A connected ecosystem for intelligent software
What if applications were discovered by the outcomes people need, adapted around their preferences, and supported by an expert companion that understands how the software works?
Assem Hijazi’s ALM (Apps LM) vision connects application design, adaptive interaction, an LLM app marketplace, and robotics-based assistance. The proposal brings intelligence into the full software experience: finding a tool, learning its capabilities, completing work, and shaping future improvements.
Four connected parts of the vision
| Part | Proposed role |
|---|---|
| The ALM software model | Integrate language-model capabilities through standalone, blended, embedded, or robotics-based application experiences. |
| Adaptive user interaction | Help people discover features, reshape menus and settings, and work through guided tasks. |
| The LLM app store | Create a marketplace for task-oriented tools spanning models, domains, countries, and deployment environments. |
| Expert robotic companions | Explore voice, visual, gesture, and physical interaction as extensions of software guidance. |
From finding an app to achieving an outcome
| Experience | What it could enable |
|---|---|
| Discover | Find applications by task, professional domain, language, or regional requirements. |
| Personalize | Apply selected preferences and configure an interface around relevant features and workflows. |
| Work | Combine familiar controls with conversation, contextual assistance, and embedded automation. |
| Learn | Receive explanations, demonstrations, and guidance while using the application. |
| Extend | Suggest missing capabilities and communicate feedback to developers for refinement. |
| Connect | Use compatible tools across local devices, cloud services, and selected models. |
The marketplace layer
The proposed LLM store provides a shared environment for discovering intelligent applications. It could support domain-specific tools, localized offerings, multiple models, and local or cloud deployment. Consistent interaction and compatibility conventions would help users move between tools and help developers reach different audiences.
This marketplace vision includes simpler model integration and adaptable applications. These remain architectural goals requiring agreed interfaces, permissions, testing, and deployment support.
The robotics layer
Robotics-based ALM applications extend the concept into expert companions that can guide users through software, present relevant options, and assist with tasks. The articles explore robotic cameras, miniature devices, voice, visual cues, gestures, and movement as possible interaction channels.
The ambition is more accessible and contextual software assistance. Such systems would need explicit permission for sensing, careful validation of inferred signals, reliable task execution, and clear human control. The broader robotic experience is a future direction rather than a capability assumed to exist in every application.
The central vision
An ecosystem where intelligent applications are easier to find, easier to use, and more responsive to human needs. The app store supplies discovery, ALM supplies the integration model, adaptive interfaces shape daily work, and robotic companions explore richer ways to interact.
