            "lastReviewed": "2026-06-24",
            "url": "https://pubmed.ncbi.nlm.nih.gov/4407425/",
            "primary": true,
            "authors": "Francisco G. Varela, Humberto R. Maturana, and Ricardo Uribe",
            "publisher": "Biosystems",
            "published": "1974",
            "citation": {
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        {
            "id": "miruntime-report-definition",
            "title": "Machine Intelligence Runtime",
            "abstract": "Foundational MiRuntime editorial report covering the category definition, architecture, governance, developer workflows, and research gaps.",
            "topic": "Category definition",
            "sourceType": "MiRuntime editorial report",
            "status": "Editorial synthesis",
            "year": "2026",
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            "url": "https://miruntime.com/research/reports/machine-intelligence-runtime/",
            "primary": false
        },
        {
            "id": "microsoft-clean-architecture",
            "title": "Common Web Application Architectures: Clean Architecture",
            "abstract": "Official guidance describing inward dependency direction and separation of application core from infrastructure and UI.",
            "topic": "Clean Architecture",
            "sourceType": "Official architecture guidance",
            "status": "Production practice",
            "year": "Current",
            "lastReviewed": "2026-06-23",
            "url": "https://learn.microsoft.com/en-us/dotnet/architecture/modern-web-apps-azure/common-web-application-architectures",
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            "authors": "Microsoft",
            "publisher": "Microsoft Learn",
            "published": "Current documentation",
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            "id": "atlas-rtc-2026",
            "title": "ATLAS-RTC: Closing the Loop on LLM Agent Output with Token-Level Runtime Control",
            "abstract": "Research on monitoring and intervening at token-generation time without changing model weights.",
            "topic": "Closed-loop control",
            "sourceType": "Research paper",
            "status": "Research prototype",
            "year": "2026",
            "lastReviewed": "2026-06-20",
            "url": "https://arxiv.org/abs/2603.27905",
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            "authors": "Christopher Cruz",
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            "published": "2026-03",
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            "id": "azure-cloud-design-patterns",
            "title": "Cloud Design Patterns",
            "abstract": "Primary catalog for patterns including circuit breaker, CQRS, event sourcing, saga, and related distributed-system controls.",
            "topic": "Distributed systems patterns",
            "sourceType": "Official architecture guidance",
            "status": "Production practice",
            "year": "Current",
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            "url": "https://learn.microsoft.com/en-us/azure/architecture/patterns/",
            "primary": true,
            "authors": "Microsoft",
            "publisher": "Azure Architecture Center",
            "published": "Current documentation",
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            "id": "temporal-durable-execution",
            "title": "Temporal Platform Documentation",
            "abstract": "Official documentation for durable workflow execution and persisted event history; cited as one compatible implementation style rather than an endorsement.",
            "topic": "Durable execution",
            "sourceType": "Official vendor documentation",
            "status": "Production implementation",
            "year": "Current",
            "lastReviewed": "2026-06-23",
            "url": "https://docs.temporal.io/temporal",
            "primary": true,
            "authors": "Temporal Technologies",
            "publisher": "Temporal",
            "published": "Current documentation",
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            "id": "varela-thompson-rosch-embodied-mind-1991",
            "title": "The Embodied Mind: Cognitive Science and Human Experience",
            "abstract": "Primary source for the enactive approach to cognition and ongoing agent–environment coupling.",
            "topic": "Enaction",
            "sourceType": "Foundational book",
            "status": "Foundational theory",
            "year": "1991",
            "lastReviewed": "2026-06-24",
            "url": "https://mitpress.mit.edu/9780262720212/the-embodied-mind/",
            "primary": true,
            "authors": "Francisco J. Varela, Evan Thompson, and Eleanor Rosch",
            "publisher": "MIT Press",
            "published": "1991",
            "citation": {
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                "ris": "https://miruntime.com/?miruntime_citation=varela-thompson-rosch-embodied-mind-1991&format=ris"
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        },
        {
            "id": "miruntime-report-future",
            "title": "Machine Intelligence Runtime Architectures and the Future of Artificial Intelligence",
