Exploring governed task execution beyond interactive agent loops

[BonifaceAlexander]

Hi folks 👋

While working with Gemini-based agents, I kept running into a recurring pattern:
excellent reasoning and tool invocation, but fragile execution once workflows
become multi-step, long-running, or require governance.

Interactive agent loops and CLIs work very well for exploration and
human-in-the-loop usage, but they intentionally don’t address concerns like:

• durable task state
• pause / resume and recovery
• approval and policy enforcement
• auditability of actions taken by the agent

This isn’t a criticism of those tools — it’s a scope boundary. An interactive
agent loop is not the same thing as an execution runtime, in the same way a
shell script isn’t a workflow engine.

To explore this gap, I built Taskcraft Runtime, an open-source, Gemini-first
execution runtime focused on governed, resumable task execution.
It’s intended as a reference implementation of the execution layer that
agent frameworks and CLIs sit on top of — not a replacement for them.

• Repo (v0.1.0): https://github.com/BonifaceAlexander/taskcraft-runtime
• Background write-up: https://dev.to/boniface_alexander/why-ai-agents-fail-in-production-without-an-execution-runtime-1ggi

I’m curious how others in the community are thinking about durability,
retries, and governance for Gemini-powered agent workflows today.
Are these concerns being handled externally, or deliberately left to
downstream systems?

[BonifaceAlexander]

Hi @gundermanc , can you check the above and let me know if would add value, all maintainer suggestion would be helpful to make it more helpful and relevant contribution, Thank you.