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In focus
- The startup proving AI agents don’t always have to revolve around LLMs
- A look back at how call center workers in the Philippines are bracing for the AI revolution
- Manus distances itself from China roots
Hello reader,
We’re halfway through 2025, and AI has moved beyond just helping us write emails. It’s now starting to handle more complex tasks on our behalf. Of course, I’m talking about AI agents, where most of the attention (and money) seems to be going.
Over the past two years, the conversation has shifted from marveling at how well AI can generate content to asking how much of our workload we can offload to AI agents.
This has a lot to do with the development of large language models (LLMs), which keep getting bigger as well as better at understanding context. But one startup believes LLMs can only go so far, and that the real key to building smarter AI agents lies elsewhere.
That startup is Pokee AI, and it just validated its contrarian bet by raising US$12 million in seed funding from top-tier US investors.
In today’s Big Story, I look into how Pokee is rethinking the AI agent stack – not by stuffing in bigger LLMs, but by combining them with models trained through reinforcement learning (RL).
RL isn’t a new technique, and as one researcher pointed out, it’s notoriously hard to get right. But that didn’t stop Pokee from replacing LLMs’ central role in planning and executing tasks by putting RL in charge.
In the race to build better AI agents, maybe it’s time more companies looked beyond the obvious and consider what’s been overlooked.
The field is moving fast. Because let’s be honest, if these AI agents don’t start working effectively soon, we humans might actually have to do things ourselves.
Glenn Kaonang, journalist
The Big Story
LLMs are central to Manus. Not so for this new AI agent
Pokee AI founder Zheqing (Bill) Zhu / Image credit: Timmy Loen
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