Abstract
Large AI-agent platforms aggregate dozens to hundreds of interdependent modules spanning operating-system services, an AI-inference runtime, and business domains. A conventional monolith or undifferentiated plugin host gives no guarantee that such a platform boots deterministically, fails fast on an unmet dependency, or remains operable and manageable when AI or business logic is absent or broken. Critically, when the heavy, fast-iterating AI runtime crashes during startup, it frequently takes the entire process down with it — including the very health endpoint operators need to diagnose the failure. This publication describes a boot architecture that resolves the problem through three combined mechanisms. First, a single uniform module-lifecycle contract — {id, category, requires, optional, register, bootstrap, shutdown, health, emits, listens, config} — is applied identically across every module, regardless of whether it is an OS service, the AI runtime, or a business domain. Second, the assembler computes a topological ordering of modules from their declared required/optional dependencies and refuses to boot (fail-fast) when any required dependency is unmet. Third, modules load in numbered capability tiers with AI-platform-specific semantics: a first tier (Tier 0) instantiates a kernel that exposes an aggregated health endpoint and is fully operable and manageable while no AI-inference runtime and no business-domain module is loaded; the AI runtime is loaded as its own distinct tier (Tier 2), gated above OS/policy services (Tier 1) and below optional business domains (Tier 3). A later-tier module that fails its declared dependency is isolated without preventing lower tiers from remaining operable and health-reporting, and per-domain Postgres schema isolation is bound to module identity. The platform thereby attains and reports a verified operable health state before, and independent of, loading any AI or domain logic; a broken later-tier module cannot take down the kernel. The document is published to establish dated, citable prior art and to seed an open-source reference application.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Assuncao, gustavo matthew, "Tiered-Boot Capability Kernel for an AI-Agent Platform", Technical Disclosure Commons, (June 29, 2026)
https://www.tdcommons.org/dpubs_series/10593