This cheat sheet covers the top 20 AI agent bottlenecks and how enterprises solve them — where agents struggle today and the proven fixes, with business impact for each.
In simple terms
The 20 ways agents get stuck, and how enterprises solve each.
How it works
- 1State management → state graphs (LangGraph), checkpoints, durable execution.
- 2Memory limitations → hierarchical short/long-term memory and context management.
- 3Planning & reasoning → ReAct, Tree-of-Thoughts, Plan-and-Execute, self-reflection.
- 4Tool/API reliability → schema validation, circuit breakers, retries and caching.
- 5Hallucination, latency, cost, observability and security each get a targeted fix.
Key points
- Prioritise correctness & safety first, then reliability & observability, then performance & cost.
- Fixes span orchestration (graphs), memory, guardrails and monitoring.
- Measure task success, reliability, latency and cost.
- Enterprise success comes from architecture, tooling and guardrails, not just a bigger model.
Why it matters
Agents fail in specific, recurring ways. This cheat sheet maps each failure to a solution, helping teams build reliable, secure agents faster.
Frequently asked questions
- What should I fix first?
- Correctness and safety, then reliability and observability, then performance and cost.
- How do I fix state loss?
- Use stateful orchestration (LangGraph), checkpoints and durable execution.
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