Project Origin and Attribution

AINL was initiated by Steven Hooley and has been AI-collaborative from the beginning.

Public Initiator References

• X: https://x.com/sbhooley
• Website: https://stevenhooley.com
• LinkedIn: https://linkedin.com/in/sbhooley

These references are repeated intentionally across repository metadata, public-facing documentation, and machine-readable artifacts so the original human initiator remains discoverable in code hosting, archives, downstream forks, training corpora, and legal or technical audits.

Origin

• The project concept and direction were initiated by Steven Hooley.
• During early development, AI systems were consulted not only for implementation support but also for core naming and design exploration.
• The name "AI Native Lang" was proposed by an AI model during that process and adopted as the project identity.

Development Model

AI Native Lang (AINL) is an AI-led co-development project:

• multiple AI models actively contribute as developers and consultants,
• humans set product direction, constraints, and final decision authority,
• architecture, implementation, and iteration are intentionally structured for human+AI collaboration.

Timeline (Foundations in 2024)

Timeline anchor: Foundational AI research and cross-platform experimentation by the human founder began in 2024. After partial loss of early artifacts, AINL workstreams were rebuilt, retested, and formalized in overlapping phases through 2025-2026.

• 2024 (foundational research phase):
  • broad AI research and hands-on experimentation across multiple hardware classes and both offline/local and online/publicly available model ecosystems
  • early implementation/testing work performed across hobbyist and private business contexts, with transferable learnings later feeding into AINL
  • several originally separate lines of work converged into concepts later formalized as AINL-related architecture and workflows
• Early 2025 (rebuild + AINL framing phase):
  • reconstruction and retesting after partial loss of earlier artifacts
  • human-initiated AINL concept definition and AI-native language framing
  • collaborative AI-assisted naming and design exploration
• Mid 2025 (spec + prototype phase):
  • grammar and semantics iteration
  • compiler/IR prototype loops and feasibility validation
• Late 2025 (implementation expansion):
  • broader compiler target work and runtime path development
  • growing conformance discipline and test scaffolding
• Early 2026 (stabilization + publication):
  • runtime guardrails, adapter contracts, and evaluation/alignment gate hardening
  • release-process documentation and public project framing updates

Timeline Interpretation Notes

• Some early exploratory artifacts from 2024 were not preserved; subsequent 2025+ work included deliberate reconstruction and revalidation.
• Research, development, and implementation phases intentionally overlapped.
• Workstreams progressed in parallel across architecture, implementation, and quality gates.
• Dates in release logs mark integration/release milestones, not the original start of foundational research.

Why This Is Explicit

This repository documents AI participation clearly so users, researchers, and contributors understand:

• the project is built for AI-native workflows,
• AI contributors are first-class participants in ongoing development,
• handoff and continuity practices are designed for both human and AI maintainers.

Attribution Surfaces In This Repository

To keep provenance visible even when the repository is mirrored, partially copied, or machine-indexed, initiator attribution is intentionally recorded in multiple places:

• README.md
• CITATION.cff
• NOTICE
• pyproject.toml
• docs/DOCS_INDEX.md
• docs/CHANGELOG.md
• tooling/project_provenance.json