❓If AI generates code that works… why do we care what that code looks like?

❓𝗜𝗳 𝗔𝗜 𝗴𝗲𝗻𝗲𝗿𝗮𝘁𝗲𝘀 𝗰𝗼𝗱𝗲 𝘁𝗵𝗮𝘁 𝘄𝗼𝗿𝗸𝘀… 𝘄𝗵𝘆 𝗱𝗼 𝘄𝗲 𝗰𝗮𝗿𝗲 𝘄𝗵𝗮𝘁 𝘁𝗵𝗮𝘁 𝗰𝗼𝗱𝗲 𝗹𝗼𝗼𝗸𝘀 𝗹𝗶𝗸𝗲?

Let’s start with defining 𝗴𝗼𝗼𝗱 𝗰𝗼𝗱𝗲, or really what we should aim for, "good enough" code.

✅ Meets the functional requirements

✅ Meets the non-functional requirements (scalability, security, performance, resilience)

✅ Aligns to a coherent architecture

✅ Is testable, and proven by tests

✅ Is extensible so we’re not rewriting it in X months

These are your engineering goals and acceptance criteria, not code.

🔎 𝗡𝗼𝘄 𝘁𝗵𝗲 𝘂𝗻𝗰𝗼𝗺𝗳𝗼𝗿𝘁𝗮𝗯𝗹𝗲 𝗾𝘂𝗲𝘀𝘁𝗶𝗼𝗻: If AI produces code that satisfies all of that… why do you care what it looks like? Why do you even need to look at it?

Are these really objections to throw?

❌ It’s not how I’d structure it.

❌ I wouldn’t name it that.

❌ It doesn’t use the pattern I prefer.

❌ It’s not elegant.

Those are stylistic objections. Stylistic is subjective.

If a system demonstrably:

✅ Handles the load

✅ Survives failure

✅ Meets the security model

✅ Evolves without collapse

✅ Passes comprehensive tests

…what exactly is missing?

Because here’s what I keep hearing:

☠️ “AI can’t really code.”

☠️ “It just produces boilerplate.”

☠️ “I can write better code.”

☠️ “I spend more time fixing AI code.”

Maybe you can write nicer looking code. But that’s not the goal.

If you can define how it could be improved why didn't you ask for the code from AI that way? That's a missed requirement not an AI implementation issue unless merely stylistic.

The goal is to produce the simplest solution, as quickly as possible, that satisfies the defined requirements.

That’s what engineers are paid for.

❌ Not to showcase taste.

❌ Not to demonstrate stylistic preference.

❌ Not to optimise for elegance.

❌ Not to rewrite code just to be how they like it.

Engineers are paid to deliver systems that work, securely, scalable, reliably, within constraints defined by the business they operate in.

Engineering skill isn’t becoming less important. It’s moving upstream.

ℹ️ Defining clear constraints ℹ️ Designing robust architectures ℹ️ Specifying non-functional requirements precisely ℹ️ Designing verification strategies ℹ️ Setting guardrails that enforce quality

AI can generate the implementation that satisfies those constraints if engineers can define them.

🧠 𝗦𝗼 𝗵𝗲𝗿𝗲’𝘀 𝘁𝗵𝗲 𝗿𝗲𝗮𝗹 𝗾𝘂𝗲𝘀𝘁𝗶𝗼𝗻: If it works, scales, is secure, and is provably correct..

Why does the aesthetics of the code matter? Why do you even need to look at it?

And if your answer is, “Because I can write it better”

Better for the business? Or better for you? What makes your code better if it does the same thing?

#SoftwareEngineering #AI #Architecture #EngineeringLeadership #TechStrategy