Hi John, thanks for the testing of GPT5!! As a novice in AI marketing, I wonder what workflows you build, where you use more than 24k words as input. Possible to give an example of a real world task where you would break this limitation? Btw, thanks a lot for your content, I'm learning much from it (no emoji here)
Hey, always happy to share! The things that really break this limitation are mostly from a data synthesis POV, where you’re trying to distill insights from large amounts of unstructured data.
Here are a few actual marketing examples of mine that broke the context window limitation:
1. Customer VOC mining – Collected voice-of-customer data in my niche/industry from Twitter, Reddit, blogs, YouTube comments, etc., and fed the combined data into ChatGPT to distill the common pains, desires, and transformations our customers experienced.
2. YouTube transcript analysis – Pulled all of Alex Hormozi’s YouTube video transcripts into ChatGPT to extract recurring themes. This quickly hit the context window limit.
3. Support log review – Uploaded years’ worth of customer support logs to identify recurring questions we could address via a chatbot or FAQs.
4. Long-form sales copy – Crafting large sales pages in a single session. As the context window fills, ChatGPT slows down noticeably and starts to forget earlier instructions.
Hi John, thanks for the testing of GPT5!! As a novice in AI marketing, I wonder what workflows you build, where you use more than 24k words as input. Possible to give an example of a real world task where you would break this limitation? Btw, thanks a lot for your content, I'm learning much from it (no emoji here)
Hey, always happy to share! The things that really break this limitation are mostly from a data synthesis POV, where you’re trying to distill insights from large amounts of unstructured data.
Here are a few actual marketing examples of mine that broke the context window limitation:
1. Customer VOC mining – Collected voice-of-customer data in my niche/industry from Twitter, Reddit, blogs, YouTube comments, etc., and fed the combined data into ChatGPT to distill the common pains, desires, and transformations our customers experienced.
2. YouTube transcript analysis – Pulled all of Alex Hormozi’s YouTube video transcripts into ChatGPT to extract recurring themes. This quickly hit the context window limit.
3. Support log review – Uploaded years’ worth of customer support logs to identify recurring questions we could address via a chatbot or FAQs.
4. Long-form sales copy – Crafting large sales pages in a single session. As the context window fills, ChatGPT slows down noticeably and starts to forget earlier instructions.