The Custom GPT Store is AWESOME! + ChatGPT Learns Over Time

TL;DR

OpenAI’s GPT Store is a marketplace for custom GPTs, accessible through ChatGPT Plus at launch, with Team and Enterprise customers also able to discover popular GPTs.

Briefing Cornell Notes

Briefing

OpenAI’s long-awaited GPT Store is now live inside ChatGPT Plus, turning custom GPTs into something closer to an app marketplace—and adding a path for builders to earn money. After two months of custom GPT creation, users have already produced more than 3 million custom versions, and the store is designed to help people find the most useful and popular ones in a single place. Access is currently gated behind ChatGPT Plus, with Team and Enterprise customers also able to find popular GPTs, while builders can publish only after verifying a Builder profile.

The store’s weekly rhythm mirrors the App Store: new featured GPTs appear regularly, and builders can set their GPTs to public after saving and completing verification (either enabling a name or linking a verified website). GPTs that violate policies can be removed. A key incentive for builders is the new revenue program planned for Q1: United States builders will be paid based on user engagement—how often people use their GPTs and how many chats they generate—though the exact payment criteria are still pending.

Beyond monetization, the store’s real differentiator is capability. Custom GPTs can combine instructions, extra knowledge, and tool access in ways that are harder to replicate with a generic chat. The transcript’s demonstrations highlight this with “Consensus,” a trending academic research GPT that can query academic papers and return science-based answers with citations. It also generates formatted citations on demand (including MLA), and it can pull relevant literature for complex scenarios like the trolley problem—complete with references and discussion grounded in academic sources.

The marketplace also emphasizes practical creativity and media generation. A “video GPT” uses a prompt-style workflow to generate a themed concept and then produces a video via API integration, while “Gilberry’s GPT” (“Gilberry Art Designer”) generates DALL·E images and also outputs Midjourney-ready commands. The transcript notes that this kind of multi-model prompting can be tedious in plain ChatGPT, but becomes packaged and repeatable inside a specialized GPT.

Other categories range from writing and SEO assistance to research, programming, and lifestyle. Search results can surface highly specific tools—tweet generators, hashtag builders, image captioning, and productivity utilities—suggesting the store is already functioning as a discovery layer for niche workflows.

Alongside the store launch, personalization is rolling out: GPTs can “learn from your chats,” carrying learned context forward between conversations and remembering preferences. Users can manage what’s stored, wipe memory, or turn the feature off, reflecting a tension between usefulness and privacy concerns.

Overall, the GPT Store positions custom GPTs as reusable, discoverable products rather than one-off experiments—while pairing that shift with a revenue model and a steady stream of curated and trending options. The remaining question is whether the marketplace will sustain beyond novelty, especially since access is currently limited to Plus subscribers and builders still want more features in the GPT creation tools.

Cornell Notes

OpenAI’s GPT Store launches as a marketplace for custom GPTs, accessible through ChatGPT Plus (with Team and Enterprise support for discovery). Builders can publish GPTs after saving and verifying a Builder profile, and GPTs can be removed for policy violations. A Q1 revenue program will pay U.S. builders based on user engagement (how often people chat with their GPTs), though payment criteria aren’t finalized yet. The store’s value is demonstrated through specialized GPTs that integrate tools and citations—such as an academic research GPT that returns referenced answers and generates MLA citations. A separate rollout adds personalization, letting GPTs learn from chats and remember preferences, with controls to manage or wipe memory.

What makes the GPT Store more than a simple directory of custom bots?

The store packages custom GPTs with specific instructions, extra knowledge, and tool access, turning them into reusable “apps.” In the transcript, “Consensus” isn’t just a chat prompt—it can query academic papers and return answers with citations, then generate MLA citations in a structured format. Similarly, “Gilberry’s GPT” produces both DALL·E images and Midjourney commands, reducing the effort needed to coordinate multiple image workflows manually.

How does monetization for GPT builders work, and what’s still unknown?

OpenAI plans a GPT Builder Revenue program in Q1. U.S. builders will be paid based on user engagement with their GPTs—metrics like how often users interact and how many chats occur. The transcript emphasizes that the payment system details and criteria are not fully defined yet, so builders know the direction but not the exact formula.

Why does access matter right now, and who can use the store?

The store is available only through ChatGPT Plus at launch, meaning it sits behind a pay wall. Team and Enterprise customers can also find popular GPTs. The transcript also notes a slow rollout over about 24 hours after announcement, with users advised to log out and back in if the store didn’t appear immediately.

What does “personalization” add, and how do users control it?

Personalization lets a GPT learn from chats so it can carry learned context between conversations and provide more relevant responses over time. It can remember preferences, and users can manage what it remembers, wipe memory, or turn the feature off. The transcript flags privacy discomfort as a reason some users may disable it.

What kinds of GPTs are trending, and what categories show up most?

The transcript highlights featured and trending GPTs, including partner-made picks and community creations. Categories include DALL·E, writing (including SEO-optimized tools), research and analysis, programming, and education/lifestyle. Search examples show how niche tools can be found quickly—like tweet-making, hashtag generation, and image captioning.

How do the demonstrations illustrate the difference between a specialized GPT and asking ChatGPT directly?

The transcript argues that generic ChatGPT can sometimes do “good enough” work, but specialized GPTs deliver more reliable, workflow-ready outputs. For example, the academic GPT can provide real citations and generate MLA formatting, while the image GPT can output both DALL·E results and Midjourney commands—tasks that would require more careful prompting and coordination outside the packaged GPT.

Review Questions

How does the GPT Store’s revenue program measure “engagement,” and what information is still missing for builders?
In what ways do specialized GPTs (like academic research or image generation) outperform generic prompting, based on the transcript’s examples?
What privacy and control mechanisms come with personalization, and why might different users choose different settings?

Key Points

1
OpenAI’s GPT Store is a marketplace for custom GPTs, accessible through ChatGPT Plus at launch, with Team and Enterprise customers also able to discover popular GPTs.
2
Builders must save their GPT and verify a Builder profile (name and/or a verified website) before publishing publicly.
3
The store uses a weekly cadence for featured GPTs and can remove GPTs that violate policies.
4
A Q1 revenue program will pay U.S. builders based on user engagement metrics, but the exact payment criteria are not yet published.
5
Personalization is rolling out so GPTs can learn from chats and carry context forward, with options to manage, wipe, or disable memory.
6
Specialized GPTs can integrate tools and workflows—such as academic citation generation or DALL·E plus Midjourney command output—making them more repeatable than ad-hoc prompting.
7
The store’s category and search experience is designed to surface niche, task-specific GPTs across research, writing, programming, and media creation.

Highlights

The GPT Store turns custom GPTs into discoverable, reusable “apps,” with weekly featured listings and public publishing gated by Builder profile verification.

“Consensus” demonstrates an academic workflow: querying papers, returning science-based answers with citations, and generating MLA citations on request.

“Gilberry’s GPT” bundles multi-model image generation by producing both DALL·E images and Midjourney-ready commands in one place.

Personalization lets GPTs learn from chats and remember preferences between conversations, but users can wipe memory or turn the feature off.

The Custom GPT Store is AWESOME! + ChatGPT Learns Over Time | Deep Dive