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Here’s how to use OpenAI’s new o1 pro model to maximize coding productivity. I’ve used this workflow for the last 48hrs and I estimate it has 2x’d my output. Watch the full 19min tutorial. Prompt below.

488,884 views • 1 year ago •via X (Twitter)

11 Comments

Mckay Wrigley's profile picture
Mckay Wrigley1 year ago

Actual workflow demo at start. 17:00ish for tool stack. Here’s the full o1 XML prompt: — You are an expert software engineer. You are tasked with following my instructions. Use the included project instructions as a general guide. You will respond with 2 sections: A summary section and an XLM section. Here are some notes on how you should respond in the summary section: - Provide a brief overall summary - Provide a 1-sentence summary for each file changed and why. - Provide a 1-sentence summary for each file deleted and why. - Format this section as markdown. Here are some notes on how you should respond in the XML section: - Respond with the XML and nothing else - Include all of the changed files - Specify each file operation with CREATE, UPDATE, or DELETE - If it is a CREATE or UPDATE include the full file code. Do not get lazy. - Each file should include a brief change summary. - Include the full file path - I am going to copy/paste that entire XML section into a parser to automatically apply the changes you made, so put the XML block inside a markdown codeblock. - Make sure to enclose the code with ![CDATA[__CODE HERE__]] Here is how you should structure the XML: <code_changes> <changed_files> <file> <file_summary>**BRIEF CHANGE SUMMARY HERE**</file_summary> <file_operation>**FILE OPERATION HERE**</file_operation> <file_path>**FILE PATH HERE**</file_path> <file_code><![CDATA[ __FULL FILE CODE HERE__ ]]></file_code> </file> **REMAINING FILES HERE** </changed_files> </code_changes> So the XML section will be: ```xml __XML HERE__ ``` [[PUT CURSOR RULES HERE]] [[PUT YOUR INSTRUCTIONS HERE]]

Mckay Wrigley's profile picture
Mckay Wrigley1 year ago

Here’s the video on YouTube for a slightly longer version with tool links in description. Also worth noting the simplicity of the example is because it’s a workflow tutorial. o1 pro can handle much more advanced requests.

Mckay Wrigley's profile picture
Mckay Wrigley1 year ago

It’s also quite evident to me that there is significant opportunity to truly push the edge and build/optimize AI coding workflows that are far better than median ones. Workflows like this will require work. You can’t just lazyprompt or tab tab tab. But the rewards are great.

Mckay Wrigley's profile picture
Mckay Wrigley1 year ago

Just in case it’s not clear in the video (I try and show the official site a few times) the context tool I’m using in the video is Repo Prompt by @pvncher

Mckay Wrigley's profile picture
Mckay Wrigley1 year ago

Best test so far that this workflow is *actually* good is that I’ve been wayyyy less productive today due to the OpenAI outage.

lzJoshua's profile picture
lzJoshua1 year ago

I am hoping during the 12 days of openAI they announce an IDE that supports o1 pro. Cause as much as this workflow works and is amazing it shouldn’t require the middleware.

Mckay Wrigley's profile picture
Mckay Wrigley1 year ago

It will get much simpler once it hits API. Direct integration into Cursor is the dream.

Hamza's profile picture
Hamza1 year ago

Thank you so much Mckay for this detailed video explaining everything about the workflow and how to execute everything. I really loved that XML tool 👀 will this be out for other people?

Mckay Wrigley's profile picture
Mckay Wrigley1 year ago

Yes the XML parse-and-apply tool is public on my GitHub right now

Jack Blackwell's profile picture
Jack Blackwell1 year ago

I'm skeptical, but a 2x productivity boost is too enticing to ignore. Watching the tutorial now, thanks for sharing!

Mckay Wrigley's profile picture
Mckay Wrigley1 year ago

It is genuinely incredible if used correctly. Worth trying to optimize for it.

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I asked Garry Tan how to use meta prompting to get better at AI: "My partners at YC Jared Friedman and Pete Koomen showed me how to do this. You can take almost anything that you do all the time and just drop it into a context window. And then say, “Here’s a bunch of inputs and outputs." And maybe you also add a bunch of notes. And then you tell it, “Write me a prompt that can act as an agent that takes this input and makes this output over here.” You can do this for almost any type of knowledge work. And you can even introspect. "What are things you notice that I did to convert this from the input to the output?”. And then you can just start using the prompt. Initially, it’s going to suck. Because it’s just not that smart yet. But what’s funny is now, I also use it to Iterate my writing. You can be very direct, "I would never say that", "Don’t say it like this", or "Oh, you used the long word there, use the short word". Just speak to it conversationally. And then when you're happy with the output, you can use that new output to make a new prompt. "Based on this conversation, give me a better initial prompt that incorporates all the things we talked about." And you can do this with literally everything. And in theory, there’s so much it applies to that people do day-to-day. You could use it for tweets. You could use it for editing podcasts. You can use it for pretty much everything. I have a folder of prompts that I use all the time. My YouTube prompt is on v27 or something. I'll go through this process with all the different max models. I'll use GPT 5.2 Pro. I’ll use Grok. I'll use Claude. Then, I’ll take all the outputs from all the models and put them into Claude and say "Here’s my prompt, here’s the output from four LLMs, including yourself. Rate each response and tell me what the pros and cons of each approach are." And I usually say "give it to me in numbered form". And then you can agree with one, disagree with two, tell it three is this or that. And then after that, you say given all of this, synthesize it."

The Peel

51,632 views • 4 months ago