The rise of AI-powered code generation has transformed how developers build applications, creating a new challenge: while AI can write services, it cannot understand the surrounding infrastructure needed to deploy and scale them. This disconnect has led to a growing gap between application development and cloud configuration—a problem that a new open-source tool, Neptune, seeks to address.

Neptune, released under the Apache License 2.0, positions itself as a solution to the "Day 2 Wall" problem where AI-generated applications become black boxes that teams cannot effectively scale or maintain. The tool operates within the development environment through an MCP (Model Context Protocol) server, analyzing code structure and intent using Abstract Syntax Tree (AST) analysis and intelligent inference to automatically generate corresponding infrastructure specifications.

"The AI could write a service, but it could not understand the system around it," explains the development team. Neptune attempts to solve this by detecting services, dependencies, and resource requirements directly from the codebase and translating them into cloud-ready configurations.

A Transparent Approach to Infrastructure

Unlike many AI tools that operate as "black boxes," Neptune emphasizes transparency. It generates a deterministic neptune.json specification that clearly outlines the infrastructure being created. This "glass box" approach allows developers to see exactly what will be built and maintain full control over their cloud environment.

Currently, Neptune can infer common infrastructure components including databases, message queues, API services, and background workers. The workflow involves the tool proposing changes to the infrastructure schema, which developers must approve before they are applied. Importantly, the AI does not have direct root access to the cloud environment—only access to the specification file.

Addressing Key Developer Pain Points

The development team outlines three critical problems Neptune aims to solve:

  1. Context Switching: The constant toggling between writing application code and managing Infrastructure as Code (IaC) using tools like Terraform or YAML breaks developer flow state and reduces productivity.

  2. The 'Day 2' Wall: Most AI-generated applications become opaque systems that teams struggle to scale, monitor, and maintain once initial development is complete.

  3. IaC Fatigue: For simple microservices, the overhead of managing complex state files and IaC configurations often feels disproportionate to the task at hand.

Early Stage, Open to Feedback

While promising, Neptune is still in its early beta stages, with the team acknowledging that "there are missing pieces and edge cases." They actively encourage feedback from the developer community, particularly regarding where the tool fails or produces unexpected results.

The transparent approach to infrastructure generation represents an interesting evolution in the AI-assisted development space. By maintaining visibility into how infrastructure decisions are made, Neptune attempts to balance automation with the control that development teams require for production systems.

As AI continues to transform software development, tools like Neptune may become essential for bridging the gap between application logic and operational requirements, potentially redefining how developers approach the full lifecycle of cloud-native applications.