yohamta

MCP is a gateway protocol, not tool use.

Yes, as long as a senior SWE guides AI agents properly.

In Japan still many system integrator company that large corporation relies on continue using waterfall approach. They keep to out source a lot of engineering work for making design documents, manual testing, etc. They would keep to hire many middle class engineers.

As a Japanese in Tokyo, I didn't know that Ramens in other countries look so good.

Multiplayer agent harness is useful only when the context and AI output does not overwhelm the team space and works asynchronously and background. If you think about it, that could be just boring job scheduler, isn't it?

Anthropic SOTA model is a gift to human. Open AI model is so annoying. I alway feel like talking to intelligent insects,

I built Dagu, a simple workflow engine and lightweight alternative to Airflow.

Lately, I’ve been using it to automate my daily workflows with an AI agent harness like opencode. Dagu helps you manage local, private workflows. It gives you a flexible Kanban-style view, a declarative workflow language with validation, and the basics you expect from production workflow infrastructure: logs, retries, status tracking, and more.

The best part of having a workflow language is maintainability. Any AI agent can help create or debug your workflows. You can do something similar with plain Bash scripts, but Bash quickly becomes hard to debug and maintain.

Because Dagu is DAG-based, it automatically runs independent steps in parallel. Each step is validated and logged separately, which makes it much easier for an AI agent to understand what failed and fix it.

Give it a try!

exe.dev は大好きなプロジェクトです。単一の仮想マシン/ローカルマシンに全てを詰め込むアイデアが好きです。私は単一マシン上でのワークフローオーケストレーションの複雑性に関わる問題を解決するため Dagu.sh を開発しています。

Claude and Open AI seems to be trying not to be 'Just a model', but this is intrinsically problematic because model can be degraded and prices only goes up once they lock-in customers. It is increasingly important for anyone who are responsible of managing 'AI workflows' to keep the sovereignty about how you use AI models. This is why I'm super excited in building the local-first workflow orchestration software called "Dagu", that allows us to own your harness on your own. It's not only more cost-effective, but outcome is better as well because you have 100% full control. I think it's only matter of time that people notice they need to own their workflow orchestration on their own not relying on Anthropic, OpenAI, or Google.