            "abstract": "Research input spanning runtime intelligence, managed execution, protocols, security, performance, hardware, and future scenarios.",
            "topic": "Future architectures",
            "sourceType": "MiRuntime editorial report",
            "status": "Editorial synthesis",
            "year": "2026",
            "lastReviewed": "2026-06-20",
            "url": "https://miruntime.com/research/reports/machine-intelligence-runtime-architectures-future-ai/",
            "primary": false
        },
        {
            "id": "onnx-runtime",
            "title": "ONNX Runtime Documentation",
            "abstract": "A cross-platform inference runtime illustrating the model-serving layer below MIR.",
            "topic": "Inference runtimes",
            "sourceType": "Official documentation",
            "status": "Production implementation",
            "year": "Current",
            "lastReviewed": "2026-06-20",
            "url": "https://onnxruntime.ai/docs/",
            "primary": true,
            "authors": "Microsoft and ONNX Runtime contributors",
            "publisher": "ONNX Runtime",
            "published": "Current documentation",
            "citation": {
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                "ris": "https://miruntime.com/?miruntime_citation=onnx-runtime&format=ris"
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        },
        {
            "id": "vllm-docs",
            "title": "vLLM Documentation",
            "abstract": "An inference and serving engine used to distinguish model scheduling from governed agent execution.",
            "topic": "Inference runtimes",
            "sourceType": "Official documentation",
            "status": "Production implementation",
            "year": "Current",
            "lastReviewed": "2026-06-20",
            "url": "https://docs.vllm.ai/",
            "primary": true,
            "authors": "vLLM project",
            "publisher": "vLLM",
            "published": "Current documentation",
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        },
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            "id": "triton-dynamic-batching",
            "title": "Triton Inference Server: Dynamic Batcher",
            "abstract": "Primary documentation for dynamic batching in an inference server.",
            "topic": "Inference scheduling",
            "sourceType": "Vendor documentation",
            "status": "Production implementation",
            "year": "Current",
            "lastReviewed": "2026-06-20",
            "url": "https://docs.nvidia.com/deeplearning/triton-inference-server/user-guide/docs/user_guide/batcher.html",
            "primary": true,
            "authors": "NVIDIA",
            "publisher": "NVIDIA",
            "published": "Current documentation",
            "citation": {
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                "ris": "https://miruntime.com/?miruntime_citation=triton-dynamic-batching&format=ris"
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        },
        {
            "id": "triton-architecture",
            "title": "NVIDIA Triton Inference Server Documentation",
            "abstract": "Primary documentation for heterogeneous model serving, backends, scheduling, batching, and operational integration.",
            "topic": "Inference serving",
            "sourceType": "Vendor documentation",
            "status": "Production implementation",
            "year": "Current",
            "lastReviewed": "2026-06-23",
            "url": "https://docs.nvidia.com/deeplearning/triton-inference-server/user-guide/docs/index.html",
            "primary": true,
            "authors": "NVIDIA",
            "publisher": "NVIDIA",
            "published": "Current documentation",
            "citation": {
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                "ris": "https://miruntime.com/?miruntime_citation=triton-architecture&format=ris"
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        },
        {
            "id": "local-first-2019",
            "title": "Local-first software: You own your data, in spite of the cloud",
            "abstract": "Foundational local-first principles adapted here to runtime control, placement, and user ownership.",
            "topic": "Local-first systems",
            "sourceType": "Research essay",
            "status": "Published research",
            "year": "2019",
            "lastReviewed": "2026-06-20",
            "url": "https://www.inkandswitch.com/essay/local-first/",
            "primary": true,
            "authors": "Martin Kleppmann et al.",
            "publisher": "Ink & Switch",
            "published": "2019",
            "citation": {
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                "ris": "https://miruntime.com/?miruntime_citation=local-first-2019&format=ris"
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        },
        {
            "id": "aws-agentcore",
            "title": "Amazon Bedrock AgentCore Runtime Developer Guide",
            "abstract": "Current vendor example of managed hosting and lifecycle controls for agents and tools.",
            "topic": "Managed agent runtimes",
            "sourceType": "Vendor documentation",
            "status": "Vendor implementation",
            "year": "Current",
            "lastReviewed": "2026-06-20",
