@kenanhsaleh: Proactive AI Agents Today’s AI products are reactive. You give the model a prompt, it responds with an answer. These ar…

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Summary

The article discusses the shift from reactive AI models to proactive AI agents that observe context and act autonomously, citing examples like OpenClaw and Poke while promoting the a16z Speedrun accelerator.

Proactive AI Agents Today’s AI products are reactive. You give the model a prompt, it responds with an answer. These are useful, but I’m excited about products that take this further and shift the paradigm from “ask → answer” to “observe → act." These agents will continuously monitor context in the background across all of your connected tools and data, predict what matters, and take action before being asked to do so – much like a human does. So instead of you prompting the model, the model will start prompting you. Examples here could include agents that remind you about tasks you forgot to complete, resolve customer issues before support tickets are filed, or debug and ship code fixes automatically. This shift represents a new paradigm where AI products behave more like humans and less like tools. We’re already starting to see this dynamic with products like OpenClaw, Poke, and more - and we’ve only scratched the surface of capabilities here. We’re accepting applications for the next cohort of @a16z @speedrun – If you’re building the next generation of AI products, apply online.
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