Free resource
Open-source AI deployment checklist
Before you deploy an open-source AI or web project for real, use this checklist to run through the most easily missed items that tend to become problems later.
Many projects do not die because people cannot build them. They die because nobody thought through deployment.
This checklist is for independent developers, small teams, and solo founders. It does not try to give you generic “AI startup advice”. It helps you think through the most important deployment, configuration, risk, and maintenance questions before you spend more time on a project.
How this resource differs from the public article
The public article is the explanation version.
It helps you understand why many projects do not fail in development, but fail because the deployment plan was never clarified.
The free checklist is the execution version.
It is not something you read once and forget. It is something you use before deploying to make sure the right questions have been answered.
- if you want to understand the problem first, read the article;
- if you want a practical checklist before deployment, get this resource;
- the article helps you understand;
- the checklist helps you actually deploy.
What you get
- a checklist you can use immediately;
- key checkpoints arranged by a real deployment flow;
- a structure that goes from “should I deploy this?” to configuration, data, auth, and launch checks;
- a draft you can extend into your own SOP or project-prep flow later.
Who this is for
- people who already chose a GitHub project but worry about deployment surprises;
- small teams deploying open-source AI or web tools;
- solo developers trying to move from “it runs locally” to “version 1 is usable”;
- anyone who wants to stop wasting time on environment issues and repeated trial-and-error.
Who this is not for
- people who only want generic AI news;
- people with no project direction who are just collecting random resources;
- people who expect one checklist to replace all technical judgment.
How to use it
Download it and go through it point by point.
If you are evaluating a specific project, it works best before the first deployment attempt. If you have already started, you can still use it to find out what you missed.
Preview
This page does not expose the full checklist, but you can preview the core areas it covers:
- deployment context: decide whether the project belongs locally, inside a private network, or on the public internet;
- environment setup: separate required variables from examples and from optional extras;
- data storage: know where the data lives and how backup will work;
- public exposure risk: identify admin pages, debug endpoints, and defaults that should never be exposed;
- rollback and recovery: decide how to recover before something breaks;
- launch scope: make it clear that this release is about getting a first usable version out, not finishing everything.
Get the checklist right away, optionally subscribe for follow-ups
Enter your email and the checklist unlocks immediately. By default you are only getting the resource, not joining email updates; if you choose to subscribe to follow-ups, I will send a confirmation email, a welcome email, and later subscription-management / unsubscribe links through Buttondown.
Checklist unlocked. This was only a resource download; I did not add you to the mailing list automatically.
If you later want new resources, topic notes, or SOP updates, come back and check the subscription box.
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Download and subscription are separate. Even if you do not confirm right away, the checklist is already yours.
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If you could not find the manage-subscription link before, use the Buttondown management link in the email you received; future topic emails will keep including management and unsubscribe links.
If you want a more structured, step-by-step version, I will keep expanding this line into an “Open-Source AI Project Launch and Hardening SOP.”
Why a free checklist instead of a course or service
Most people do not need a grander solution. They need the first useful structure that can actually reduce trial and error.
The point of this checklist is not to decide for you. It is to help you see the important questions before you spend more time and money.
What might come next
If this checklist helps you reduce one round of blind trial-and-error, I may keep extending it into a more complete version. The next obvious expansion would be an Open-Source AI Project Launch and Hardening SOP.
- launch and hardening SOP for open-source AI projects;
- guidance on choosing between deployment paths;
- a quick risk checklist for self-hosted projects;
- a small-tooling stack for solo builders.
Explanation first, or execution first?
- if you want the explanation version first, read Companion article: 10 things to confirm before deploying a GitHub project;
- if you want the execution version now, use the form above to get the checklist and work through it before deployment.