When people talk about leaving their agents to run overnight, what are those agents actually doing? The limited utility I've had using agent-supported software development requires a significant amount of hand holding, maybe because I'm in an industry with limited externally available examples to build am model off of (though all of the specifications are public, I've yet to see an agent build an appropriate implementation).
So it's much more transactional...I ask, it does something (usually within seconds), I correct, it iterates again...
What sort of tasks are people putting these agents to? How are people running 'multiple' of these agents? What am I missing here?
Hope it helps!
Getting AI to generate valid mermaid diagrams on scale extremely hard. With maid i'm hitting 100% accuracy.
Maid is basically built from scratch mermaid parser, without any dependnecies, which knows how to auto-fix common AI slop diagramming issues.
(mcp auth is terrible btw)
A2A is for communication between the agents. MCP is how agent communicate with its tools.
Important aspect of A2A, is that it has a notion of tasks, task rediness, and etc. E.g. you can give it a task and expect completely in few days, and get notified via webhook or polling it.
For the end users for sure A2A will cause a big confusing, and can replace a lot of current MCP usage.
I'm building Probe https://probeai.dev/ for a while now, and this this docs-mcp project is showcase of its capable. Giving you a local semantic search over any codebase or docs without indexing.
Feel free to ask any questions!