What’s your single biggest struggle right now with AI?
I’m curious for anyone building products with AI in 2025. What’s your single biggest struggle right now?
Maybe it’s noisy architecture drift when using AI-assistants. Or pricing surprises due to compute costs. Or struggling to retain trust in AI output.
Drop your pain point and vote on how you're trying to handle it let’s learn from real‑world experience.
I am genuinely curious and would love to hear from you!
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The struggle to keep regenerating content for a unique output. I think sometimes AI gets too repetitive.
LLMs.txt Generator
@ricalgmn Totally feel this. Vanilla 'write me a blog post about X' prompts will almost always surface the same high‑probability phrases, because the model is literally trained to stay in that safe zone. A few things been done to shake the repetition:
Prompt remix. Add unusual constraints: "Open with an unexpected analogy, cite one paper published after 2024, and end with an action‑oriented checklist." When the model has to clear very specific hurdles, the output diverges fast.
Temperature & top‑p jitter. Generate three variants at T = 0.8 / 1.0 / 1.2 and let a quick similarity check pick the least‑redundant one. It’s basically A/B testing for creativity.
RAG for freshness. Feed it a bite‑size chunk of new source material each time (recent articles, internal docs, user interviews). The retrieval step forces the model to anchor on something it hasn't phrased before.
Similarity filter. We embed every draft and compare cosine distance to last month’s content; if it's > 0.85 we auto‑regenerate. Cheap, fast, and keeps Google happy.
Multi‑step drafting. Outline → hook writing → body paragraphs → copy edit. Breaking the task into stages forces the model (and you) to rethink structure instead of riffing on the same template.
Curious what you've tried so far is pure prompting, fine‑tuning, or any retrieval layer? And how do you define "unique" (SEO‑unique, brand-voice-unique, or literally never‑seen‑before)? Would love to swap notes.
@nicksuccesslaunch Thank you so much Nick, this is incredibly helpful! When I say "unique", I was referring to outputs that sound like the same recycled phrasing over and over, just like what you mentioned. Might just try your approach, especially prompt remix and RAG.
What is a pain point for me is less about how I use it, and how it's almost becoming a crutch. I open linkedin, posts are written using AI, I open instagram, captions are written using AI.. it's fine but also exhausting to see posts sounding like they're coming from the same place, same style, same emojis. I'm afraid more about the fact that humans are becoming hyper dependent on these systems, which in turn making us loose our creativity and our intelligence.
LLMs.txt Generator
@chaosandcoffee I think we notice it more because the algorithms keep pushing the same AI‑generated stuff across my feed. Last month if I watch any short content I try to scroll away if I see its AI-generated and it helped. It really did. I started seeing more genuine content. About creativity If you zoom out 10–20 years, most mainstream content was already templated, spun, or publisher‑approved to sell us something. Nothing’s really changed except the tools. Humans already lean on plenty of tech, but this wave could seriously reshape daily life over the next five years. Only what keep are humans is creativity and this can't be taken in my opinion
LLMs.txt Generator
@cristian_stoian_urzica that pain is real. I love when you forget to prompt not to change any existing parts and it just goes all over the place
Latency is killing our UX. Users hate waiting more than 2 seconds.
LLMs.txt Generator
@sultan_ansari1 Have you found any workarounds or trying to keep the customer attention?
YourGPT
Honestly, the biggest struggle for us is managing the cost while keeping the output consistent. Its amazing, but once you start scaling or adding custom logic, things can get expensive fast. Also, making sure users trust the AI’s response and don’t get weird or off-brand results is an ongoing challenge. We are trying a mix of prompt engineering, lightweight fine-tuning, and smarter fallback logic, but it’s definitely a work in progress.
LLMs.txt Generator
@neha_8 Totally feel the pain of those runaway compute bills. Have you found any quick wins with a tiered-model setup or caching layer, or is prompt-tuning still your main lever for keeping quality and cost in balance?