GTCode is the technical home of Ekewaka Lono: AI systems engineering, machine-learning research, implementation notes, and consulting work for teams that need systems to hold up outside the demo.
The current public site is focused on practical AI architecture, model evaluation, agent workflows, software reliability, and research frameworks for structured reasoning.
Work
- AI consulting for production architecture, delivery support, model evaluation, agentic workflows, data pipelines, and operational reliability.
- Technical articles on AI systems, engineering practice, interpretability, computational investigation, and applied research.
- Guides and research notes for CNS / GCTS work, structured narrative objects, evidence modeling, and implementation experiments.
- Repositories covering software projects, AI tooling, and system prototypes.
- AI research news and AI security news for curated technical monitoring.
Consulting
GTCode helps teams move from prototype to maintainable system. The work is usually at the architecture-and-delivery layer: choosing boundaries, building evaluation loops, shaping retrieval and agent workflows, hardening data paths, and making the system observable enough to debug.
For professional inquiries, use [email protected].
Research Direction
The research track centers on structured reasoning under incomplete records: how models represent claims, conflict, evidence state, uncertainty, and synthesis. The goal is not just fluent output, but traceable reasoning that can be inspected, revised, and challenged.
Start with the articles, guides, or consulting brief.