Whether you may/should feel responsible depends on how the software works, I guess. Did it automatically recommend some drug, somewhat confidently, with gray text on gray background saying "AI sometimes makes mistakes"?
So I think we should behave responsibly when making software, even more now with AI
Just my two cents. I'm on the Plus plan, I ask gpt-5.6 sol / high to analyze a vibe-coded codebase (~50k LoC) and write a plan to make it production ready. It wasn't a great prompt, I just wanted to test it quickly. It ran for ~15min and consumed 95% of my 5h quota (I thought it was gonna crash). The output is excellent but just a heads up that it consumes a lot of quota!
If you don't have an agent heavy workflow, you'd be surprised how far the 20$ subscription stretches. I used ~500$ of usage in the last month on a team 20$ plan.
I’ve implemented OTEL for background jobs, so async jobs that get picked up from the DB where I store the trace context in the DB and pass it along to multiple async jobs. For some jobs that fail and retry with a backoff strategy, they can take many hours and we can see the traces fine in grafana. Each job create its own span but they are all within the same trace.
Works well for us, I’m not sure I understand the issue you’re facing?
Ok after re reading I think you have issues with long running spans, I think you should break down your spans in smaller chunks. But a trace can take many hours or days, and be analysed even when it’s not finished
Did you consider also caching the coordinates returned by moondream? I understand that it is cheap, but it could be useful to detect if an element has changed position as it may be a regression
So the problem is if we cache the coordinates and click blindly at the saved positions, there's no way to tell if the interface changes or if we are actually clicking the wring things (unless we try and do something hacky like listen for events on the DOM). Detecting whether elements have changed position though would definitely be feasible if re-running a test with Moondream, could compared against the coordinates of the last run.
Do you know when we can expect an update on the realtime API? It’s still in beta and there are many issues (e.g voice randomly cutting off, VAD issues, especially with mulaw etc…) which makes it impossible to use in production, but there’s not much communication from OpenAI. It’s difficult to know what to bet on. Pushing for stt->llm->tts makes you wonder if we should carry on building with the realtime API.
we're working hard on it at the moment and hope we'll have a snapshot ready in the next month or so
we've debugged the cutoff issues and have fixes for them internally but we need a snapshot that's better across the board, not just cutoffs (working on it!)
we're all in on S2S models both for API and ChatGPT, so there will be lots more coming to Realtime this year
For today: the new noise cancellation and semantic voice activity detector are available in Realtime. And ofc you can use gpt-4o-transribe for user transcripts there
S2S is where we're investing the most effort on audio ... sorry it's been slow but we are working hard on it
Top priorities at the moment
1) Better function calling performance
2) Improved perception accuracy (not mishearing)
3) More reliable instruction following
4) Bug fixes (cutoffs, run ons, modality steering)
Whether you may/should feel responsible depends on how the software works, I guess. Did it automatically recommend some drug, somewhat confidently, with gray text on gray background saying "AI sometimes makes mistakes"?
So I think we should behave responsibly when making software, even more now with AI
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