Overview
This episode covers OpenAI's major updates to custom GPTs, demonstrating new model support, key features, business applications, and live examples of their practical use in automating knowledge work.
OpenAI Custom GPTs: What’s New
- OpenAI now allows custom GPTs to access all major models, including GPT-4o, 03, 04 Mini, and 4.5, not just GPT-40.
- Users and creators can set a recommended model to guide usage and optimize for specific tasks or industries.
- Building GPTs remains available only to paid users on the web; enterprise and EDU extended model support is rolling out soon.
- GPTs with custom actions are restricted to GPT-4o and 41 models for action execution.
- GPTs can be shared privately, published to a public store, or even monetized via private URLs.
Live Demonstrations: Custom GPT Use Cases
- Insight Synthesizer: Acts as a research analyst, synthesizing recent multi-source web data into a dashboard with sentiment analysis and thematic clusters.
- Data Storyteller: Converts uploaded spreadsheets into a 10-slide data narrative, highlighting trends and actionable insights via basic charts and bullet points.
- Meeting Actionizer: Processes meeting transcripts to extract decisions, action items, and performs automated follow-up research, streamlining post-meeting tasks.
- Investor Snapshot: Generates one-page, up-to-date financial and news reports for any public company in an easy-to-read format.
- Personalized Learning Architect: Designs custom learning plans (e.g., Python for data analysis), incorporating relevant resources and tailored analogies.
Advantages and Applications for Business
- Enhanced model selection enables customized GPTs to handle more complex, agentic workflows and nuanced tasks.
- Custom GPTs help automate repetitive knowledge work, saving time and reducing manual prompting.
- The new capabilities support internal automation, personalized data analysis, and decision support across teams.
- Sharing and upgrading GPTs is simplified via a model picker and the GPT store, fostering team collaboration.
Building and Configuring GPTs
- GPTs are created through a chat-based or configuration interface; technical expertise is not required.
- Instructions, knowledge files, and capabilities like web search, code execution, and custom actions can be toggled as needed.
- Performance may degrade when uploading large volumes of files; best results usually occur with fewer, targeted uploads.
Recommendations / Advice
- Evaluate common, repetitive knowledge work tasks within your business that could benefit from automation using custom GPTs.
- For advanced use (actions, API hooks, context management), consider deeper customization and continued learning through future segments or resources.
Questions / Follow-Ups
- Audience feedback is requested on running advanced segments covering actions, context stacking, and building for specific models.
- Suggestions are invited for future topics or use cases to address in upcoming episodes.