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Building Kobako with AI: Will It Eventually Crash?

Last week I published Kobako: Letting Agents Safely Operate Rails, introducing the goals of the Kobako gem. Since then I’ve kept pushing development forward with Claude Code—but I quickly ran into a situation that demanded major changes. Is this simply the fate of developing with AI?

This is a question worth discussing: when using AI to assist development, is the problem that AI isn’t capable enough, or that the design we humans handed it was too poor?

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When Claude Code Runs for Hours

The Ralph Loop technique — a trick for making AI Coding Agents automatically repeat execution — was popular last year, but I didn’t trust whether it was safe enough or sufficiently stable.

A few months ago, Claude Code’s update introduced the /loop skill, which essentially uses Claude Code’s built-in Cron tool to repeat specific prompts at fixed intervals, achieving a similar effect. At least it’s safer and more controllable.

However, things are rarely that simple.

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From Agent to Agentic AI

Recently, due to work requirements, I needed to evaluate AI Agents and also ended up comparing them with Agentic AI. If you’re also evaluating or adopting AI agent-related technologies, these two concepts may look similar but are quite different.

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Should You Have Your Own Agent Skills?

I often see discussions like “this tool is amazing,” but after actually using another person’s Agent Skill, it usually doesn’t feel quite right, and the results don’t match expectations. On top of that, letting arbitrary people provide your Agent Skills is quite dangerous from a security perspective, since we authorize Agents to do many things—far more dangerous than regular software tools.

Beyond security, there are many other reasons why having your own set of Agent Skills is a better approach.

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Are Design Patterns Still Useful in the AI Era?

Have you noticed that AI-generated code often requires significant rewriting every time you integrate it? Since the launch of Coding Agents, there have been constant voices claiming that software engineers will be replaced. However, through my recent collaboration with colleagues, the overall situation still aligns with the reality that “professionals remain.”

Some might think that with Coding Agents, “there’s no need to learn software development,” but they fail to realize that much of advanced software development knowledge isn’t about “implementation” - it’s about “design” and “architecture.”

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AI Skills Worth Investing in 2026

In 2025, we experienced a year of rapid advancement in LLMs (Large Language Models). Tools in the form of AI Agents have become increasingly common, and Coding Agents for software development have matured to the point of becoming standard equipment, rather than just one of many means to quickly modify files.

However, for software engineers, I believe the most worthwhile investment in 2026 isn’t learning to use tools like Coding Agents, but rather developing more fundamental capabilities.

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Using Claude Code's Agent Feature Correctly

Have you seen Claude Code’s Sub-Agent feature and immediately wanted to design a bunch of them? Backend Agent, Frontend Agent, and so on—it feels like getting more powerful tools. But do you really need them?

During WebConf 2025, chatting with friends about this topic revealed that many people are still unfamiliar with when to use Sub-Agents. Two talks at the conference provided good entry points: ihower’s AI Agents Development and 91APP’s Chief Architect Andrew’s From Service to Agent.

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The Potential of Ruby's ri Command for Coding Agents

Recently, the Hono framework launched the Hono CLI tool, and I quickly created a Hono Plugin for Claude Code, adding Agent Skill support for querying documentation using Hono CLI.

At the same time, I realized that the ri (Ruby Information) command, which I rarely use, provides similar capabilities to the Hono CLI. Therefore, I created the Ruby Plugin ahead of schedule to provide the ri skill.