some rewriting

Author: masci

site/content/writing/the-coding-interview-in-2025.md

@@ -19,16 +19,17 @@ including this aspect into the hiring process is tricky.
 From what I see and am told, companies today use variations of these techniques for technical screening interviews:
 some prohibit AI completely, doing their best to prevent candidates from using it by asking them to share their full
 screen and narrate their thought process. Others explicitly permit AI, sometimes using interview tools with integrated
-assistants so the interviewer can watch the interaction unfold, or simply asking candidates to be transparent about how
-they use these tools.
+assistants so the interviewer can watch the interaction unfold, or simply asking candidates to be transparent if they
+use these tools.
 
-However, I believe that prohibiting AI in interviews is a flawed approach. First, getting used to AI tools can actually
+I believe that prohibiting AI in interviews is a flawed approach. First, getting used to AI tools can actually
 [make you slower](https://arxiv.org/abs/2506.08872) when they are taken away, which means you might lose strong
-candidates who simply lack practice coding without an assistant. Second, you really don't want to hire someone who has
-no idea how to use coding assistants; a good candidate should at least have an opinion on the matter. And finally,
-let's be honest, cheaters are always going to find a way to cheat.
+candidates who simply lack practice coding without an assistant. Second, you want to hire someone who either knows how
+to use coding assistants, or at least has an opinion about why they shouldn't be used. And finally, let's be honest,
+cheaters gonna cheat. But even when AI is permitted, during the interview it is often seen as a tool, and there's
+little to no focus on understanding how the candidate incorporated this tool into their engineering work.
 
-All things considered, I think the best approach is the opposite: **go all in on generative AI and see how the candidate navigates its quirks.**
+All things considered, I think the best approach is to **go all in on generative AI and see how the candidate navigates its quirks.**
 
 ## The interview blueprint
 
@@ -64,11 +65,12 @@ Start by asking if the candidate needs any clarification before moving to the ne
 ### Step 2: get to a working solution
 
 Any good coding assistant should be able to provide a working solution very quickly. What you're looking for here is
-how the candidate interacts with the tools. The problem is simple enough that some candidates may opt to code it
-manually, which is a perfectly good sign. If they do, you can shift the AI-coding evaluation to later steps.
+how the candidate interacts with the AI tools. The problem is simple enough that some candidates may opt to code it
+manually, which is perfectly fine and a good sign of a strong performer. If they do, you can shift the AI-coding
+evaluation later, during one of the subsequent steps.
 
-Chances are that the keywords "balanced parentheses" will skew both the human and the coding agent towards a stack-based
-solution:
+In this case, chances are that the keywords "balanced parentheses" will skew both the human and the coding agent
+towards a stack-based solution:
 
 ```python
 def is_balanced(word: str) -> bool:
@@ -97,7 +99,7 @@ to question its decisions. Start with these follow-up questions:
 - If the code doesn't use a stack, ask them if a stack would be better or worse.
 
 What to look for:
-- **Can the candidate refine the assistant's output?** Look for examples like adding or improving typing, or makingvariable names clearer.
+- **Can the candidate refine the assistant's output?** Look for examples like adding or improving typing, or making variable names clearer.
 - **Is the candidate able to iterate on the output?** See if the candidate is able to optimize the code and how.
 
 ### Step 4: produce the optimal solution
@@ -126,8 +128,7 @@ What to look for:
 
 ## Conclusion
 
-Embracing generative coding in the hiring process isn't just about passively adopting a new technology; it's about
-finding out how a candidate adapted to these new tools, shifting the focus from memorization to guided collaboration
-with an AI assistant and getting a clearer picture of their real-world skills. You’ll see if they can ask the right
-questions, critically evaluate a generated solution and refine it into an elegant, optimal product, which is something
-coding assistants have yet to prove they can do.
+Embracing generative coding in the hiring process isn't just about passively allowing the use a new technology; it's
+about finding out how a candidate adapted to these new tools and getting a clearer picture of their real-world skills.
+You’ll see if they can ask the right questions, critically evaluate a generated solution and refine it into an elegant,
+optimal product, which is something coding assistants have yet to prove they can do.