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2 minute read
LLM tools can be extremely helpful at extracting key information to respond to RFPs. If you want an LLM tool to help you draft stronger, faster RFP responses, the most important work isn’t the model, it’s the library behind it. A messy repository makes the tool confidently wrong. A curated one makes it feel like you hired a great proposal assistant.
Here’s how to set up your library so LLMs actually help you win.
Keys to Setting up a Library
1. Treat your library as a single source of truth
LLMs don’t know which version is “right.” If content lives across emails, local folders, and random uploads, you’ll get outdated or inconsistent answers.
Best practice:
- One authoritative “Approved” library
- Clear ownership by section
This reduces rework, risk, and bad answers.
2. Use a shared drive, not file uploads
Uploading files into tools creates copies—and copies go stale.
A shared drive:
- Keeps one live version
- Preserves version history
- Makes updates instantly available to people and the LLM
Rule of thumb: the drive is the system of record. Tools read from it; they don’t replace it.
3. Match your folder structure to how RFPs are scored
RFPs are evaluated by section. Your library should mirror that logic.
Recommended structure:
- Company Overview & Legal Entity Information
- Relevant Experience & Past Performance
- Case Studies & Success Stories
- Product & Services Offered
- Methodology, Process & Delivery Approach
- Staffing, Roles & Organizational Structure
- Compliance, Certifications & Regulatory Alignment
- Security, Privacy & Risk Management
- Service Levels, SLAs & Support
- Financial Stability & Insurance
- Technical Capabilities
- Boilerplate, Standard Language & Disclaimers
This helps both humans and LLMs find the right answer fast.
3. Match your folder structure to how RFPs are scored
Proposal content expires.
Simple rules that work:
- Assign an owner per section
- Add “Last reviewed” dates
- Review higher-risk content more often
- Remove outdated content instead of letting it quietly break future proposals
How LLMs actually interpret your content
LLMs don’t “read everything” or reason like a human reviewer. They work by:
- Breaking your library into small chunks
- Comparing the meaning of an RFP question to those chunks
- Pulling the closest matches
- Drafting an answer using only that material
Tags and structure matter because they guide this matching process. When content is clearly scoped, consistently named, and properly labeled, the LLM is far more likely to pull the right answer and avoid the wrong one.
Bottom line: understanding how LLMs interpret data helps you structure content in a way that improves accuracy, speed, and confidence in your responses.
Next steps (one-week effort)
- Create a shared drive with folders by Content Category
- Assign owners to each section
- Identify the best and most accurate files per Content Category and load them
- Archive outdated content so it doesn’t accidentally get loaded in the future
That baseline setup alone can dramatically improve LLM output quality.