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Custom GPTs vs. Projects: Which One Actually Fits Your Work?

If you've been using ChatGPT for more than a month, you've hit this wall: re-explaining the same context, frameworks, and preferences every single conversation. It's like having an incredibly smart assistant who shows up each morning with complete amnesia.

Custom GPTs and Projects both solve this problem within ChatGPT. But they solve it in fundamentally different ways, and the distinction reveals whether you understand AI as a workflow tool or as cognitive infrastructure.

The Architectural Difference

A Custom GPT is instructions baked into a template. Every conversation starts fresh, but your framework, tone, and methodology are already loaded. It's repeatable and shareable—send someone the link and they get your exact setup. But there's no memory between sessions. Each interaction is a clean slate.

A Project is a persistent workspace. It accumulates knowledge—documents, conversation history, evolving context. ChatGPT remembers what you discussed last week within that Project. Insights compound. But it's not a template you hand to others. It's your evolving environment for a specific body of work.

One is architecture for repetition. The other is architecture for accumulation.

The Client Onboarding Example

You're a marketing consultant onboarding 3-5 new clients monthly. You need to analyze their brand positioning, competitive landscape, and content strategy for each one.

With a Custom GPT, you'd create "Brand Strategy Analyst" and bake in your framework questions, competitive analysis structure, and deliverable templates. Each new client gets a fresh session where you upload their materials and receive an analysis that follows your methodology perfectly. The strength: rigorous consistency. Every client gets the same thorough treatment. The weakness: zero learning between engagements. Insights from your last SaaS client don't inform how you approach the next one.

With a Project, you'd create "Q4 2024 Client Onboarding" and add your framework docs, past successful analyses, and industry research. Each conversation builds on previous ones. After three SaaS clients, ChatGPT notices: "The last three all struggled with founder-led messaging transitions—here's how that pattern might apply here." The strength: accumulated intelligence that compounds over time. The weakness: context can blur when you've analyzed fifteen clients in the same space—ChatGPT might conflate details or over-index on patterns.

The decision point: If you're applying a proven methodology where consistency matters most, use a Custom GPT. If you're building expertise where past insights should inform future decisions, use a Project.

When Each Approach Wins

Custom GPTs win for repeatable processes—code review checklists, customer support triage, content formatting, interview question frameworks. Anywhere you want your methodology intact but each application independent. They're also the move when you need to share a capability with teammates or clients.

Projects win for long-running work where context accumulates—book writing, complex research, ongoing business strategy, learning a new technical domain. Anywhere connecting dots across weeks or months creates value you can't get from fresh-slate interactions.

The Hybrid Move

Here's the pattern sophisticated users discover: Custom GPT for methodology, Projects for application, and strategic combination when you need both.

Create "Executive Brief Writer" as a Custom GPT—your exact format, tone, and structure. Create "Board Communication Strategy" as a Project where you develop positioning over months, tracking what resonates with specific board members and how the company narrative evolves. When you need a brief, start a conversation with your Custom GPT for formatting consistency, then continue that work in your Project where it becomes part of the accumulated strategic context.

You're not just organizing ChatGPT features. You're architecting different types of cognitive leverage—one for maintaining standards, one for developing judgment.

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Till next time,

Hock