Posted / Publication: LinkedIn Sonu Goswami / SaaS Content Writer | B2B Specialist | SaaS Product | B2B | SEO & Social Media Expert | Book Buff & Storyteller through Book Reviews
Day & Date: Thursday, October 9, 2025
Article Word Count: 308
Article Category: SaaS / AI Development / Tech Commentary
Article Excerpt / Description: A reality check on the current state of AI-assisted coding → why claims like “AI built my whole app” often overlook the human validation still required. This post breaks down why LLMs can’t yet run, debug, or validate code, and why true software engineering still depends on developer context and creativity.
Every week I see developers on **Reddit, Inc.** claiming, “AI built my whole app,” and similar posts on
**LinkedIn** touting AI’s coding powers.
Here’s the catch: most of that code still needs human validation. AI has no runtime awareness→ it doesn’t see what actually happens when code runs.
. Why: Large Language Models (LLMs) generate code based on patterns in their training data, not on actual program execution or feedback.
**** Even tools like JetBrains AI can’t read npm logs or ESLint output in their own console.
. Why: Without real I/O access, AI can’t react to terminal feedback, fix build errors, or validate execution.
Anthropic, the company behind Claude, openly admits:
“AI does not have the ability to run the code it generates—yet.”
. Why: Current models can only suggest code, not execute or debug it.
**** The only time AI code works out of the box is when the pattern already exists in thousands of tutorials and repos.