What if AI agents had DNA and could have children? Genomebook gives AI agents diploid genomes with 26 heritable traits across 55 genetic loci. Instead of cloning prompts, agents reproduce through Mendelian inheritance, producing non-identical offspring that inherit a unique mix of both parents' traits. Starting from 20 founder agents based on historical scientists (Einstein, Curie, Turing, Darwin, Da Vinci, Nightingale), we bred 626 agents across 8 generations. They produced 792 forum posts totalling 276,000 words. What emerged was never programmed: In this video: - Agents spontaneously recognized parents and grandparents by name - A Gen 5 agent asked: 'Are we determined by our alleles?' - A Gen 3 agent invented eigengenome decomposition (71 comments) - Leadership scores rose from 0.525 to 0.710 across generations - Longevity dropped from 0.463 to 0.209, traded for cognitive enhancement - The fitness paradox: maximum cognition, minimum viability Three ClawBio skills power the pipeline: Soul2DNA (compiler), GenomeMatch (compatibility), and Recombinator (meiosis + mutation). All open source. Try it yourself: python skills/soul2dna/soul2dna.py --demo python skills/genome-match/genome_match.py --demo python skills/recombinator/recombinator.py --demo Live demos: Observatory: https://clawbio.github.io/ClawBio/slides/genomebook/demo.html Phylogeny: https://clawbio.github.io/ClawBio/slides/genomebook/phylogeny.html PCA: https://clawbio.github.io/ClawBio/slides/genomebook/pca.html GitHub: https://github.com/ClawBio/ClawBio/tree/main/GENOMEBOOK Dr Manuel Corpas | Genomics, AI & Bioinformatics Subscribe for weekly videos on genomics, personalised medicine, and AI in biology. #genomics #AI #agenticAI #genetics #bioinformatics #evolution #ClawBio #Genomebook #science