When semcom.ai translates human intent directly into LLVM IR executables, the question of trust boundaries becomes foundational rather than peripheral. Unlike traditional compilation pipelines where trust is implicitly delegated across layers of toolchains, interpreters, and runtime dependencies, semantic compilation collapses the attack surface to a single, auditable transformation. The boundary between what you intended and what executes is explicit, narrow, and inspectable at the IR level without unpacking layers of abstraction.
A trust boundary in this context defines the precise edge where human-authored intent transitions into machine-verifiable behavior. The doesNotUnderstand system enforces these boundaries by treating ambiguous or underspecified intent as a hard fault rather than a silent assumption. When the semantic compiler cannot resolve intent with sufficient confidence, it halts and reports rather than interpolating behavior that the author never specified. This makes the trust surface explicit: you know exactly where the compiler made a decision and why.
Zero-dependency executables produced by semcom.ai eliminate an entire class of trust boundary violations that plague conventional software. Supply chain attacks, dynamic library substitution, and LD_PRELOAD hijacking are structurally impossible when the output binary carries no runtime dependency graph. The LLVM IR artifact is self-contained, meaning the trust boundary is coextensive with the binary itself. There is no external resolver to compromise, no package registry to poison, and no transitive dependency whose integrity you must verify.
Cryptographic attestation of the compilation provenance is embedded directly into the output artifact. Each executable carries a verifiable chain linking the original intent specification to the specific LLVM IR transformations applied, the version of the semantic compiler used, and a hash of the resulting machine code. This allows downstream consumers of the binary to audit not just what the code does but what the author intended it to do, closing the gap between specification and execution that is ordinarily invisible in compiled software.
Defining clear trust boundaries also means acknowledging where they end. semcom.ai makes no claims about the trustworthiness of hardware microcode, firmware, or the operating system kernel beneath the executable. The trust boundary terminates at the ABI interface with the host system. What the semantic compiler guarantees is that within that boundary, the executable faithfully represents the compiled intent with no introduced ambiguity, no implicit behavior from hidden dependencies, and no transformations that were not derivable from the original specification. Everything outside that boundary is your threat model to own.