An architectural monograph, systems engineering specification, and empirical benchmark on deterministic in-silico synthesis verification, tri-scale streaming invariants, and biophysical safety for generative AI in computational biology. The work addresses the catastrophic asymmetry of AI hallucinations in genomic design: while hallucinated code crashes an interpreter, hallucinated nucleotide sequences cause multi-thousand-dollar physical synthesis failures and cytotoxic hazards. Features an ultra-lean, deterministic 6-gate biophysical runtime (IUPAC alphabet, Crick modulo-3 reading frame, canonical initiation, GC content and Shannon entropy, in-silico translation, and terminal stop), a dual canonical execution token SHA256(SHA256(DNA) || SHA256(Protein)) neutralizing synonymous codon bypass, subquadratic O(N log N) Locality-Sensitive Hashing (LSH-CSR), an SQLite WAL tombstone vault with zero-millisecond rejection, and low-RAM stream backpressure (64 KB). Validated across three independent cloud environments (E2B Firecracker microVMs at 560 ms boot, Kaggle kernels, Google Colab Pro at 86% token reduction) and tested against live open-science repositories (UniProtKB, EuropePMC) with 0 mocks. Includes an extensive biographical and ethical introduction chronicling the collaborative defense and open-source mentoring of twelve-year-old Kenyan builder Harun (koda2026 / bio-os) against online harassment, alongside the author's personal journey from twenty years in commercial kitchens to systems architecture. Monograph comprising Introduction (37 paragraphs), Chapters 1 through 9, affirmative Conclusion, and 30 verified primary source citations [S01]–[S30]. By Jean-Sébastien Beaulieu (SecuredMe, ORCID 0009-0007-2904-0443).
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