The Project 2025 Trump II Strategic Plan LLM
Now that Donald Trump has been reelected, Republicans unsurprisingly revealed that Project 2025 was the plan all along. Read about that here, here and here.
With news of Trump II wanting to use recess appointments to install operations-level appointees, it's clear that the Project's goal of a quick takeover of the bureaucracy is coming true.
They crated it for a reason. It's fair, to me, to use a tool like this LLM to find out what's to come for our families, friends and neighbors.
- Sebastian James
- November 11, 2024
- 6:25 am
- 0 comments
The Project 2025 Trump II LLM is a large language model (LLM). Think of an LLM as a super-sophisticated chatbot able to provide detailed and nuanced answers to a question. The best practice for using LLMs is to fill them with data around a single topic or subject and use it as a digital assistant. A really, really smart digital assistant; complete with the occasional mistake or misinterpretation.
Inside the bot, I've packed the following:
- The 900-page Project 2025 Manuscript
- The 46 promises that make up Agenda 47, a list of early Trump campaign promises
- The 2024 GOP platform
- The recent Supreme Court decision on presidential immunity
- Legal writing on AI and US law
- Legal writing on liability and climate change
- Legal writing on the impact of the Patriot Act and individual liberty
- The Peoples Guide to Project 2025, a breakdown of the effects of the project
- The texts of major Supreme Court legal decisions like Citizens United, Dobbs, Roe v. Wade, and Brown v. Board of Education, Creative LLC and Obergfell
- The texts of Sarbanes-Oxley and Dodd-Frank
- Model fine-tuning and training docs
Using the Project 2025 Trump II LLM
We encourage you to use the starter questions to begin diving into Project 2025, and let those responses feed your curiosity to ask more. Below the chatbot you'll find links to its data and the URL's it uses to frame opinion on its application.
Here are some good questions to ask about the combination of the 2024 GOP Platform, Agenda 47 & Project 2025:
- Recap the top ten changes under Project 2025 by cabinet agency
- What happens to the Federal Reserve under Project 2025?
- How will Project 2025 change American foreign policy?
- How will American manufacturing policy change?
- What will American universities look like at the end of four years of Project 2025?
- How do the Project 2025 judicial policies enable Agenda 47?
Tips on using the LLM
Be clear and specific in your questions
Good questions follow the principles of clarity and specificity. Use simple, unambiguous language and provide enough context and details for the model to understand what you are asking.
Structure your questions meaningfully
Use formatting like bullet points, line breaks, quotes etc. to make them easier to parse. This helps the LLM better understand the structure and intent of your prompt.
Provide examples
Giving a few examples of the kind of output you want can steer the LLM in the right direction, a technique called "few-shot prompting".
Use keywords strategically
Including relevant keywords in your questions can help the LLM focus on the right information for the task.
Leverage data sources
If you have existing data sources like documentation or previous content, providing those as context can greatly improve the LLM's output quality and consistency.
Try different question variations
Experiment with different ways of phrasing and structuring your prompts. Small variations can sometimes lead to very different outputs.
What happens if it acts weird?
The technology sputters at times. Don't fret, just re-ask or rephrase the question. Call it on little errors. The technology will only get better; unlike the outcomes of a successful Project 2025 Trump II .
Tips on using the LLM
Be clear and specific in your questions
Good questions follow the principles of clarity and specificity. Use simple, unambiguous language and provide enough context and details for the model to understand what you are asking.
Structure your questions meaningfully
Use formatting like bullet points, line breaks, quotes etc. to make them easier to parse. This helps the LLM better understand the structure and intent of your prompt.
Provide examples
Giving a few examples of the kind of output you want can steer the LLM in the right direction, a technique called "few-shot prompting".
Use keywords strategically
Including relevant keywords in your questions can help the LLM focus on the right information for the task.
Leverage data sources
If you have existing data sources like documentation or previous content, providing those as context can greatly improve the LLM's output quality and consistency.
Try different question variations
Experiment with different ways of phrasing and structuring your prompts. Small variations can sometimes lead to very different outputs.
What happens if it acts weird?
The technology sputters at times. Don't fret, just re-ask or rephrase the question. Call it on little errors. The technology will only get better; unlike the outcomes of a successful Project 2025 .