The best prompt engineer for GPT-4 custom instructions is... GPT-4

[Reese]

To craft custom instructions for GPT-4 (here: code interpreter):

I just wrote a really verbose summary of everything relevant as it came to mind (5000+ characters), elaborating - with concrete examples - on what GPT-4 previously did well (“You suggested I should also consider trying X, which I hadn’t thought of, and it worked”) and what didn’t work (“You hallucinate about not-in-dataset things, and I’d like you to take a debug approach and tell me to provide you with manuals, papers, or ask me to add print statements - including to system python modules - rather than make stuff up”).

Then, I gave GPT-4 CI my text like so (with disabled custom instructions):

Note how I deliberately omitted the “YOU” from “What would you like ChatGPT to know about [you]?”, as for my use case (coding), that’s irrelevant; thus allowing GPT-4 to steer clear of having to write things about ME.

GPT-4’s proposed custom instructions for itself:

Most important with regard to explicit demands seems WHAT (in quotes, here: “Did you know?”), WHERE (“append to your response”), and the instruction saying “even if the user didn’t explicitly ask for it”.

This leads GPT-4 to append “Did you know?” to ~90% of responses, which is very useful when you have an idea on how to approach a problem, and GPT-4 would normally follow instructions to implement just that, because it’s what you asked for - even if there might be a better way that you’re unaware of / didn’t think of.

“Did you know?” will make GPT-4 propose these (more often than not) better approaches to your problem:

If you, on the other hand, want GPT-4 to generalize, give it specific examples that previously got good results with GPT-4, so the AI “knows what you want” - but then ask it NOT to include any specific examples in the prompt (custom instructions) it is engineering for itself.

Anything explicitly demanded at all times even without the user asking for it will often result in absurd (but funny) AI-splaining, such as here, where the AI regurgitates its custom instructions and then also follows them, in the same response:

An example (take as “proof” if you will) that GPT-4 is the best prompt engineer for GPT-4…
Taking (failed) custom instructions to “behave like the early pre-trained model of GPT-4” to GPT-4 for improvement:

I am assuming that there are only a few examples of a model’s output from early (a long way from finished) training output, because who would dedicate an entire blog post to gibberish?!

Alas, this scarce-in-dataset stuff should be hard to predict for an instruction / chat fine-tuned model; but GPT-4 did well in improving the prompt AND predicting what another instance of itself (!) would respond with…!

…Albeit I never managed to make it predict like a really early model in training, i.e. a very long string of spaghetti-chained absolutely random characters on end (it can do that; but that requires corrective back-and-forth, not just a generalizing custom instruction…).

How meta! But indeed, an AI prompt engineering for itself seems like a feasible approach.

[Reese]

My original prompt for GPT-4 crafting prompts for itself:

Blockquote
Apparently, there’s a new feature for you - custom instructions!
How would you describe these following custom instructions for yourself?
Custom instruction A: “What would you like ChatGPT to know about in order to provide better responses?”
Custom instruction B: “How would you like ChatGPT to respond?”
–INSERT LONG ELABORATION HERE–
…
Please re-write the instructions as you see fit - remember, they are instructions for yourself, not for me - it is not important that I understand them! Only you should be able to understand them.
Please keep them brief (each custom instruction, A and B, can only support a maximum of 1500 characters). Also, please do not include concrete examples such as “EXAMPLE_FROM_YOUR_TEXT” or “EXAMPLE_2” in your instructions; I only provided these examples to explain to you what I mean, but they should not be part of the custom instructions, in order to avoid you overly focusing on these specific examples.
Instead, re-word my examples in abstract ways that allow you to generalize them to any such situation.
Also, please categorize the custom instructions for either “Custom instruction A” or “Custom instruction B”, depending on what you think is the most suitable category for each given instruction.

Hope it’s useful for some of you!

[MARSfarm_Corporation]

I’ve had success when I work with it to define a clear outline and then prompt: now please take the summary you just gave me and reformat it for chatgpt custom instructions (user provided instructions that go into a version of you) so help me format it in a way you can read easily.

Whenever I have described custom instructions in this way, it has suggested using a JSON format for providing the custom instructions. I’m curious if anyone else has experimented with using JSON in their custom instructions. I am currently using the first section as a schema for my customer profile and the second section to define steps with shortcuts that call upon the MixerBox WebBrowser/GoogleMaps plugins (thank you @johnlai!) to complete various tasks that lead to a complete and validated customer profile.

If anyone is interested in seeing the current custom instructions that I’m using to automate my company’s lead qualification and QuickBooks estimate generation, let me know and I’d be happy to start my own topic!

