What is Astra?

Modern AI systems reason in patterns, not token‑by‑token syntax. Yet we still ask them to produce languages that were never designed for them — languages where a missing comma or mis‑nested block can break everything.

Astra solves this mismatch. It provides a pattern‑driven, indentation‑structured, and drift‑aware substrate that both humans and AI can write reliably. Expression can vary; meaning stays stable.

Astra programs describe tasks using clear structure and natural phrasing. Here is a small example:

task "count_errors":
    input:
        path: file_path
    output:
        count: integer

    steps:
        read all lines from path into lines
        keep only lines that contain "ERROR" into errors
        set count to length of errors
        return count

Even with flexible phrasing, Astra captures the intent, resolves it into a deterministic structure, and executes it safely.

At a high level, Astra follows a simple flow:

• Expression — you write tasks in natural‑language‑shaped form
• Meaning — Astra resolves phrasing into canonical structure
• Execution — the program runs deterministically and safely

The details of this process are covered in the Docs, but this page provides the conceptual overview.

Astra is not a variant of Python, YAML, JSON, or any existing scripting language. It is a pattern‑based language with its own semantics, safety model, and execution pipeline.

It is designed from the ground up for:

• human readability
• AI writability
• deterministic execution
• drift‑aware interpretation
• pattern‑driven extensibility

“Astra” is a common name used by unrelated tools, libraries, and companies. This site refers specifically to Astra — the AI‑native orchestration language described in these pages.

To understand Astra more deeply:

• Philosophy — the worldview behind the language
• Docs — the architectural model
• Ecosystem — the systems around Astra
• Roadmap — where Astra is going next