If you are new here, start with the articles below rather than scanning every recent post. This blog is less interested in announcing new tools than in the operational, security, and architectural questions that appear when a team puts AI and automation into a real system.
What this blog covers
AI agents and coding automation
AI coding tools are not just convenient autocomplete. Once they can call tools, change repositories, or trigger workflows, they become new actors in a delivery process. The useful questions are about permissions, review boundaries, audit trails, and failure modes.
Security and the open web
Automation changes who bears operational costs. The residential-proxy and scraper discussion is a useful example: identifying a request, limiting abuse, and protecting a small site should not make legitimate readers pay the price.
Backend operations and architecture
The preferred systems are not necessarily the flashiest ones. They are systems whose behavior can be explained, observed, recovered, and changed safely when something fails.
How to read an article here
| Question | What to look for |
|---|---|
| Is this needed by our team now? | Conditions for adoption and reasons not to adopt |
| Who can explain a failure? | Logs, permissions, rollback paths, and auditability |
| Does automation reduce or add risk? | Human review points and realistic failure modes |
| Can we reproduce the decision? | Sources, concrete procedures, and links to the evidence |
English editions are being added selectively. Korean remains the primary archive; use the language switcher when an English counterpart is available.
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