Hoffman predicts that by 2026, AI agents will move beyond coding into broader professional domains, enabling parallelized, intelligent workflows that transform how individuals and organizations operate. He highlights a shift toward entrepreneurial work models, driven by AI-native developers who orchestrate systems without deep coding knowledge. While generative AI fosters a positive creative addiction, public sentiment may turn more negative as economic impacts emerge—making it crucial to position AI as a pragmatic amplifier. Enterprise adoption will accelerate through AI-driven meeting documentation, strategy alignment, and task automation. Hoffman views early AGI not as human-like consciousness but as superior performance in specific domains via agent coordination, though alignment and interpretability remain challenges. He also points to AI in biology—such as his startup Manas AI—as an underrated frontier, where AI could simulate complex biological systems and drive scientific breakthroughs. Models like Anthropic’s Opus 4.5 exemplify progress through balanced design focused on usability and human collaboration, rather than raw scale.