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Open AI’s New GPTs - How to Create & Share! thumbnail

Open AI’s New GPTs - How to Create & Share!

MattVidPro·
5 min read

Based on MattVidPro's video on YouTube. If you like this content, support the original creators by watching, liking and subscribing to their content.

TL;DR

GPT Builder lets creators define a custom assistant’s purpose and behavior using natural language, with real-time updates to the GPT configuration.

Briefing

OpenAI’s new GPTs feature is rolling out a way for non-developers to build customized versions of ChatGPT—then share them via links—using a guided “GPT Builder” workflow. The core value is practical: creators can define a GPT’s purpose in plain language, set its behavior and guardrails, and optionally attach tools like web browsing, image generation, file-based knowledge, and custom API actions. That combination turns a chat model into a more specialized assistant, from creative image generators to real-world decision helpers.

The walkthrough starts with the “Create a GPT” beta on the OpenAI site, where a left-side builder and right-side live preview update together. A simple example—“comic book image Creator”—shows how natural-language prompts can generate a name, starter suggestions, and even a profile picture using DALL·E 3. The builder then tailors behavior through an instruction set: the GPT is designed to produce comic-style visuals, guide users on character design, settings, and plot visualization, and keep outputs strictly within the comic/illustrative format. The creator also chooses how the assistant should handle ambiguity (ask for clarification vs. use judgment) and sets the communication style (casual and friendly).

A key part of the configuration is capabilities. The creator can upload files as “knowledge” so the GPT can reference specific documents or datasets for that custom use case. Capabilities can include web browsing, DALL·E image generation, and code interpreter (left enabled in the example). Most notably, the “actions” section allows a GPT to call external APIs—effectively enabling agent-like workflows such as retrieving data or triggering services—provided the creator sets up authentication (e.g., API keys). This is positioned as the path to “superpower” GPTs that do more than chat.

After testing in the playground, the GPT can be saved and published with different visibility settings: only the creator, anyone with a link, or public (with a note that public listing in the GPT store is expected in the coming weeks). Sharing is immediate via a copyable URL, and the GPT appears in the creator’s Explore sidebar so it can be edited, deleted, or opened for new chats.

The transcript also demonstrates a more functional GPT, “Auto advisor,” aimed at car buying. By uploading a screenshot of a car listing, the GPT breaks down the listing and uses web search to check pricing context and reliability—though it struggles when key variables like location aren’t provided. The creator highlights that entertainment and utility both benefit from the same customization pipeline.

Finally, community-made GPTs are tested from a “share gpts” area on the creator’s Discord: “grug’s wisdom” (caveman-style replies with web search), “deal Scout” (finding a Best Buy deal via web search), and “GPT Genesis” (a GPT idea generator). The overall takeaway is that the barrier to building and distributing specialized assistants is low enough that many users will experiment immediately, even before a formal GPT store launches.

Cornell Notes

OpenAI’s GPTs feature lets users create customized ChatGPT assistants through a guided GPT Builder interface, then share them via link or public listing. Creators define purpose and behavior in natural language, which can automatically generate names, starter prompts, and even profile images using DALL·E 3. The configuration supports “knowledge” uploads (files the GPT can reference), capabilities like web browsing and image generation, and “actions” that let GPTs call external APIs with authentication—enabling more agent-like workflows. Examples include a comic-book image generator and a car-buying “Auto advisor” that analyzes listings and uses web search, with limitations when location data is missing. Community GPTs such as grug’s wisdom and deal Scout demonstrate how quickly people are turning customization into niche tools.

How does the GPT Builder turn a simple idea into a working custom assistant?

The builder uses a two-pane workflow: a creation/configure area on the left and a live preview on the right. A creator types a plain-language goal (e.g., “make a bot that generates comic book images”), and the system responds by updating the GPT configuration in real time—suggesting a name, adding conversation starters, and generating a profile picture. The creator then refines “instructions” that define what the GPT should do (comic-style visuals, character and setting guidance) and what it must avoid (anything other than comic/illustrative images).

What does “capabilities” change for a custom GPT, and why does it matter?

Capabilities determine what tools the GPT can use for its specific job. In the example, capabilities include web browsing, DALL·E image generation, and code interpreter (left enabled). Web browsing lets the GPT search for up-to-date information; DALL·E enables image creation; code interpreter can support analysis or research tasks. Together, these tools expand the GPT from text-only assistance into a multi-modal, task-oriented assistant.

What is the practical role of “knowledge” uploads?

Knowledge uploads let a GPT reference specific files for that custom assistant. The transcript gives an example of uploading a large reference document (like a SpongeBob Wikipedia dump) so the GPT can answer in a consistent “SpongeBob” voice. For other GPTs, uploading PDFs or style references (e.g., comic drawing guidance) can help the assistant produce outputs aligned with the creator’s intended style.

Why are “actions” considered the biggest upgrade beyond chat?

Actions allow a GPT to call external APIs, turning it into an automated agent that can perform tasks rather than only generate text. The transcript notes that actions can be set up with authentication such as an API key, and that examples can be simple (like fetching weather) or more complex. This is framed as “mod support” for custom GPTs—letting creators connect their assistants to real services and workflows.

What limitation shows up in the car-buying “Auto advisor” example?

The GPT can analyze a car listing screenshot and use web search to estimate pricing context and reliability, but it struggles to extrapolate price accurately when crucial details are missing—specifically location. The transcript highlights that without location, web-based price comparisons can be unreliable, and the GPT may not fully compute a “reasonable price” conclusion.

How do community GPTs demonstrate the feature’s range?

Community examples show both playful and practical uses. “grug’s wisdom” delivers caveman-style answers and can search the web for weather and other facts. “deal Scout” finds a Best Buy deal via web search and compares it to other market options. “GPT Genesis” focuses on ideation—suggesting unique GPT concepts like a “culture exchange companion” for language and travel—showing that the customization pipeline supports both tools and meta-creators.

Review Questions

  1. What specific configuration elements (instructions, capabilities, knowledge, actions) most directly control a GPT’s behavior and usefulness?
  2. In the examples given, where does web browsing help—and where does it still fail without additional user-provided context?
  3. How does link-based sharing change the speed at which GPTs can be tested and iterated compared with waiting for a public store?

Key Points

  1. 1

    GPT Builder lets creators define a custom assistant’s purpose and behavior using natural language, with real-time updates to the GPT configuration.

  2. 2

    Custom GPTs can generate assets like profile pictures using DALL·E 3 as part of the creation flow.

  3. 3

    “Knowledge” uploads allow a GPT to reference specific files for consistent, use-case-specific answers and outputs.

  4. 4

    Capabilities such as web browsing and DALL·E expand GPTs beyond text into research and image generation.

  5. 5

    Actions enable GPTs to call external APIs with authentication, making automated, agent-like workflows possible.

  6. 6

    Publishing supports multiple visibility levels, including link-only sharing before the GPT store fully launches.

  7. 7

    Community-created GPTs demonstrate rapid experimentation across entertainment (grug’s wisdom) and utility (deal Scout, Auto advisor).

Highlights

The GPT Builder can generate a GPT’s name, conversation starters, and even a DALL·E 3 profile picture from a simple description.
Actions turn a custom GPT into something closer to an automated agent by letting it call external APIs with authentication.
The car-buying “Auto advisor” can analyze listings and search the web, but price judgments degrade when location isn’t provided.
Community GPTs range from caveman-style web-searching “grug’s wisdom” to deal-finding “deal Scout.”

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