I’m a solo dev building TigrimOSR, a Rust-native AI agent workspace for engineering and developer workflows.

The main problem I’m trying to solve is that agentic AI is still too random for serious engineering decisions. For design work, calculations, reports, code changes, or technical review, I don’t want agents just “vibing” through tasks. I want a more solid workflow: defined roles, structured steps, traceable tool use, observable progress, and outputs that can be reviewed before they affect real decisions. TigrimOSR is my attempt to build that kind of environment. It is built in Rust with egui as a self-contained desktop app. The goal is to combine chat, files, terminal, tasks, tools, and multi-agent orchestration in one UI, instead of spreading agent work across separate CLIs and web apps. Current direction/features include: Multi-agent swarms with YAML definitions Different orchestration modes for structured workflows Shared blackboard / agent communication Support for OpenAI, Anthropic, Gemini, DeepSeek, Kimi, Ollama, and OpenAI-compatible APIs Local CLI agents like Claude Code, Gemini CLI, and Codex MCP tools, Python execution, shell commands, and file read/write Headless Linux mode for heavier remote jobs Native desktop control and browser web UI Live monitoring of agent/tool progress The use case I care about most is engineering work where decisions need a clear process: design alternatives, calculation checks, code generation, document review, report writing, QA/QC, and technical reasoning. I want agents to behave more like a structured engineering team than a random chatbot. Still early and very much solo-dev built, but I’d really appreciate feedback from developers or engineers using agents for real work. What kind of workflow structure would make agents trustworthy enough for engineering design or technical decision-making?