That prompt you shared at the end is actual gold. I've spent decades playing devil's advocate on every pitch that crossed my desk, and most retail investors never do it once. They read a bullish article, get excited, and buy. The institutions pay six-figure salaries for people to tear apart theses - you just gave everyone that capability for free.
Just remember that GPT pulling bond pricing data on distressed debt is cool until it isn't. I've seen plenty of "cutting-edge models" blow up because they couldn't smell what the data couldn't show. The 2008 models all said everything was fine too, right up until it wasn't.
The real edge isn't having GPT 5.2. It's knowing when to trust it and when to trust your gut.
Your comment is gold! You're right. Nothing is bulletproof. But it feels like investors have been given a gift by combining bearish prompts and GPT. In the past, we had to do our own pre-mortems, but it's not easy with all the bias you have after analyzing a company. Now, you get a sort of an independent analyst to kill our idea.
Brilliant breakdown on the cost efficiency jump with GPT5.2. That 390x improvement in cost per task while maintaining accuracy is the kinda shift that changes how we actaully deploy these models in production workflows. I've been experimenting with using older models for quick thesis validation but the bond pricing insight GPT5.2 surfaced automatically feels like it's crossing into genuinly useful territory for distressed situatons. Curious if the reasoning gains translate to spotting accounting red flags better tahn 5.1.
I haven't had the time to compare both models yet. But it's a great idea. OpenAI claims it should be better at these things. I'll see if I can write a post about it in the future.
That prompt you shared at the end is actual gold. I've spent decades playing devil's advocate on every pitch that crossed my desk, and most retail investors never do it once. They read a bullish article, get excited, and buy. The institutions pay six-figure salaries for people to tear apart theses - you just gave everyone that capability for free.
Just remember that GPT pulling bond pricing data on distressed debt is cool until it isn't. I've seen plenty of "cutting-edge models" blow up because they couldn't smell what the data couldn't show. The 2008 models all said everything was fine too, right up until it wasn't.
The real edge isn't having GPT 5.2. It's knowing when to trust it and when to trust your gut.
Your comment is gold! You're right. Nothing is bulletproof. But it feels like investors have been given a gift by combining bearish prompts and GPT. In the past, we had to do our own pre-mortems, but it's not easy with all the bias you have after analyzing a company. Now, you get a sort of an independent analyst to kill our idea.
Brilliant breakdown on the cost efficiency jump with GPT5.2. That 390x improvement in cost per task while maintaining accuracy is the kinda shift that changes how we actaully deploy these models in production workflows. I've been experimenting with using older models for quick thesis validation but the bond pricing insight GPT5.2 surfaced automatically feels like it's crossing into genuinly useful territory for distressed situatons. Curious if the reasoning gains translate to spotting accounting red flags better tahn 5.1.
I haven't had the time to compare both models yet. But it's a great idea. OpenAI claims it should be better at these things. I'll see if I can write a post about it in the future.