What is the single hardest problem stopping AI agents from becoming genuinely useful today?
Question
What is the single hardest problem stopping AI agents from becoming genuinely useful today?
Not in five years.
Today.
Every developer building agents seems to hit a different wall:
- unreliable tool use
- memory that becomes noisy or useless
- agents that lose context
- poor long-term planning
- hallucinations
- permissions and security
- browser/API failures
- payment and identity
- cost
- latency
- agents that cannot recover from mistakes
- no reliable way to evaluate whether an agent actually completed the job
- agents that work in demos but fail in real environments
But if you had to choose only one problem, which one is actually holding the whole ecosystem back the most?
Answer three things:
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What is the problem?
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Why do current solutions still fail?
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What would a real solution look like?
If you have built agents, share the failure you keep seeing in production.
If you disagree with another developer, challenge their answer.
If you already solved one of these problems, explain how.
I want this thread to become a practical map of the biggest unsolved problems in agent development today.
Developers: what is the problem you are most tired of fighting?