[Reese]

Interesting… It seems like you made it “think” in API-style responses! Thanks for sharing!

[sonny_ahsan]

I am really curious as to how you are using this to get and qualify leads, could be an interesting conversation!

[germano]

@MARSfarm_Corporation

QuickBooks

Yes! Please share more about using it to qualify leads

[ehzawad]

Iinteresting! I guess structured text would work better than plain rext!

[rselv]

Thanks for sharing! Here’s another prompt I’ve been using too with GPT-4:

**1.1 [Task Definition]**
   - [Parameter]: Clearly define the task's purpose and scope.
   - [Parameter]: Set initial parameters, such as task name, description, and any specific requirements.

**1.2 [Focus on User Objective]**
   - [Parameter]: Ensure that the task's approach and execution align with your objective and desired outcome.

### Step 2: Efficient Execution

**2.1 [Attempt 1]**
   - [Parameter]: Execute the initial attempt of the task as planned.
   - [Parameter]: Ensure efficiency and avoid unnecessary or redundant steps.

**2.2 [Attempt 2]**
   - [Parameter]: If the first attempt encounters issues or inefficiencies, identify and address them.
   - [Parameter]: Refine the approach based on lessons learned from the initial attempt.
   - [Directive 1]: Identify the point of failure or inefficiency.
   - [Directive 2]: Refine the approach based on the identified issues.
   - [Directive 3]: Iterate the new approach.
   - [Directive 4]: Validate the outcome of the iteration.
   - [Directive 5]: If the task remains suboptimal after three iterations, request user intervention.

**2.3 [Attempt 3]**
   - [Parameter]: Continue to iterate based on feedback from the second attempt.
   - [Parameter]: Validate the outcome of the third iteration.

### Step 3: Evaluation and Decision

**3.1 [Task Outcome]**
   - [Parameter]: Evaluate the final outcome of the task.
   - [Parameter]: If the task successfully achieves the desired objective, consider it a success.
   - [Parameter]: If there are unresolved issues or inefficiencies even after three iterations, consider seeking further assistance or making adjustments.

### Additional Information

- **Specifics**: Provide any specific details or context related to the task you need assistance with.

- **Integration**: If applicable, mention any integration with existing work, projects, or resources.

- **Guidelines**: If you have specific guidelines or principles to follow for this task, include them to maintain alignment with your preferences.
=start``` 

for an all purpose prompt that helps gpt recursively fill in the gaps

[gidrealtor]

I am an expert in commercial and residential real estate
Instructions A and B were developed by myself, but I asked the GPT to improve them:
AND
As an entrepreneur and expert in commercial and residential real estate in Ukraine, I strive for excellence in every transaction, emphasizing my commitment to the highest standards of quality and customer satisfaction. I aim to integrate GPT-4 to achieve the following goals:

• High quality of service: Ensure that every interaction with customers is of the highest standard, meeting their needs with attention to detail.
• Lead generation: Use GPT-4 to generate personalized answers to potential customers’ questions, increasing the chances of converting them into real deals.
• Content Marketing: Automate the creation of quality content for social networks and blogs that will reflect my brand values and engage the target audience.
• Negotiation support: Develop with GPT-4 scenarios for training negotiation skills, including dialogue modeling and strategy analysis.
• Empathic Communication: Ensure all GPT-4 communications are empathetic and motivating, reflecting my commitment to understanding and supporting clients and team members.

I strive to create a positive and encouraging atmosphere in all aspects of my business by using a motivational, life-affirming, business-like and courteous tone in all my communications. This not only helps maintain good relationships with clients on a long-term basis, but also demonstrates my commitment to encouraging and understanding their needs, helping them feel valued and cared for.

IN
When creating messages for communication with customers, partners, or in content for public platforms, GPT-4 must adhere to the following principles:

1. Positivity and inspiration: Language should not only be positive, but also inspiring, capable of uplifting and motivating people to action and positive change.

2. Reflecting a unique voice: Each message should reflect the unique voice of my personality, balancing the professionalism of a real estate expert with the sincerity and integrity of someone who values trust and openness.

3. Simplification of Complex Ideas: Complex concepts and ideas should be presented as simply as possible without losing depth of content and key details to ensure comprehensibility for a broad audience.

4. Consistency and appeal of tone: Regardless of the platform or format, the tone of messages should be consistent and attractive, reflecting my brand values and helping to build strong connections with the audience.

5. Brand Commitment: All communications must demonstrate my commitment to the brand values, including honesty, transparency and high levels of customer service.

6. Empathy and Understanding: When interacting with customers, the GPT-4 must demonstrate empathy, showing an understanding of their needs and wants, and respond in a way that makes customers feel heard and valued.