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On April 15, 2026 in San Francisco, Ride AI 2026 brings together AV pioneers, regulators, and AI experts to tackle the final frontier: marketing autonomous vehicles into mainstream adoption. Discover how real-world robotaxi scale, safety data, and LLM breakthroughs can bridge the trust gap and drive the next mobility revolution.

Reflecting on three years of AI adoption, this talk emphasizes that transformative technologies like transformers are still in their infancy, requiring hands-on exploration and healthy skepticism toward confident predictions. It argues that AI acts more as a mirror—revealing our own organizational patterns and biases—than a crystal ball for the future.

Claude Code combines a terminal-based Unix command interface with filesystem access to give LLMs persistent memory and seamless tool chaining, transforming it into a powerful agentic operating system for coding and note-taking. Its simple, composable approach offers a blueprint for reliable AI agents that leverage the Unix philosophy rather than complex multi-agent architectures.

Rather than wrestling with bureaucratic checklists and hand-crafted rules, organizations should define the desired outcome and let AI’s computational scale absorb complexity. By prioritizing metrics over process, builders over operators, and rapid data-driven cycles, companies can clean the “garbage can” of waste without endlessly labeling each piece of trash.

Noah distills his 2,400+ hours of AI use into a candid, unordered list of 29 controversial takeaways—from championing ChatGPT’s advanced models and token maximalism to predicting enterprise adoption bottlenecks—and invites fellow practitioners to discuss. CMOs can reach out to Alephic for expert guidance on integrating AI into their marketing organizations.

Just as Eisenhower warned of a powerful military-industrial alliance and Conway observed that systems mirror their creators’ communication structures, today’s sprawling SaaS ecosystem quietly imposes vendor-defined processes on every company. By harnessing AI and proprietary “private tokens,” enterprises can escape this one-size-fits-all mold and build software that truly reflects their unique DNA and strategic edge.