Draft:Advanced Virtual AI Systems Programming

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Draft:Advanced Virtual AI Systems Programming

AVAP (Advanced Virtual AI Systems Programming) is a high-level, AI-native programming language designed for the creation, orchestration, and management of AI Systems (APIs + MCP Servers + AI Agents) developed by 101OBEX, Corp in Palo Alto the heart of Silicon Valley. Unlike general-purpose languages like Python or C++, AVAP is domain-specific, focusing on the abstraction of backend logic and service integration.

Raúl Nogales (Founder & CEO) and Rafael Ruiz (Co-Founder & CTO) began working on AVAP (Advanced Virtual API Programming) in 2024 as a new arquitecture for virtual programming language. AVAP (Advanced Virtual AI Systems Programming) or AVAP 3.0, released in 2026, was a major revision and coverage increase the language from API to AI Systems.

AI Systems: The Next Evolution of Software

For decades, software systems have been designed around a simple model: humans operate applications.

Users interact with interfaces, developers write code, and operators manage the infrastructure that keeps systems running. APIs enable communication between services, but the execution and orchestration of systems ultimately depend on human intervention.

Artificial intelligence is changing this model.

Recent advances in AI reasoning, agent architectures and system interaction protocols are enabling artificial intelligence to move beyond analysis and content generation. AI is increasingly capable of executing actions, coordinating processes and interacting directly with software systems.

This shift introduces a new class of software architecture.

From Applications to AI Systems

Traditional software architectures were designed for applications and humans.

AI introduces a fundamentally different requirement: systems must expose capabilities that artificial intelligence can discover, understand and execute.

An AI System is a software system whose capabilities can be discovered, reasoned about and executed by artificial intelligence, enabling humans and AI to operate it collaboratively.

In an AI System, digital infrastructures are no longer composed solely of applications and services. Instead, they are structured around capabilities that can be invoked and coordinated by intelligent agents.

These systems typically integrate:

  • APIs and services
  • executable capabilities and tools
  • orchestration layers
  • interaction protocols enabling AI access
  • intelligent agents capable of reasoning and execution

Together, these components form systems where software and artificial intelligence collaborate to execute processes, manage operations and evolve digital infrastructure.

The Infrastructure Gap

While artificial intelligence capabilities have advanced rapidly, most existing software infrastructures were not designed to support AI-operated systems.

Traditional architectures lack:

  • structured capability layers
  • AI-discoverable system functions
  • lifecycle management for AI-operable systems
  • operational intelligence for autonomous orchestration

As a result, organizations face a growing gap between the capabilities of artificial intelligence and the structure of the software systems it needs to operate.

Enabling the next generation of software requires a new technological foundation.

Design Philosophy

The core philosophy of AVAP is "Logic over Infrastructure." It aims to reduce the overhead of traditional API development by:

  • Virtualization: Decoupling the API logic from the server instance, enabling seamless versioning and live updates.
  • AI Integration: Providing native syntax for interacting with Large Language Models (LLMs) and generative AI to automate data mapping and service discovery.
  • Security by Design: Implementing granular access control and tokenization at the language level rather than through external middleware.

Technical Architecture

AVAP is structured around the AVAP Engine, which interprets scripts and manages the lifecycle of a request.

  • The Virtual Core: Manages the execution context and state between different steps of an API or MCP tools call.
  • Discovery Engine: An AI-driven component that allows AVAP to automatically identify and connect to external services (REST, SOAP, or Databases) based on semantic descriptions.
  • Protocol Neutrality: AVAP acts as a translation layer, capable of ingesting one protocol and outputting another (e.g., transforming a legacy SOAP response into a modern JSON/REST endpoint).

Syntax and Examples

AVAP uses a structured syntax that combines declarative elements with imperative logic. A typical script defines a Logical Step and a Target Service.

// This is a basic starting point for developing an API using AVAP language.

// Creates a global variable named 'final_message' with the value \"Hello World!\".

addVar(final_message, 'Hello World!')

// You can capture parameters sent by the client via query string, headers, or request body.

addParam(name,name_recovered)  

// You can read or write from a database into AVAP variables.
// This template omits real DB operations, but here's an example:

// ormAccessSelect('username,id', dbase, 'age > 25', usersList)

// AVAP allows you to connect to databases using AVAP Connectors, external database libraries, 
// psql_connector = avapConnector(\"REJfQ09OTkVDVE9SMTc1MDQ2MjI0MDMyO1=\")
// users = psql_connector.query(\"select * from obex_users;\")
// or its native ORM capabilities.

// You can add validations, conditions, loops, or transformations here.
// Example: personalize the message if 'name' was provided.

if(name_recovered,None,'!=')
    final_message = \"Hello %s\" % name_recovered
end()

// Adds the variable 'final_message' to the result object.
// Any variable added via 'addResult' will be included in the API response.

// To control the HTTP status code returned by the API, assign it to the '_status' system variable.

addVar(_status,205)

// Use addResult to include it in the final response payload.

addResult(_status)

addResult(final_message)

Deployment and Ecosystem

The AVAP ecosystem is built around AVAP Sphere, its central platform for professional and enterprise environments, available in both on-premise and cloud deployments. This flexibility allows organizations to adapt the system to their specific needs in terms of scalability, security, and infrastructure control. AVAP Sphere acts as the core layer, providing orchestration, data management, and application services.

  • AVAP Cloud: Powerful API platform to manage the entire API lifecycle in a SaaS model from design to testing and deployment. Powered by AVAP technology, virtuality and artificial intelligence will be in the core of every AI System.
  • AVAP Language Server: AVAP Language Server empowers developers with a high-performance environment to seamlessly execute and manage API code. Designed for speed and scalability, it translates AVAP code into real-time actions, ensuring efficient API execution and smooth communication between servers.
  • AVAP Gateway Advanced: AVAP Gateway Advanced is a high-performance, intelligent solution that goes beyond basic proxy functionality.
  • AVAP Virtual Server: Redefining API Managers, iPaaS to AI Systems lightweight scalability, virtual and with universal compatibility.

References

Official Website[1]

Developer Website[2]

Repository Open Source AVAP Lenguaje Server [3]

Repository Open Source AVAP Language Definition Server [4]

Repository Open Source PLATON (Kernel Virtual Language Programming) [5]

Reddit Channel for Developers [6]

  1. ^ htpps://www.avapsphere.com
  2. ^ htpps://developer.avapsphere.com
  3. ^ https://github.com/AVAP-Framework/AVAP_Lite_oss
  4. ^ https://github.com/AVAP-Framework/AVAP_Definitions_Server
  5. ^ https://github.com/The-PLATON-Foundation/PLATON-OSS
  6. ^ https://www.reddit.com/r/AVAPDev

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