My AI model started giving nonsense answers during a client demo

I was presenting a new text analysis tool to a marketing firm in Chicago last Tuesday. The model suddenly started outputting random strings of characters instead of sentiment scores. I had to quickly switch to a backup API endpoint I had set up, which saved the meeting. Has anyone else had a live demo go sideways and have a good recovery plan?

3 comments

3 Comments

patricia_rodriguez6d ago

Last March I had a model start outputting raw JSON during a live demo for a logistics company in Dallas, right in front of three VPs. The backup API I had was basically a stripped down version with pre-calculated results, not even a full parallel system. It worked fine because I tested that fallback path separately every single week, including running it through the same demo script. What saved me was keeping a simple local HTML mockup on my laptop that could display sample outputs without hitting any API at all. I just switched screens, said "let me show you the offline version real quick", and the demo kept rolling. The key is having multiple layers of backup that you actually practice with, not just one spare API you assume will always work.

james_ross2mo ago

Honestly, calling that a "good recovery plan" feels off to me. Having a backup API is just basic prep, not some genius save. Tbh if your model spits out random junk in a demo, the real problem is your testing was weak. You got lucky the backup worked, but that doesn't fix why the main one failed so badly.

harper2542mo ago

Chicago's a tough market for demos, I've had my share of glitches there. Having a backup ready isn't just basic prep, it's the smart move that shows you planned for real world problems. Testing can't catch every weird edge case once you're live. The fact you had a working fallback is what clients remember, not the initial hiccup.