What are the key bottlenecks for AI Agent development in the next 1–2 years?
I've been following the progress of AI Agent systems like Devin (by Cognition), AutoGen, and OpenAI's GPTs.
I’m curious: what do you think will be the key bottlenecks for AI Agents over the next 1–2 years? Will it be reasoning capabilities, long-term task planning, toolchain integration, or something else?
If someone were to build in this space today, which technical challenges or application areas would be the most worthwhile to tackle?
(For context: I’m an engineer exploring how to apply AI Agents to SaaS product development, with a particular interest in reasoning, multi-step tasks, and tool usage.)
Would love to hear your thoughts, and any resources you'd recommend digging into. Thanks!
I have literally referred to 100+ resources, guides, etc. some are too amateur, some are too vanilla for a coder like me. I want to learn just one thing -> build enterprise level agents, that can actually get shit done and add value not some workflow shit. can someone point me to the right direction
imo it will be the transmission speed between brain and computer
imagine how much more productive you would be, if you could get your thoughts (AND the relevant context) into the agents FAST
however, tbf, this is not a problem to be solved in the next 1-2 years