            "url": "https://docs.aws.amazon.com/bedrock-agentcore/latest/devguide/agents-tools-runtime.html",
            "primary": true,
            "authors": "Amazon Web Services",
            "publisher": "AWS",
            "published": "Current documentation",
            "citation": {
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                "ris": "https://miruntime.com/?miruntime_citation=aws-agentcore&format=ris"
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        },
        {
            "id": "google-agent-platform",
            "title": "Gemini Enterprise Agent Platform Overview",
            "abstract": "Current vendor example of a platform for deploying, governing, and observing agents.",
            "topic": "Managed agent runtimes",
            "sourceType": "Vendor documentation",
            "status": "Vendor implementation",
            "year": "Current",
            "lastReviewed": "2026-06-20",
            "url": "https://docs.cloud.google.com/gemini-enterprise-agent-platform/overview",
            "primary": true,
            "authors": "Google Cloud",
            "publisher": "Google Cloud",
            "published": "Current documentation",
            "citation": {
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        },
        {
            "id": "mlflow-model-registry",
            "title": "MLflow Model Registry",
            "abstract": "Primary documentation for model versioning, lineage, aliases, metadata, and lifecycle management.",
            "topic": "Model lifecycle and lineage",
            "sourceType": "Official documentation",
            "status": "Production implementation",
            "year": "Current",
            "lastReviewed": "2026-06-23",
            "url": "https://mlflow.org/docs/latest/ml/model-registry/",
            "primary": true,
            "authors": "MLflow project",
            "publisher": "MLflow",
            "published": "Current documentation",
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            "id": "otel-genai",
            "title": "OpenTelemetry Semantic Conventions for Generative AI Systems",
            "abstract": "Vendor-neutral semantic conventions for traces, metrics, events, and operations involving generative AI.",
            "topic": "Observability",
            "sourceType": "Official specification",
            "status": "Evolving specification",
            "year": "Current",
            "lastReviewed": "2026-06-24",
            "url": "https://github.com/open-telemetry/semantic-conventions-genai",
            "primary": true,
            "authors": "OpenTelemetry project",
            "publisher": "Cloud Native Computing Foundation",
            "published": "Current specification repository",
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            "id": "mcp-spec-2025",
            "title": "Model Context Protocol Specification — 2025-11-25",
            "abstract": "Authoritative protocol requirements for connecting AI applications with tools, resources, and prompts.",
            "topic": "Protocols and tools",
            "sourceType": "Protocol specification",
            "status": "Published specification",
            "year": "2025",
            "lastReviewed": "2026-06-24",
            "url": "https://modelcontextprotocol.io/specification/2025-11-25",
            "primary": true,
            "authors": "Model Context Protocol project",
            "publisher": "Model Context Protocol",
            "published": "2025-11-25",
            "citation": {
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        },
        {
            "id": "vigil-2025",
            "title": "VIGIL: A Reflective Runtime for Self-Healing LLM Agents",
            "abstract": "A research prototype for reflective diagnosis and guarded repair around agent execution.",
            "topic": "Recovery and reflection",
            "sourceType": "Research paper",
            "status": "Research prototype",
            "year": "2025",
            "lastReviewed": "2026-06-20",
            "url": "https://arxiv.org/abs/2512.07094",
            "primary": true,
            "authors": "Christopher Cruz",
            "publisher": "arXiv",
            "published": "2025-12",
            "citation": {
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                "ris": "https://miruntime.com/?miruntime_citation=vigil-2025&format=ris"
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        {
            "id": "nist-airmf-2023",
            "title": "Artificial Intelligence Risk Management Framework (AI RMF 1.0)",
            "abstract": "Voluntary framework for governing, mapping, measuring, and managing AI risk.",
            "topic": "Risk management",
            "sourceType": "Government framework",
            "status": "Published guidance",
            "year": "2023",
            "lastReviewed": "2026-06-20",
            "url": "https://www.nist.gov/itl/ai-risk-management-framework",
            "primary": true,
            "authors": "National Institute of Standards and Technology",
            "publisher": "NIST",
            "published": "2023-01-26",
            "citation": {
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                "ris": "https://miruntime.com/?miruntime_citation=nist-airmf-2023&format=ris"
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        },
        {
            "id": "nist-genai-profile-2024",
