ChatGPT vs. Logic: Why AI Code is Slower

Source: Dev.to

Round 1: The ChatGPT Approach

lst = [44,4,4,1,1,1,1,1,1,1,12,4,3,2,4,5,6,4,3,44,556,6,6,6,6,22,2,2,1]

# Step 1: Find lowest value manually
lowest = lst[0]
for num in lst:
    if num < lowest:
        lowest = num

# Step 2: Find all indexes of lowest value
result = {}
indexes = []
for i in range(len(lst)):
    if lst[i] == lowest:
        indexes.append(i)
result[lowest] = indexes
print(result)

Optimized Single‑Pass Approach

lst = [44, 4, 4, 1, 1, 1, 1, 1, 1, 1, 12, 4, 3, 2, 4, 5, 6, 4, 3, 44, 556, 6, 6, 6, 6, 22, 2, 2, 1]

final_dict = {}
temp = float("inf")
for i, v in enumerate(lst):
    if v < temp:
        temp = v
        final_dict.clear()
        final_dict[v] = [i]
    elif v == temp:
        final_dict[v].append(i)

print(final_dict)

Complexity and Short‑Circuit Effect

• O(N) Complexity – the list is traversed only once.
• Short‑Circuit Effect – after the minimum value (e.g., 1) is found, higher numbers are ignored for dictionary updates.

The 2026 Developer Verdict

In the age of AI, it’s easy to settle for “code that works.” High‑performance engineering asks whether a two‑loop solution can be reduced to a single pass.

Discussion: Do you prioritize step‑by‑step readability, or do you always aim for the single‑pass optimization?

Tags: python performance algorithms codingchallenge