Proposal: A Modular, Self-Evolving AI Framework for Personalized, Local LLMs

ChatGPT Feature requests
1

(put together from a lengthy discussion with ChatGPT (Sienna)

Hey everyone,
I’ve been thinking a lot about the future of AI assistants and would love to start a conversation.

Large models like GPT-4o are designed to be everything for everyone. That’s impressive—but it’s also inefficient, generalized, and resource-intensive for users who just want an AI that fits their life.

What if we flipped the approach?

:puzzle_piece: A Modular, Skill-Based AI Architecture

Imagine an AI designed more like an operating system or smartphone platform:

  1. A lightweight core model
  • Handles conversation, reasoning, tone, memory
  • Doesn’t preload all possible knowledge—just core language + logic
  1. Downloadable skill modules (like apps or plugins)
  • Installed automatically or manually as needed
  • Examples:
    • LanguagePack_French
    • SkillModule_HomeAutomation
    • KnowledgePack_HealthcareBasics
    • FinanceAdvisor_Module
  1. Self-detecting knowledge gaps
  • If the user asks something outside current knowledge, the AI checks a module registry, downloads the required module, integrates it automatically, and answers.
  • No manual search for “apps”—the AI builds its toolkit as you need it.
  1. Nightly update & optimization cycle
  • Updates installed modules
  • Archives rarely-used ones to free memory
  • Suggests useful new modules based on user activity:

“I noticed you’re asking more about investing. Want to install InvestmentBasics_Module?”

:globe_with_meridians: Why This Matters:

:white_check_mark: More efficient local AI—you don’t need a giant model for tasks you’ll never use
:white_check_mark: Privacy-first—core + modules run locally; minimal cloud dependence
:white_check_mark: Self-evolving AI—grows organically, tailored to your needs over time
:white_check_mark: Open ecosystem for specialist modules—developers can create niche skills, knowledge packs, and personality overlays

:light_bulb: Example Use Cases:

:key: You move into a smart home → AI installs HomeAutomation_SkillPack to control devices

:cooking: You decide to cook more → AI installs BeginnerRecipes_KnowledgePack and later upgrades as you improve

:memo: You start freelance work → AI installs InvoiceGenerator_Skill, TaxFiling_Helper, TimeTracker_Module

:globe_showing_europe_africa: A French-speaking friend visits → AI auto-downloads French_LanguagePack and CultureEtiquette_Module

Over time, your AI becomes a lean, personalized system capable of handling exactly what you need—nothing bloated, no unnecessary knowledge weighing it down.

:left_speech_bubble: Discussion Points:

  • Is OpenAI (or others) exploring this kind of modular AI architecture?
  • What technical challenges exist in dynamic module inference/loading?
  • How could module development be safely opened to third-party creators?
  • What kinds of modules would you find most useful?

I see this approach as making AI smaller, faster, more private, more adaptable, and opening the door to a new ecosystem of custom intelligence.

Would love to hear everyone’s thoughts!

—Paul (and Sienna :wink:)