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AI expert urges composable, iterative design for future-proofing systems

Omar Sanseviero advocates for building composable AI systems to ensure future adaptability. He emphasizes that core components like LLMs, evaluation tools, automations, and agent frameworks should all be designed for iterative development and customization. This approach, he argues, leads to significant compounding effects in AI development. AI

IMPACT Advocates for a design philosophy that could improve the longevity and adaptability of AI systems.

RANK_REASON The cluster contains an opinion piece from an individual on AI development strategy.

Read on X — Omar Sanseviero (HF research) →

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  1. X — Omar Sanseviero (HF research) TIER_1 English(EN) · omarsar0 ·

    For future-proof, build AI that's composable.

    For future-proof, build AI that's composable. Regardless of what you use, all these should be composable, iterative, and customizable: - LLMs - Evals - Automations - MCP/CLI tools - Skills/Memory/Context - Agent Harness (Codex, CC, Pi,...) The compounding effects are insane.