            "title": "Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile",
            "abstract": "Companion profile describing generative-AI risk considerations and suggested actions.",
            "topic": "Risk management",
            "sourceType": "Government profile",
            "status": "Published guidance",
            "year": "2024",
            "lastReviewed": "2026-06-20",
            "url": "https://www.nist.gov/publications/artificial-intelligence-risk-management-framework-generative-artificial-intelligence",
            "primary": true,
            "authors": "National Institute of Standards and Technology",
            "publisher": "NIST",
            "published": "2024-07-26",
            "citation": {
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        },
        {
            "id": "airi-2026",
            "title": "AI Runtime Infrastructure",
            "abstract": "Research framing for an execution-time layer that observes and intervenes around agent behavior.",
            "topic": "Runtime architecture",
            "sourceType": "Research paper",
            "status": "Research",
            "year": "2026",
            "lastReviewed": "2026-06-20",
            "url": "https://arxiv.org/abs/2603.00495",
            "primary": true,
            "authors": "Christopher Cruz",
            "publisher": "arXiv",
            "published": "2026-03",
            "citation": {
                "bibtex": "https://miruntime.com/?miruntime_citation=airi-2026&format=bibtex",
                "ris": "https://miruntime.com/?miruntime_citation=airi-2026&format=ris"
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        },
        {
            "id": "test-time-compute-2024",
            "title": "Scaling LLM Test-Time Compute Optimally Can Be More Effective than Scaling Model Parameters",
            "abstract": "Primary research on allocating inference-time compute as a separate capability and systems concern.",
            "topic": "Runtime intelligence",
            "sourceType": "Research paper",
            "status": "Research",
            "year": "2024",
            "lastReviewed": "2026-06-20",
            "url": "https://arxiv.org/abs/2408.03314",
            "primary": true,
            "authors": "Charlie Snell, Jaehoon Lee, Kelvin Xu, and Aviral Kumar",
            "publisher": "arXiv / ICLR",
            "published": "2024-08",
            "citation": {
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                "ris": "https://miruntime.com/?miruntime_citation=test-time-compute-2024&format=ris"
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        },
        {
            "id": "self-consistency-2022",
            "title": "Self-Consistency Improves Chain of Thought Reasoning in Language Models",
            "abstract": "Foundational inference-time sampling and aggregation method for reasoning tasks.",
            "topic": "Runtime intelligence",
            "sourceType": "Research paper",
            "status": "Research",
            "year": "2022",
            "lastReviewed": "2026-06-20",
            "url": "https://arxiv.org/abs/2203.11171",
            "primary": true,
            "authors": "Xuezhi Wang et al.",
            "publisher": "arXiv / ICLR",
            "published": "2022-03",
            "citation": {
                "bibtex": "https://miruntime.com/?miruntime_citation=self-consistency-2022&format=bibtex",
                "ris": "https://miruntime.com/?miruntime_citation=self-consistency-2022&format=ris"
            }
        },
        {
            "id": "tree-of-thoughts-2023",
            "title": "Tree of Thoughts: Deliberate Problem Solving with Large Language Models",
            "abstract": "Primary research on runtime search over intermediate reasoning states.",
            "topic": "Runtime intelligence",
            "sourceType": "Research paper",
            "status": "Research",
            "year": "2023",
            "lastReviewed": "2026-06-20",
            "url": "https://arxiv.org/abs/2305.10601",
            "primary": true,
            "authors": "Shunyu Yao et al.",
            "publisher": "arXiv / NeurIPS",
            "published": "2023-05",
            "citation": {
                "bibtex": "https://miruntime.com/?miruntime_citation=tree-of-thoughts-2023&format=bibtex",
                "ris": "https://miruntime.com/?miruntime_citation=tree-of-thoughts-2023&format=ris"
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            "id": "owasp-agentic-threats",
            "title": "Agentic AI Threats and Mitigations",
            "abstract": "Threat-model guidance for agentic systems, including tool, identity, memory, and autonomy risks.",
            "topic": "Runtime security",
            "sourceType": "Security guidance",
            "status": "Published guidance",
            "year": "Current",
            "lastReviewed": "2026-06-20",
            "url": "https://genai.owasp.org/resource/agentic-ai-threats-and-mitigations/",
            "primary": true,
            "authors": "OWASP Agentic Security Initiative",
            "publisher": "OWASP",
            "published": "Current guidance",
            "citation": {
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                "ris": "https://miruntime.com/?miruntime_citation=owasp-agentic-threats&format=ris"
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