[D] AI Agents: too early, too expensive, too unreliable

[**Reference: Full blog post**](https://www.kadoa.com/blog/ai-agents-hype-vs-reality)

There has been a lot of hype about the promise of autonomous agent-based LLM workflows. By now, all major LLMs are capable of interacting with external tools and functions, letting the LLM perform sequences of tasks automatically.

But reality is proving more challenging than anticipated.

The [WebArena leaderboard](https://docs.google.com/spreadsheets/d/1M801lEpBbKSNwP-vDBkC_pF7LdyGU1f_ufZb_NWNBZQ/edit#gid=0), which benchmarks LLMs agents against real-world tasks, shows that even the best-performing models have a success rate of only 35.8%.

# Challenges in Practice

After seeing many attempts …

agent agents ai agents autonomous challenges functions hype llm llms machinelearning major practice reality tasks tools workflows