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I just got real feedback from my first active users, here’s what surprised me most

I’ve been building Leado, an AI agent that finds high-intent Reddit conversations for founders and indie hackers.

This week, 3–4 users sent me feedback after using it consistently, and a few things surprised me:

What I expected:
• users want more data
• more features = more value
• growth would come from adding more subreddits

What actually mattered:
• “Alerts must be relevant, not frequent.”
• “Stop giving me noise. Give me the 1 post that matters.”
• Better subreddit discovery > more subreddits
• Clean UX + setup = less churn
• People pay for signal, not quantity

These insights forced me to simplify a lot in Leado. Now the agent focuses on fewer, higher-precision triggers — and users immediately noticed the difference.

If you’re building an AI agent:
Relevance > volume.
Precision > features.

Happy to share more if anyone is building in the same space.

posted toAvatar for product Leado
Leado
  1. 1

    I’ve built a platform that helps businesses understand how visible they are in AI search engines like ChatGPT, Perplexity, and Claude. It shows a clear visibility score, tracks where and how a brand is mentioned, and compares performance against competitors. As AI becomes a primary discovery channel, this gives companies a way to measure and improve their presence where traditional SEO no longer applies.

  2. 1

    man focusing on customer feedback is so underrated... I guess part of it is because it is so often repeated by social media gurus...

    yet you took that to your advantage and now have a leverage..

    great share of your journey and looking forward to reading more

    best wishes

  3. 1

    Great post, Alex , the “signal over volume” insight is spot on.

    I do Reddit marketing for founders, and one thing I see a lot is that even when tools surface the right conversations, many makers still struggle to actually turn those threads into real visibility and engagement.

    That’s the part I handle , crafting natural posts, boosting the right conversations, and helping founders get more traction from Reddit without it feeling promotional.

    If you ever want to test a small Reddit push for Leado, I’d be happy to help amplify it

    Michael precious (@preshtechs

    olution)

  4. 1

    Real user feedback is invaluable—unexpected insights often reveal improvement areas and guide smarter product decisions.

  5. 1

    Insights often surprise and guide improvements more than expected assumptions.”

  6. 1

    Real user feedback is priceless—glad you’re learning early. Surprises like these help shape stronger products.

  7. 1

    Love this. It’s wild how often we assume users want “more,” when what they really want is less, but better. Especially in AI tooling — everyone’s drowning in notifications, dashboards, and data streams. Getting one alert that actually matters is 100x more valuable than 20 that don’t. The point about “signal over quantity” is dead on. Most founders don’t need endless inputs; they need confidence that what does surface is worth acting on. Your simplification mindset is exactly where agent tooling needs to go. Relevance isn’t just a feature — it’s the product.

  8. 1

    Receiving real feedback from first active users was eye-opening, revealing unexpected insights and valuable opportunities for improvement.

  9. 1

    Feedback from first active users provided surprising insights, highlighting areas for improvement and opportunities for growth.

  10. 1

    Receiving feedback from first active users revealed unexpected insights, highlighting areas for improvement and growth opportunities.

  11. 1

    Receiving feedback from first active users is eye-opening, revealing unexpected insights and opportunities for improvement.

  12. 1

    Interesting, thanks for sharing!

  13. 1

    i like this angle a lot. Curious how you filtered the feedback itself though — when multiple users are asking for different things, how do you distinguish between "this is a real gap" vs. "this is one person's preference"? Especially early on when sample sizes are small and every user feels like they matter equally.

  14. 1

    This is a fantastic insight, thanks for sharing. The "Relevance > volume" lesson is so crucial. It's easy to fall into the trap of thinking "more features = more value," but your user feedback proves the opposite.

  15. 1

    This is true actually, precision is much more needed than whatever features it has