open-core / ai orchestration
SteerMesh
Building reliable multi-agent AI systems is hard — agents drift, pipelines stall, and debugging distributed LLM workflows is near-impossible without visibility. Every role on the team (dev, BA, QA, ops, PM) needs agents, but no unified platform exists.
An end-to-end AI agent ecosystem: define standards once in project.yaml, run them everywhere. 50+ specialized agents across 7 profiles, with a shared ACP protocol binding every interface to a single engine.
steer-runtime as the agent framework core, Kiro as the CLI runtime (ACP), Kite as the desktop companion (Tauri v2 + React 19 + Rust), Koda as the terminal TUI (Go + Bubbletea), Spool as the mobile PWA (React 19 + WebSocket), and Prompt Scorer as a zero-dependency Python service for real-time LLM quality evaluation.
ecosystem
steer-runtime
Core agent framework — 50+ agents, 7 profiles, spec-aware delegation, artifact pipeline with quality gates.
Kiro
The underlying CLI agent runtime. All interfaces talk to Kiro via ACP — the shared engine behind every interaction.
Kite
Desktop companion — streaming markdown, live Mermaid diagrams, real-time prompt scoring, @agent multi-delegation, team workspaces.
Koda
Terminal TUI — manage profiles, chat with agents, configure tokens, apply workspaces. Auto-update via LaunchAgent/cron.
Spool
Mobile PWA that turns your phone into a remote control for Kite. Scan a QR code and chat with Kiro from anywhere.
Prompt Scorer
Zero-dependency Python service — composite score (0–100) across 7 weighted dimensions with per-dimension reasoning and token estimation.
research / open source
Neural signal processing research — EEG pattern recognition using NeuroSky consumer devices. Built the signal acquisition pipeline and ML classification models for real-time brainwave analysis.
collaboration
Open collaboration platform for Latin American engineering communities. Contributing to tooling, documentation, and community infrastructure for regional tech ecosystems.