UnderMouse

In the rapidly evolving world of AI, the quality of your prompts can make or break the usefulness of the responses you get. Whether you’re experimenting with the powerhouse ChatGPT-4o, its streamlined sibling 4o-mini, the versatile o3, or diving deep with research-focused models, mastering prompting techniques will help you unlock the full potential of these tools.

Know Your Models: 4o, 4o-mini, o3, and “Deep Research”

4o: The flagship model, optimized for reasoning, creativity, and handling complex, multi-step tasks.
4o-mini: A lighter-weight variant designed for faster responses with strong reasoning capabilities, ideal when you need quick iterations.
o3: A general-purpose model with balanced performance and efficiency; great for everyday tasks where latency matters.
Deep Research: Tailored for niche, highly specialized queries—think academic literature, advanced technical deep dives, or fine-grained data extraction.

Choosing the right model depends on your use case. If you’re drafting a detailed report or solving a complex technical problem, 4o is your best bet. For rapid prototyping or lower-stakes queries, 4o-mini or o3 may be more cost and time-efficient. When you require authoritative, citation-style answers, turn to Deep Research. These are the models I am most familiar with and regularly use all of them but I would encourage you to try out other models from OpenAI or the many competitors out there (Anthropic, DeepSeek, Google, Meta, etc.).

Keep Prompts Focused on Granular Components

One of the most common pitfalls is overloading a single prompt with multiple objectives. Instead, break down your request into discrete, granular components:

Define the goal: Start by stating exactly what you want (e.g., “Explain the concept of gradient descent in 3 sentences”).
Specify constraints: Limit length, style, or format (“Use bullet points,” “Keep it under 100 words”).
Isolate sub-tasks: If you need multiple things, run them as separate prompts or explicitly label them:

Part A: Define gradient descent.
Part B: Provide a simple Python code snippet.

By focusing each prompt on a single, well-defined task, you help the AI zero in on the relevant information without getting sidetracked.

Include Only Relevant Information

Less is more. Packing your prompt with unnecessary background can dilute the response. Before you hit “send,” ask yourself:

Does the model need this detail to answer correctly?
Will excluding it still yield the insight I want?
Am I adding context because I assume the AI lacks basic knowledge?

If the answer is “no,” trim it out. A concise, relevant prompt reduces processing overhead and improves the clarity of the response.

The Role of Context and When to “Start Fresh”

AI models maintain context within a chat session, which can be both a blessing and a curse:

Use context to build on previous answers, refine drafts, or carry forward variables in a multi-step workflow.
Start a new chat when you notice drift—when the AI starts referencing old topics, or when your new question is entirely unconnected to the previous thread.

Creating fresh chats helps “reset” the model’s memory, ensuring it treats your new prompt as a standalone task and doesn’t conflate separate projects. If you are deep into a chat session and not getting the results you are looking for, it can be helpful to prompt "summarize this chat session" and use that to start your next chat.

Leveraging t3 Chat for Multi-Model Interaction

T3 chat interfaces give you access to most available AI models from different companies, not just OpenAI’s offerings. You can seamlessly switch among GPT-4o, GPT-4o-mini, o3, Deep Research, Anthropic’s Claude, Google’s Gemini, and more. This flexibility lets you:

Brainstorm in 4o for rich, creative ideas
Iterate quickly in 4o-mini (my personal favorite) to test variations at speed
Validate facts in o3 for concise accuracy
Dive deep in specialized research models when you need technical rigor
Tap into different models for different perspectives or domain strengths

By picking the optimal model at each step, you balance depth, cost, and turnaround time - getting the best of every AI provider in one unified chat.

Best Practices for Brainstorming with AI

AI shines as a brainstorming partner. To maximize creativity:

Frame open-ended prompts: “Generate 10 potential blog titles about sustainable fashion.”
Use iterative refinement: Take the AI’s output, pick your favorite ideas, and ask it to expand or combine them.
Encourage variety: Prompt for different tones (“professional,” “casual,” “playful”) or formats (“headlines,” “taglines,” “social media captions”).
Set guardrails: If you want out-of-the-box ideas but not nonsense, specify: “Novelties welcome, but keep suggestions realistic and actionable.”

Putting It All Together

Effective prompting is part art, part science. By choosing the right model, crafting granular, relevant prompts, managing chat context, and leveraging t3 chat for model agility, you’ll get sharper, more useful responses. And when it’s time to brainstorm, follow best practices to spark creativity without losing focus.

With these strategies in hand, you’ll transform your interactions with AI from hit-or-miss experiments into consistent problem-solving powerhouse.

Did I miss your favorite AI prompting strategy? Let me know what works for you at undermouseweb@gmail.com