kajolshah_bt

5 ms·

1.
Tell HN: Warning: Third-Party Services Can Cost Mobile Apps Too Much
1 points by kajolshah_bt 7mo ago|0 comments
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by kajolshah_bt 7mo ago
I wrote this myself (Director at Budventure). I keep getting asked: How much does a React Native app cost in the US? I wrote down the common price ranges and the reasons that usually change the costs. I also added a one-page PDF checklist
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React Native App Development Cost in the US (2026) + a One-Page Budget Checklist(budventure.technology)
2 points by kajolshah_bt 7mo ago|1 comments
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by kajolshah_bt 8mo ago
I think a lot of people push back on calling LLMs AI because the word means different things to different people. For many engineers, AI used to mean systems that can reason, adapt, and make judgments over time. LLMs don’t really do that. T
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by kajolshah_bt 8mo ago
The spending numbers are wild. More than the moon landing and we’re mostly using it to autocomplete emails and generate slide decks. That doesn’t mean it’s useless. It just means the infrastructure is way ahead of the everyday experience. W
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by kajolshah_bt 8mo ago
I think you’re onto something. Every time we blame the model, I wonder how much of it is just the system we dropped it into. If you put anything, human or model, inside a loop that rewards fast feedback, visibility, and ranking, you’re goin
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by kajolshah_bt 8mo ago
I don’t think you’re missing anything. The hype cycle is real. But I also don’t think the signal is zero. It’s just buried under capital and compute flexing. The pattern I see isn’t AI is revolutionary. It’s: 1) The easy wins are done. 2) T
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by kajolshah_bt 8mo ago
I see this split clearly in real products: some users treat AI like a tool to support their workflow, others treat it like a replacement for thinking. The first group uses AI to reduce repetitive work and interprets results critically; the
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by kajolshah_bt 8mo ago
I don’t think AI is killing B2B SaaS. It’s exposing what was already broken. A lot of legacy SaaS shipped features that never solved real customer problems; AI just makes that obvious because users now expect intelligence and responsiveness
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by kajolshah_bt 8mo ago
That description matches a lot of what we’ve seen in real products. AI does make some parts of development and workflows easier like summarizing data, generating initial drafts, or auto-completing repetitive patterns. Those wins are real. T
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by kajolshah_bt 8mo ago
I’ve gone through a similar journey, not in big tech, but in practical business work. We started with quick experiments: generative prompts in internal tooling, a couple of proof-of-concept bots, and integration of recommendations in mobile
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by kajolshah_bt 8mo ago
Thanks for sharing your thoughts! I totally get where you’re coming from on notifications. It’s like apps that bombard you with prompts or notifications right away are almost disrespecting your time and focus. It really is about having apps
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by kajolshah_bt 8mo ago
This matches my experience pretty closely. A lot of teams treat notifications as a default feature instead of something that has to earn its place. From the builder's side, it’s often framed as keeping users engaged, but from the user&
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by kajolshah_bt 8mo ago
This is a really helpful way to separate the two. I think a lot of product discussions collapse engagement into notifications, when in reality many useful tools are pull-based by nature. I personally have apps I use weekly that would be wor
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by kajolshah_bt 8mo ago
This is really helpful. That matches what I’ve seen too, but you’ve explained it more clearly than most product docs ever do. The part that stands out to me is how default notification prompts feel like an insult to intelligence rather than
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Ask HN: Why do users mute apps instead of deleting them?
3 points by kajolshah_bt 8mo ago|8 comments
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Ask HN: What AI features looked smart early but hurt retention later?
1 points by kajolshah_bt 8mo ago|0 comments
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by kajolshah_bt 8mo ago
Yes, exactly. A lot of demos just don’t fail in the real world. They were never designed for real usage in the first place. They work once, in a clean flow, and fall apart as soon as people behave… like people.
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by kajolshah_bt 9mo ago
This is such a classic failure mode: even a 15–20% confident misroute is brutal because it forces “review everything,” kills trust, and increases repeats/reopens. When you rolled back, did you keep AI as suggestions only + rules-based
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by kajolshah_bt 9mo ago
Totally agree — the “demo vs real world” gap is always the messy edge cases: accents, crosstalk, domain terms, and people talking like… people. Did you end up adding any guardrails (confidence thresholds, “please repeat,” glossary/term
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Ask HN: What AI feature looked in demos and failed in real usage? Why?
8 points by kajolshah_bt 9mo ago|4 comments
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Ask HN: What 'AI feature' created negative ROI in production?
5 points by kajolshah_bt 9mo ago|4 comments
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by kajolshah_bt 9mo ago
Strongly agree. In my experience, asking “what concrete action changes if this works?” filters out most premature AI ideas. If no one can point to a changed decision, AI just adds cost and complexity without leverage. When the answer is vag
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by kajolshah_bt 9mo ago
I’ve seen AI help only after teams agree on workflows, data definitions, and success metrics. When those aren’t clear, AI often makes the confusion harder to notice. Curious if others have seen the same pattern.
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Ask HN: At what point does adding AI slow a product down?
1 points by kajolshah_bt 9mo ago|1 comments
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by kajolshah_bt 9mo ago
I’ve seen AI help with COBOL only after the system is well understood. When specs are fuzzy or tribal knowledge isn’t written down, AI just produces confident but risky code. It speeds things up only once the basics are already clear.
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Most Companies Don't Fail at AI – They Fail Before It Even Starts
2 points by kajolshah_bt 9mo ago|2 comments