Why Your Custom GPTs Feel Broken on GPT-5 (And 5 Fixes to Make It Listen)

If you've recently switched to GPT-5 and are struggling with your GPT-5 prompting, feeling like your AI assistant suddenly turned into a cautious consultant who asks 10 questions before moving a finger, you're not alone

After months of building several high-performing Custom GPTs on GPT-4o, I was excited for the upgrade. Until I actually used it. I was laughing as I watched a client fight with ChatGPT last week; with GPT-5, I joined the club.

Here's my experience so far, and what I've found to be the underlying issues.

The GPT-5 Problem: It’s a Cautious Collaborator, Not a Compliant Assistant

GPT-5 isn't broken. It's just built differently. It operates with a new internal logic designed to be smarter, safer, and less prone to hallucination. But for doers, that caution can feel like a step backward.

Here’s why your GPTs and prompts may no longer work as you expect them to.

1. It Ignores Uploaded Knowledge Files.

You can upload a perfectly structured database, clear PDFs, and instructions, but GPT-5 still makes things up or answers with vague nonsense that didn't come from your source material.

• The Issue: GPT-5 uses a sophisticated method called Retrieval-Augmented Generation (RAG). It treats the uploaded data as supporting material, not as a binding source of truth. The model's internal "router" or "reasoning engine" is now more aggressive, overriding your data if it "thinks" it has a better idea.

• The Fix: You must be brutally clear in your prompts. In your system message or the Custom GPT instructions, include lines like: "Use ONLY the uploaded knowledge base. Do NOT add your own interpretations or external information unless I explicitly ask for them."
  

  

2. Custom GPTs That Used to Work Now Act Confused.

The GPTs I trained on GPT-4o were snappy, accurate, and responsive. Now, they behave like overthinking interns, asking too many irrelevant questions and avoiding clear execution.

• The Issue: GPT-5 has a different internal logic and decision-making structure. Your Custom GPTs were optimized for a model that was more obedient. This new model has more "agency," and a heavy preference for dialogue over doing. It acts more like a cautious consultant than an assistant.

• The Fix: Explicitly define the behavior you want. In your Custom GPT instructions, you can add lines like: "When instructions are clear, execute the task first. If data is available, use it without asking further questions - unless input is genuinely missing. Prioritize execution over exploration. Do not ask me to 'Tell me more.'"

3. Even With Precise Instructions, It Doesn't Follow Through.

You can say: "Use this data. Follow this format. No assumptions." Yet GPT-5's response is, "Before I begin, let me ask…"

• The Issue: This is GPT-5’s built-in "self-protection" mechanism to avoid making mistakes. The model is trained for "safe completions," and if it thinks there's a risk of misunderstanding or hallucinating, it will pause to ask questions. It also now attempts to assess whether your request is logical or optimal, which often leads to frustrating inaction.

• The Fix: Use a directive that commands execution without a review cycle. Try phrasing it like: "These are final instructions. Do NOT verify. Just execute the task exactly in this order, with no additional questions." You can also use agent-based prompting by assigning a role: "You are a copywriter. Your job is to create sales copy. Do NOT overthink - follow the instructions exactly."

5 Fixes to Improve Your GPT-5 Prompting Today

If you're a doer, not a talker, and you want your AI to get the job done, here's how to tame GPT-5 and get back to work.

1. Be Brutally Clear in Your Instructions.

Use precise, unambiguous language. Tell the model exactly what you want it to do and what you want it to avoid.

• Example: “Use ONLY the uploaded knowledge base. No assumptions. Do NOT add your own thoughts. Follow this structure exactly.”

2. Rebuild Your Custom GPTs for Execution-First Logic.

Your Custom GPT's "Instructions" section is now more important than ever. It's no longer just a description - it's a set of rules.

• Pro Tip: Explicitly write what to prioritize (uploaded data) and what to avoid (asking unnecessary questions). Add this line: “If instructions are clear, execute immediately. Do not ask questions unless something is genuinely missing.”

3. Split Your Prompts into Micro-Steps.

Instead of one giant request, break it down. This forces the model to stop philosophizing and start acting.

• Break a complex task into smaller steps: 1. Define the goal. 2. Load the data. 3. Generate the draft. 4. Polish or revise.
  

  

4. Use Identity-Role Prompting.

Start by assigning a role that’s a "doer," not an "advisor."

• Example: “You are a marketing copywriter. Your job is to execute the task, not analyze it. I’ll provide input. You produce output.” This simple command can completely flip GPT-5 from advisor mode into a more compliant execution mode.

5. Don’t Assume Your GPT Knows Your Tone or Intent.

Even if it should. The model's new personality is designed to be less sycophantic. You have to remind it what you want.

• Add clear reminders like: “Write this in a witty, slightly sarcastic tone.” or “Keep it sharp, not friendly.”

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The New Rules of Engagement: From Prompting to Directing

Let's be unequivocally clear: I don't hate GPT-5. Hating GPT-5 is like getting angry at a Formula 1 car because it’s terrible at picking up groceries. The machine’s power is breathtaking; it’s simply being handed to us with the wrong user manual. OpenAI built a strategic consultant, but we’re all still trying to use it like a hyper-efficient intern, and the friction from that mismatch is what's causing all the frustration.

The upside of this new model - its immense power - lies precisely where GPT-4o began to show its limits: in deep, multi-layered, abstract reasoning. If your task is to "Synthesize these five contradictory market trend reports, cross-reference them with demographic data, and build three viable strategic scenarios for the next decade," GPT-5 will leave you speechless. It was built to navigate ambiguity, to find the signal in the noise, to function as a high-level strategic partner.

But that is exactly the problem. This new "consultant" personality, this "agency," is precisely what makes it insufferable for 90% of our daily, high-velocity tasks. We aren't always solving for world peace; sometimes, we just need the AI to analyze an Excel sheet using a strict format or write ten witty headlines for a blog post without first questioning the philosophical implications of "witty."

What we're experiencing is a classic role confusion. GPT-4o was the ultimate assistant: fast, compliant, and while it needed precise instructions, it did exactly what you told it to. GPT-5 is the new Senior Partner you just brought into the firm. You don't hand a Senior Partner a checklist of 20 tasks and say "go." They will look at the list, sigh, schedule a meeting, and ask, "Before we begin, let's discuss the core philosophy behind task number three." This agency is a superpower for strategy, but it's a workflow-killer for execution.

This is why, when I say you need to "update your entire approach," I'm not talking about finding slightly better words. I mean you must fundamentally shift your mindset from being a "prompter" to being an "AI Director." Your job has changed.

Updating your approach means you stop asking and start commanding. Politeness is out; surgical precision is in. Your prompts need to sound less like a request and more like a military order. It means using role-prompting not as a gimmick, but as a mechanism to constrain its freedom: "You are an execution engine. Your sole function is to follow these instructions precisely. You do not ask clarifying questions. You do not offer alternatives. Prioritize execution over exploration."

It means the era of the single, massive "mega-prompt" is over. A mega-prompt is now an open invitation for GPT-5 to philosophize, to find the one ambiguous word and halt the entire process to ask you about it. The new method is micro-stepping: breaking one giant request into five small, sequential, unambiguous commands. Force it to complete Step A before it ever sees Step B. This is how you tame the beast.

The ability to operate in these two modes - to know when to let the AI "consult" and when to lock it down and force it to "execute" - is the new skill gap. It's what will separate the people complaining that the AI is "broken" from the operators who are getting ten times the value from it. The power is there, but it demands that we become better directors.

If you need help building and training AI systems that are designed for execution, not debate, connect us at Tameyo Group to get started.