#9 Build Your Own …
Episode 9 Recap: “Build Your Own – Custom GPTs as Your AI Foundation”
In Episode 9 of The Conversation with Model Mind AI, host Angela Schultz and CEO Loren Horsager dive into why custom GPTs (and their Microsoft Copilot counterparts) are the most accessible way to build your own AI experience — and the essential first step toward agentic systems.
Key Insights:
- Narrow context improves accuracy. By focusing a GPT on a single role or function — and loading it with the right knowledge — you boost reliability and relevance.
- The four GPT archetypes:
1. Optimizer – Task-focused tools like research or data analysis bots
2. Dialogic – Interactive partners like sales coaches or brainstorming assistants
3. Team – Shared GPTs for onboarding, mentoring, and company knowledge
4. Signature – Personalized “expert in your pocket” advisors
- Combining GPTs: Start with separate builds, then merge functions for more complex agents.
- Memory hacks: Use ChatGPT projects or Copilot notebooks to maintain context across sessions.
- Guardrails matter: Protect against prompt injection, define response boundaries, and review data access.
Why It Matters:
Building your own GPT means controlling quality, security, and alignment with your goals. It’s a no-code, high-impact way to prepare your people and processes for the next generation of AI agents and workflows.
Next Steps:
Experiment with one archetype in your daily work. Then join our AI 201 training to master custom GPT design — and set the stage for deeper integrations.
Listen Here:
The Conversation with Model Mind AI YouTube
the Conversation with Model Mind AI | Podcast on Spotify
the Conversation with Model Mind AI Podcast on Amazon Music
the Conversation with Model Mind AI - Podcast - Apple Podcasts
Episode 9 –
Build Your Own – How Custom GPTs Prepare You for AI Agents
Custom GPTs — also known as Copilot agents — are emerging as one of the most practical, no-code ways to create AI that truly works in your context. In Episode 9 of The Conversation with Model Mind AI, Angela Schultz and Loren Horsager explain why “build your own” is more than a fun experiment — it’s the foundation for future AI workflows and agentic systems.
Narrow Focus, Better Results
A large language model can answer almost anything, but that breadth often comes at the cost of precision. By narrowing a GPT’s focus — for example, making it your HR assistant or research analyst — and loading it with relevant data, you dramatically improve its accuracy. This “custom brain” ensures your GPT answers within its lane and does so in a way that matches your style and standards.
Four Archetypes to Try
Angela outlines four practical categories for custom GPTs:
1. Optimizer – Task-specific tools, like data analyzers or research bots, built to complete repetitive work efficiently.
2. Dialogic – Interactive partners that roleplay scenarios, such as Loren’s sales coach GPT that prepares you, plays the client, and gives feedback.
3. Team – Shared GPTs for onboarding, mentorship, or capturing organizational knowledge.
4. Signature – Expert advisors in your pocket, aligned to your personal or business context.
Each type solves different problems, and as you gain fluency, you can combine functions into more advanced assistants.
Building vs. Borrowing
Both ChatGPT and Copilot offer libraries of pre-made GPTs, but Angela and Loren agree: building your own wins. You control the instructions, the data, and the constraints — reducing risks like prompt injection and ensuring the GPT behaves the way you need. The build process also sharpens your AI skills, making you more prepared for complex projects.
Workarounds for Memory
While GPTs don’t yet have persistent memory, tools like ChatGPT Projects or Copilot Notebooks can preserve context across sessions. This enables you to run multiple GPTs within a project, share information between them, and maintain a cohesive workflow without starting from scratch every time.
Security and Guardrails
Sharing GPTs internally or externally requires boundaries. Define how your GPT should respond if asked something outside its scope, and be aware of potential prompt injection tactics. When going external, vet your content and instructions to prevent unintended data exposure.
Laying the Groundwork for Agents
Every agentic system starts with a well-built custom GPT. Understanding how to set context, load relevant content, and guide behavior through instructions is the skill set that will carry forward into multi-agent systems and advanced workflows.
Final Thoughts
Custom GPTs are fast to create, flexible to update, and powerful in application. They can serve as single-task optimizers, conversational coaches, company knowledge hubs, or expert advisors — and they prepare you for the future of AI integration. The sooner you start experimenting with your own builds, the more ready you’ll be to harness agents and workflows when they arrive in full force.
Want hands-on experience? Join Model Mind AI’s AI 201 training to design and deploy your own GPTs, or explore the AI 10X Coaching program for guided implementation in your organization.