What's the pain point you keep hearing from prospects that nobody else seems to be solving?
Some of the most defensible products come from a quiet observation — a pain point everyone is complaining about and nobody is fixing.
I am curious about what's on the community's list right now. The kind of thing where prospects keep describing the same problem, the existing tools all fall short, and the gap feels obvious from the inside but isn't yet on any 'top 10 AI startup ideas' list.
A few examples of pain points that are visible from enterprise discovery calls lately:
→ Evaluating AI agent output at scale (still mostly manual or LLM-as-judge)
→ Multi-agent debugging — when 4 agents collaborate, who failed?
→ AI agent observability that compliance teams actually trust
What's your version? What are you hearing repeatedly from prospects that feels like the next obvious thing to build?
Looking forward to some honest answers for this
Replies
Athena
As a CTO building in the AI era, this hits so close to home. Everyone is rushing to deploy agents, but nobody knows how to measure if those agents are actually driving durable product value post-launch, or just generating expensive token noise.
Observability for code execution is one thing, but observability for actual product value is the massive hidden gap right now.
@tal_elor I agree with your point.
This is the conversation nobody wants to have after launch. Teams celebrate shipping the agent, then three months later someone asks "what did this actually change?" and the room goes quiet.
We ran into this exact thing. The agent was working perfectly from a technical standpoint, zero errors, fast responses. But when we looked at whether it actually moved any business metric, the answer was... unclear. That's when we realized we'd been measuring uptime instead of outcomes.
The "expensive token noise" framing is painfully accurate. Curious what metrics you're using on your end to separate real value from activity that just looks productive?
For my case, we usually rely on conversion or satisfaction rate from the clients to judge that