How to Build a Custom GPT, Claude Project, or Gemini Gem in 2025

In the world of AI, the big three – OpenAI’s Custom GPTs, Anthropic’s Claude Projects, and Google’s Gemini Gems – are quick-and-easy ways to interact with large language models (LLMs). Whether you’re a real estate professional looking to build a custom assistant or a founder aiming to scale operations through automation, these tools offer a fast way to create mini AI agents that are tailored, task-specific, and quite useful.

This post breaks down the essential steps to build your own custom GPT, Project, or Gem. By the end, you’ll know how to structure instructions, upload knowledge, refine performance, and test like a pro.

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What Are These Custom Mini “AI Agents”?

In simple terms, all three platforms let you:

• Define a custom set of instructions (the brain).
• Upload supporting documents or data (the knowledge).
• Enable capabilities/tools like web search or coding.
• Provide prompt examples for users to get started.

Think of them like teaching your junior analyst to perform a very specific task exactly the way you want it to.

Step-by-Step: Building Your Custom GPT, Project, or Gem

1. Start with a Use Case

Clarify the task your AI agent is solving. The narrower and more defined, the better. Examples include:

• A deal screener trained on your investment criteria.
• An email assistant that drafts responses in your tone.
• A leasing bot trained on your company’s policies.

2. Set Custom Instructions

Use a structured prompt framework like RODES:

• Role (R) – Define the AI’s persona. Be specific about who the assistant is and the voice it should adopt.
• Objective (O) – Clearly state the goal. What is the user trying to accomplish with this interaction?
• Details (D) – Provide the blueprint for success. Include requirements, constraints, and context.
• Examples (E) – Include sample inputs and desired outputs. This helps align the AI’s responses with expectations.
• Sense Check (S) – Ask the AI to confirm understanding before proceeding. This minimizes misinterpretation and ensures accuracy.

Here’s how this might look in a commercial real estate context:

• Role: You are a seasoned real estate analyst trained to analyze market trends.
• Objective: Analyze industrial cap rate trends in the Chicago market over the last five years.
• Details: Focus on Class A industrial buildings larger than 200,000 SF from Q1 2018 to Q1 2023.
• Examples: Generate a list of relevant sale comps with accompanying cap rates and sale dates.
• Sense Check: Ask, “Before performing the analysis, do you have any questions?”

3. Upload Supporting Knowledge

This is where your AI gets smart. You can upload:

• Examples of prior work (e.g., past investment memos, deal reviews).
• Process documentation.
• FAQs or client resources.

Ensure your instructions clearly state when and how to use these files. Curate them carefully—they serve as a secondary set of prompts.

4. Add Prompt Starters

Give users a head start. Examples:

• Help me screen this real estate deal.
• Write an LOI for a retail property.
• What’s the cap rate for this investment?

5. Choose Capabilities

Decide what additional capabilities your agent should have, such as:

• Code Interpreter: Essential for working with spreadsheets, PDFs, and data.
• Web Browsing: If your GPT needs real-time data.
• Image Generator: Great for design, branding, or mockups.
• Canvas: Ideal for spatial tools and drawings.

6. Test and Iterate in Preview

Don’t skip this step. Play around:

• Try common user inputs.
• Verify if it uses the right tone and knowledge.
• Check if it stays within scope.

Tweak instructions and re-upload better-curated knowledge if needed.

Pro Tip: Add Signals to Make It Feel Human

Want to make your GPT feel more intuitive? Add a file called user_signals.txt. In it, define user “signals” like frustration, confusion, or praise and include suggested response styles. This helps the GPT adapt, reassure, or clarify automatically.

Examples:

• Signal: User is confused.
  Response: “Totally get that. Want to walk through an example together?”
• Signal: User expresses frustration.
  Response: “Sounds like a tricky spot. Let’s work through it step by step.”

Naming Matters

Your agent’s name should be:

• Concise and descriptive.
• Consistent with your branding.
• Avoid ending with “GPT” unless it adds value.

Examples:

• Investor Screener
• Tracy Assistant
• CRE Deal Coach

Tools of the Trade

Here’s a simple checklist to ensure a quality build:

• Clear purpose
• RODES-based instructions
• Curated and relevant knowledge files
• Conversation starters
• Appropriate capabilities enabled
• Real-world testing

Closing Thoughts

Custom GPTs, Claude Projects, and Gemini Gems are true amplifiers of your expertise. With a clear purpose, smart instructions, and curated knowledge, your AI agent can become a valuable member of your team.