Aquibur Rahman (@AR_Bits) header
Aquibur Rahman (@AR_Bits) profile picture

CEO @ Mailmodo (YC S21). Building, breaking, learning & telling. Marketing isn't demand generation. It is Trustmaxxing.

San Francisco, CA
Joined September 2014
Photo by Aquibur Rahman (@AR_Bits)Photo by Aquibur Rahman (@AR_Bits)Photo by Aquibur Rahman (@AR_Bits)Photo by Aquibur Rahman (@AR_Bits)Photo by Aquibur Rahman (@AR_Bits)Photo by Aquibur Rahman (@AR_Bits)Photo by Aquibur Rahman (@AR_Bits)Photo by Aquibur Rahman (@AR_Bits)Photo by Aquibur Rahman (@AR_Bits)
Big day at @mailmodo! We just launched Mailmodo AI: the Lovable for email marketing. Emails that took 4–5 days to plan, design & send? Now happens in minutes. All you need is a prompt. Mailmodo AI does the rest. And we are live on Product Hunt 👇
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PhonePe is sitting on India's biggest AI opportunity and isn't using it yet: a personal AI agent like @muse and Instinct, but for India. It could be the strongest part of their IPO story. Here's why:
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Open @PhonePe: icons fighting for a tap. Anything beyond a UPI payment is hard work. Insurance, gold, mutual funds, bills: all there, mostly buried. Not built for most users like our parents. An agent fixes that. Just say what you need, and every @PhonePe product gets used.
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If I were @PhonePe, I'd ship this before the IPO. Wait too long and ChatGPT or Muse trains Indians on a habit that's hard to win back.
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By 2027, an increasing number of enterprises will finetune open-weights models for their own usecase reducing dependency on LLMs. Large companies will become larger. Small companies will pay the fee for being small.
We were able to fine tune an open weight model (Qwen3.5-9B) on proprietary internal data at @coinbase, and it out performed frontier models, at much lower cost and speed, for a specialized task (fraud prevention in this case). I think we'll see more of this pattern inside companies. The frontier models are amazing generalists. But increasingly you'll see specialist models out perform on more narrow tasks, either working on teams, or by themselves. We're making it easy to fine tune models internally for our employees. We even have a skill for it in our internal harness that makes it easy to spin these up and start training them: "/fine-tune-and-serve-llm I want to fine-tune Qwen for payments risk review. help me get started" I imagine we'll have some backend services that could be replaced entirely by this new architecture.
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In 2027, B2C brands could face a brutal combination: - higher acquisition costs - lower margins - weaker retention And ironically, they may end up paying more to @Meta. Here's why ↓
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And someday Meta could have the perfect product to sell you: Access to that customer again. More ads. More marketing budget. Agents will send stores plenty of orders while charging them again every time their own customer comes back into the funnel.
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For every B2C founder, the question is: How are you thinking about this change in your user funnel?
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