// SOLVING THIS WITH AN AI ASSISTANT (2026)
If you are working through this problem with an AI coding assistant — Claude, ChatGPT, Cursor chat, Gemini, GitHub Copilot, Aider, or any agent — the goal isn’t to ask for the answer. It is to use the tool to understand the pattern. The prompt sequence I’d run:
The pattern matters more than the answer. If the agent just hands you optimized code, you’ve trained yourself to lose interviews.
There are n cities connected by m flights. Each flight starts from city u and arrives at v with a price w.
Now given all the cities and flights, together with starting city src and the destination dst, your task is to find the cheapest price from src to dst with up to k stops. If there is no such route, output -1.
Example 1: Input: n = 3, edges = [[0,1,100],[1,2,100],[0,2,500]] src = 0, dst = 2, k = 1 Output: 200
Explanation: The graph looks like this:
The cheapest price from city0to city2with at most 1 stop costs 200, as marked red in the picture. Solution:
class Solution {
public int findCheapestPrice(int n, int[][] flights, int src, int dst, int K) {
if(flights.length==0) return -1;
HashMap<Integer, List<int []>> graph = new HashMap<>();
for(int[] flight: flights){
if(!graph.containsKey(flight[0])){
graph.put(flight[0], new ArrayList<int[]>());
}
graph.get(flight[0]).add(new int[]{flight[1], flight[2]});
}
PriorityQueue<Node> q = new PriorityQueue<Node>((a,b) -> (a.cost - b.cost));
q.add(new Node(src, 0, -1));
while(!q.isEmpty()){
Node curr = q.poll();
if(curr.city == dst){
return curr.cost;
}
if(curr.stop<K){
List<int []> nexts = graph.getOrDefault(curr.city, new ArrayList<int[]>());
for(int[] next: nexts){
q.add(new Node(next[0], curr.cost+next[1], curr.stop+1));
}
}
}
return -1;
}
}
class Node {
int city;
int cost;
int stop;
public Node(int city, int cost, int stop){
this.city = city;
this.cost = cost;
this.stop = stop;
}
} Here is the video explanation:
For the AI-native engineering side of HackerHeap — building MCP servers, comparing agents (Claude Code, Cursor, Windsurf, Codex, Gemini, Copilot), and weekly working code — see the Friday Build newsletter and the MCP archive.
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