shisa-ai/shisad

shisad is currently in its infancy with only 13 stars and no forks, making it a classic 'idea-stage' prototype. The core architectural pattern—decoupling the LLM's 'thought' from the system's 'action'—is the industry standard for production agents (often referred to as 'Human-in-the-loop' or 'Validator-in-the-loop'). While the 'security-first' branding is timely, the project lacks a technical moat or a unique primitive that isn't already being addressed by more mature infrastructure providers like E2B (sandboxed runtimes) or orchestration frameworks like LangGraph and CrewAI. The 'daemon' approach is a common pattern for local automation, but without a significant ecosystem of pre-built security policies or community traction, it is easily replicable. Frontier labs like OpenAI and Anthropic are increasingly building these safety guardrails directly into their platform APIs and desktop integrations, posing a severe threat to standalone security wrappers at the daemon level. Within 6 months, we expect OS-level agent runtimes (like Windows Copilot+ or Apple Intelligence) to provide similar execution isolation by default.