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In focus
- Burning more AI tokens isn’t something to be proud of
- Vietnamese startup bags fresh funding for its SME-focused AI financial software
- SkyeChip’s IPO levels up Malaysia’s semiconductor powerhouse status
Hello reader,
A lot of people in my social circle have been bragging lately about being gym rats. Good for them. But it’s also sparked a pretty pointless competition of who spends the most hours at the gym.
Never mind that half the time in a crowded gym is spent waiting around for the squat rack instead of actually training harder.
A similar pattern is emerging in AI. It’s called tokenmaxxing – burning through as many tokens as possible each day across prompts, agents, and automated workflows. Maxing out Claude’s most expensive plan has somehow become its own form of tech bro street cred.
But like the gym analogy, high usage doesn’t necessarily mean high output. Sometimes it just means you’re spending more time inside the system.
Today’s insights piece explains why this is the wrong thing to optimize for. Token burn – like hours logged at the gym – tells you effort was exerted, but it doesn’t immediately tell you anything got better.
The metrics that actually matter include how much time AI can save on specific workflows, whether AI outputs survive without heavy rework, and where the recovered time goes. The last one is where most teams go silent.
The question we should be asking is not “are we using AI?” but rather “are we any better because of it?”
Also in this issue: Vietnamese B2B SaaS startup SoBanHang has raised new funding to build an AI-native financial operating system for SMEs. It’s eyeing regional expansion as early as next year.
Glenn Kaonang, journalist
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1️⃣ Tokenmaxxing is not a productivity strategy
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