How AI Agents Scale (and Fail)
1. How AI Agents Scale (and Fail)
AI agents are powerful, but they can be fragile. In this video, we'll explore common failure modes and their solutions when scaling AI agents.2. The confident start
You've just built an AI travel assistant. In development, it's brilliant-3. The confident start
it finds cheap flights,4. The confident start
checks visa rules,5. The confident start
and suggests destinations based on the weather. It feels intelligent, even delightful. Your team's excited!6. The confident start
Then you launch.7. The confident start
At first, it's exciting users from all over the world start using it. But soon, issues appear.8. Trouble at scale
Complaints surface. Some users are confused. Others get incorrect information and complain about how slow it is to respond. Behind-the-scenes, costs are also soaring far beyond what was originally anticipated. So what's happening?9. Failure mode #1 - Fragile evaluation
You begin to dig into the user data, and find that the breadth and variety of user inputs is greater than expected. Users are writing in fragments, using slang, other languages, and emojis. You also find that the agent is making hidden assumptions like a user's country, currency, or calendar, which is upsetting the international user base. So how do we fix this?10. Failure mode #1 - Fragile evaluation
It starts with evaluation. Ditch the ideal test cases.11. Failure mode #1 - Fragile evaluation
Use real queries-messy, diverse, and multilingual. Include slang, partial sentences, and typos. If that's what your users send, that's what your agent should be ready for. Simulate global user interactions to catch hidden assumptions: different time zones, cultural events, currencies, even accessibility needs.12. Failure mode #2 - Intent drift
People are also starting to ask for things the agent wasn't designed for-like airport lounges, restaurant bookings, or rail tickets. If it tries to answer anyway, the risk of a bad user experience skyrockets. To counter this,13. Failure mode #2 - Intent drift
set boundaries, also called guardrails, that restrict the agent's scope of operation. An agent shouldn't pretend it knows everything. If it's out of scope, it should say so politely and clearly. Users trust honesty over nonsense.14. Failure mode #3 - Undesirable feedback loops
To adapt to user feedback, your team implemented a user rating system that is used to optimize the agent's outputs. However, you're seeing users upvoting more frequently when the agent makes jokes, which is causing it to prioritize charm over truth. Not ideal when trying to give travel advice. Design your feedback loops carefully. Don't optimize for 'likes' alone. Blend human review with clearly-defined metrics, such as truthfulness, clarity, tone. That way, charm won't beat correctness.15. Failure mode #4 - Latency bottlenecks
Now let's talk performance. As usage increases, latency becomes a real issue. Multi-step reasoning,16. Failure mode #4 - Latency bottlenecks
tool use,17. Failure mode #4 - Latency bottlenecks
retrieval-all of it can contribute to delays. What seemed smart in testing now feels slow in production. To reduce latency, think architecturally.18. Failure mode #4 - Latency bottlenecks
Cache common queries.19. Failure mode #4 - Latency bottlenecks
Use lighter models for simple tasks.20. Failure mode #4 - Latency bottlenecks
Trigger heavier reasoning only when needed.21. Failure mode #5 - Cost explosion
These same issues can also cause costs spiral out of control. You might be using long prompts, multiple tools, advanced reasoning models, and external APIs for retrieval. All of that adds up fast-especially when multiplied by thousands of users. First, use cost-aware design during development. Ask early: Could this function be cached? Can we answer this with a smaller model? Do we need this retrieval step every time? Most of the cost-cutting opportunities show up in architecture design rather than optimization.22. Failure mode #5 - Cost explosion
Adding fair usage limits to costly features will also help you showcase your agent while mitigating some of the risk of a cost explosion.23. Let's practice!
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