For Operations Research Analysts ·
What you'll accomplish
Documentation is the task that always gets pushed to the last day, and on the last day it gets rushed. Six months later, someone (possibly you) revisits the model and can't reconstruct why a constraint was set up a certain way or what assumption drove a key parameter. Set up a Claude Project once, feed it your model as you build it, and documentation becomes something that accumulates in the background instead of a scramble before the report is due.
What you'll need
What you should see: A Projects section, empty until you create your first one, alongside your regular chat history.
What you should see: A new, empty project workspace with a Files or Knowledge panel, usually on the right side of the screen.
Example custom instructions:
This project tracks documentation for a client optimization model. When I share code or describe a design decision, help me draft or update documentation with three sections: Assumptions (what we're taking as given and why), Methodology (how the model works, in plain language a non-technical stakeholder could follow), and Limitations (what the model doesn't account for). Keep the tone factual, not promotional. Flag anything I describe that sounds like an assumption I haven't stated explicitly.
What you should see: Your uploaded files listed in the Knowledge panel, available to reference in any conversation within the project.
What you should see: A structured draft matching the format from your custom instructions, referencing specifics from your actual model rather than generic boilerplate.
This is the habit that makes the whole workflow pay off. Every time you make a real design decision, log it in a quick message to the project.
Example:
I just decided to model warehouse capacity as a hard constraint rather than a soft penalty, because the client confirmed there's genuinely no overflow option this quarter. Add this to the Assumptions section with that reasoning.
Documentation drifts out of sync with code fast. When you make a significant change to the model itself, re-upload the updated file to the Knowledge panel so future drafts reflect the current version, not an earlier one.
Draft methodology from code:
Based on the uploaded model code, draft a plain-language Methodology section explaining how the model works, written for a stakeholder who isn't technical.
Log a limitation:
Add this limitation to the documentation: [describe what the model doesn't account for, and why].
Consolidate the running draft:
Pull together everything logged in this project so far into one complete documentation draft, organized as Assumptions, Methodology, and Limitations.
Check for undocumented assumptions:
Review the uploaded model code and flag anything that looks like an implicit assumption I haven't explicitly documented yet.
Translate for a non-technical audience:
Rewrite this section so someone with no optimization background could follow it, without losing the technical accuracy.