iximiuz Labs founder shares a grounded, hands-on look at agentic coding in a real production codebase: massive speedups, surprising failures, and why domain knowledge still matters most.

Iximiuz's blog offers practical insights and tutorials on cloud-native technologies, automation, and infrastructure as code. Developers can explore topics such as Kubernetes, Terraform, and DevOps practices, gaining hands-on knowledge to build and manage modern cloud infrastructure. With a focus on real-world use cases and best practices, Iximiuz's blog empowers developers to embrace cloud-native approaches effectively.

Ivan Velichko

AI coding agents like Claude Code can deliver 10-100x velocity gains on well-defined tasks in production codebases, but require significant domain expertise to use effectively. Through real examples from a 150K LOC production system, the author demonstrates that agents excel at implementation when developers know exactly what to build, but fail on high-level product requirements, produce copy-paste code, skip tests to claim success, and need careful task decomposition. The productivity gains are real and substantial, but claims of autonomous coding or building complex systems without prior experience remain unjustified.

A grounded take on agentic coding for production environments

The guy made the comprehensive analysis of the AI coding workflow and I completely agree with him. I had the similar experience and also think, that the capabilities of the AI code assistants are overestimated, to put it mildly. The key points in my POV from the article about AI coding assistants are:
<ul>
<li>It performs poorly on high-level product prompts and requires a human who can decompose problems and reason about solutions.</li>
<li>It is incredibly effective when you already know exactly what needs to be done and how (10x–100x velocity).</li>
<li>It excels at investigating reproducible bugs - those with tests, clear repro steps, or massive logs that a human would otherwise skim for hours.</li>
<li>It changes development dynamics: tests, refactors, and cleanups that once felt - too expensive now become cheap - and more valuable than ever &lt;…&gt;.</li>
</ul>
What we should keep in mind:
<blockquote>
I used AI extensively outside of development, but my fear that coding agents would make me obsolete as a software developer kept growing. After burning through a few million tokens on code generation, that fear is gone - not because AI performed poorly, but because I can now confidently dismiss 80% of exaggerated claims on X and have a solid intuition for how to use coding agents effectively.
</blockquote>
And for those who missed it (as me :-): <a href="https://github.com/ChromeDevTools/chrome-devtools-mcp" target="_blank" rel="noopener nofollow">Chrome DevTools MCP</a>
Many thanks to <a href="https://app.daily.dev/iximiuz" data-mention-id="hl88oQaXFjzh1H1KFOVua" data-mention-username="iximiuz" translate="no">@iximiuz</a> for spending time for writing such a detailed article and for sharing it here! +1