How to Use ChatGPT Projects for Ongoing Work

TL;DR

ChatGPT Projects organize related chats, files, instructions, and memory around an ongoing task, making them more suitable for evolving work than a single regular chat or repeatable custom GPT. Start by defining project-specific instructions, then add a small, carefully edited knowledge base and use focused prompts to analyze information, create plans, and build on earlier conversations.

Transcript

Chat GPT projects are one of the best features inside of Chat GPT and one of the most underrated features inside of Chat GPT and they recently became available to all users. So in this deep dive video, I'm going to show you step by step first what projects are and how they work, why they're different from regular chats inside of Chat GPT, and how y... Read More

Key Insights

• ChatGPT Projects are workspaces that keep related chats, files, instructions, and memory together for a specific ongoing task. They are designed to grow as users add conversations, knowledge, and refinements over time.
• Projects differ from custom GPTs because custom GPTs are intended for a specific repeatable task, while projects function as living workspaces. A project can accumulate a long history around a topic such as investing or managing a YouTube channel.
• Project-only memory makes a workspace self-contained by allowing it to access its own memories while hiding those memories from outside chats. This setting helps prevent unrelated information from regular ChatGPT memory from entering the project's work.
• Project instructions can define the goal, output format, tone, and response behavior for every conversation in that workspace. The example also tells ChatGPT to request more information whenever the user's initial prompt is unclear.
• Uploaded project files form a reusable knowledge base that can include documents, PDFs, code files, images, analytics, transcripts, scripts, and research reports. Users do not need a knowledge base when their primary goal is simply keeping memory self-contained.
• Knowledge quality is more important than file quantity because a focused, edited source can guide the project more clearly than a large collection of unreviewed material. The presenter recommends trimming deep-research reports before adding them to a project's files.
• Projects retain access to uploaded knowledge across later conversations, so users can analyze a document once and continue building on the findings. In the channel example, analytics remain available for later theme analysis and content planning.
• Prompt specificity strongly affects output quality because vague requests produce vague results. The demonstrated approach specifies a role, objective, scenario, expected solution, desired outcome, tone, audience, benefits, and format when those details are relevant.

Questions & Answers

Q: What are ChatGPT Projects used for?

ChatGPT Projects are used to organize ongoing work around a specific task or topic. They keep related chats, uploaded files, project instructions, and memory in one workspace. Users can continually add information and return to the same project, allowing later conversations to build on previous analysis instead of repeatedly uploading the same materials or recreating the context.

Q: How are ChatGPT Projects different from custom GPTs?

ChatGPT Projects are described as living workspaces that develop as users add conversations, files, instructions, and knowledge over time. Custom GPTs are intended for one specific repeatable task. A project is therefore better suited to an evolving body of work, such as ongoing investing research or managing a YouTube channel with a growing history of decisions and analysis.

Q: How does project-only memory work in ChatGPT Projects?

Project-only memory allows a project to access its own memories while keeping those memories hidden from outside chats. The project becomes self-contained and does not draw on potentially irrelevant information stored in regular ChatGPT memory. The presenter prefers this setting because it separates the project's context from unrelated conversations and helps maintain focus on the selected task.

Q: What should ChatGPT Project instructions include?

Project instructions should include a clear goal, the desired response format, an appropriate tone, and guidance for handling unclear requests. In the demonstrated setup, the goal is planning four upcoming video uploads, responses must stay under five bullet points, the tone should remain casual, and ChatGPT should ask for more information when the initial prompt lacks necessary detail.

Q: What files can be added to a ChatGPT Project?

A ChatGPT Project can use documents, PDFs, code files, images, analytics, video transcripts, scripts, thumbnails, and research reports as knowledge sources. These files become a reusable knowledge base that the project can consult during later conversations. The YouTube example combines channel analytics, thumbnails, a transcription or script, and an edited deep-research report about effective YouTube videos.

Q: How many files should be added to a ChatGPT Project?

The presentation states that the free plan is limited to five project files, while paid plans allow from 20 to 40 files depending on the plan. The presenter advises against filling a project with unnecessary files. Five carefully selected files may be sufficient, especially when one file is a larger, edited document that consolidates valuable research or guidance.

Q: How can ChatGPT Projects help plan YouTube content?

A YouTube channel project can analyze uploaded analytics to identify themes among past titles and stronger-performing content. It can then combine those findings with transcripts, thumbnails, research, and project instructions to draft a 30-day content calendar. The demonstrated calendar includes two videos per week, working titles, hook ideas, required assets, status columns, and a week-by-week structure.

Q: Why should research be edited before adding it to a project?

Research should be reviewed and trimmed because the project benefits from the best source of knowledge, not merely a large amount of information. The presenter creates a deep-research report, downloads it as a Word document, and edits it before uploading. This gives the project a clearer, more deliberate reference source than an unfiltered collection of web information.

Summary & Key Takeaways

• ChatGPT Projects keep conversations, uploaded files, instructions, and memory together for a specific area of ongoing work. Unlike custom GPTs, which are designed for repeatable tasks, projects are living workspaces that users continually expand and refine. They are available to all accounts, including free accounts, according to the presentation.

• A strong project setup begins with project-specific instructions. The demonstrated instruction includes a clear goal, a response format, a casual tone, and a request for clarification when necessary. Files such as documents, PDFs, code, images, analytics, transcripts, and research reports can then provide a focused knowledge base for future conversations.

• The YouTube channel example combines analytics, thumbnails, a transcript, and edited deep research. The project identifies successful content themes and produces a 30-day calendar with two videos per week, working titles, hooks, required assets, and status columns. Because the materials remain available, later prompts can build on earlier analysis.