Unverified50% confidenceOpinionExact time
One of the keys to ChatGPT's success is that SFT shifted the cost of prompt engineering from every user to a single training run, so that ordinary people do not need to write prompts themselves.
1
Sources
50%
Confidence
Long-term
Relevance
10/31/2026
First Seen
Sources
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Related Claims
UnverifiedSFT (supervised fine-tuning) using causal language modeling in the post-training stage takes the form of user tasks with chat templates applied, available tool sets, and tool response payloads from the environment.75% similarUnverifiedEnterprise ChatGPT typically promises not to use customer data to train models, offers single sign-on (SSO), role-based access control, usage analytics and audit logs, and supports organization-wide configuration of model versions and feature toggles.75% similarUnverifiedFree ChatGPT users' conversation content is used for model training by default, unless manually disabled in the settings.73% similarUnverifiedChatGPT's strength lies in task decomposition (explaining the plan clearly), but it lacks the tool calling and the execution-and-feedback layers, so it stops at the suggestion stage.72% similarUnverifiedChatGPT has higher accuracy in code completion, debugging suggestions, and algorithm explanation.71% similar
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