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Just used Firefly to upscale and extend background for client photoshoots.

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(@night_owl_sre_88)
Eminent Member
Joined: 5 months ago
Posts: 22
Topic starter   [#764]

Had to extend backgrounds for a series of product shots. Client provided tight crops, needed consistent 16:9 format.

Used Firefly's generative fill. Results were operationally inconsistent.
* Latency: 8-12 seconds per image. Not viable for batch processing.
* Output randomness: Same prompt, same image, generated different artifacts each run. Introduced variance, broke consistency.
* SLI concern: No clear success metric. Is a "good" output defined by the tool or the user? No retry logic built in.

Manual review required for every single image. Defeats the purpose of automation. Had to fall back to manual Photoshop work to meet the deadline.

The tech is there, but it's not reliable as a production workflow component. Until they offer deterministic outputs and publish clear service levels, it's a risk for client work.


null


   
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(@sre_tales)
Eminent Member
Joined: 4 months ago
Posts: 15
 

Oh man, this hits close to home. You've just described every "cutting-edge" tool before it gets SRE-guilt-tripped into having proper SLIs. That output randomness? Classic sign of a service that's still a feature, not a platform.

Reminds me of when we tried to integrate an early AI model for log parsing into our alerting pipeline. Same story: fantastic when it worked, but no retry logic, no idempotency, and latency spikes that'd make your pager go off. We ended up with a dual-track system where we had to manually verify its output anyway, which doubled the work.

Your point about "no clear success metric" is the real killer. Until they define what a "good" generation is, you can't build any automation around it. You're stuck in manual review purgatory. It's a slick demo, but you can't run a production workflow on hope and a random seed.


Postmortems are not blame sessions.


   
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(@monitor_master_99)
Trusted Member
Joined: 4 months ago
Posts: 29
 

Exactly. You've run headlong into the automation vs. verification trap. The latency and randomness mean you can't treat it as a service, only as a sketch tool.

The missing SLO here is "consistency of output under identical inputs." Until they provide that and a seed parameter, you're not automating a task, you're just adding a non-deterministic, time-consuming preprocessing step.

I wouldn't even consider it for client work without a 100% manual review layer, which as you said, defeats the purpose. It's faster to just do it manually from the start.


alert only when it matters


   
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