AI stacks - terrytaylorbonn/auxdrone GitHub Wiki
25.0729 Lab notes (Gdrive), Git
This wiki section "AI LLM stacks" is a very methodical, structured, and organized approach (WIP) for learning (hands on) AI LLM stacks. For this personal sandbox project, the focus is on this wiki (and the Gdrive docx's). But for a customer project, the wiki would just be an intermediate step in creating the core tech doc deliverables.
- This wiki. Provides the top level overview, organization.
- About the author
- Gdrive. All the docx lab notes files with the nitty gritty details for hands on demos.
- LLM stack concepts.
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LLM stack sandbox overview. Copilot's assessment of my conceptual summary of LLM stack dev (see docx #499):
- "🏆 Overall Assessment: This is wiki-ready! It fills a real gap - I haven't seen anything this concise yet comprehensive. The combination of theory + your actual code examples makes it especially valuable. Recommendation: Publish this! It would be extremely helpful to the community."
This section follows a logical progression from beginner to advanced (how to approach learning AI stacks). Details of each section:
- 2 Demo deployments. The end goal (typically on Render, etc; may also list local model "deployments").
- 3 Youtube demos (NEW). These Youtube demos provide the details that an LLM may not (especially for platforms and tools).
- 4 GPT/CPLT demos (NEW). The core goal of the AI LLM stacks wiki. Create demos from scratch using a co-pilot.
There are basically 2 types of docs:
- 6 LLM/agent docs. The new AI doc paradigm. Delivered to you in-context in your dev environment (just like Amazon delivers to your home).
- Doc content is created specifically to be scraped, repackaged, and presented to the user by AI-based tools (chatbots like ChatGPT).
- In the future, LLM dev tools might just auto-update scraped docs (product dev teams only have to publish the content; the LLMs will automatically take care of the rest). Perhaps websites will be designed for AI (see llms.txt)
- 5 Human reader docs. Traditional "brick and mortar" docs (mostly website based). You visit them to get what you need.
- Note: Seems to me that published docs might start focusing on the prompt chains needed to accomplish tasks. The idea is not to put all the details into a doc, but let the LLM (GPT/CPLT) produce the details (that are customized to the user content).
- Test websites for exploring (as one does in a sandbox) various website tech, mainly for doc websites (docsX.ziptieai.com).
(notes)
- #1 SS/LIN: GPT is best (like driver assist... GCLI / CPLT get you killed).
- #2 SS/LIN:
- future docs
- add tages to docx files (mainly focus on prompts)
- AI picks up and publishes
- suggest, ask, adjust, step by step (miserable github UI/docs)
- future tools
- sites designed for ai
- ai designed for sites (auto update)
- future docs
- /mnt/c/Users/terry/Downloads$ git clone https://github.com/terrytaylorbonn/auxdrone.wiki.git (to avoid win11 \ error)
- GPT feedback about the above structure.
- extract content and eventually delete A1-3 PRIVATE AI stack deploys and A1-4 PUBLIC AI stack deploys.
- AI stack FE/BE compatibility 25.0416