Refactoring A.I.-Generated Spaghetti Code: Lessons from a 20% Failure Rate

Debugging & Refactoring Spaghetti Code - The A.I Special 🤖

Brandon Lozano inherited a sales data API project that suffered from a sub-optimal 80% success rate due to heavy reliance on unvetted A.I. code generation. The system relied on PipeDream for hosting but lacked version control, proper dependency management, and configuration access.

Why This Matters

The technical reality of A.I.-driven development often results in spaghetti code when human oversight is absent, leading to critical failures in high-stakes environments like sales data processing. In this case, the lack of architectural planning resulted in nested loops and sequential API calls that crippled performance and reliability.

Relying solely on A.I. without deep domain knowledge creates a black box system where errors are difficult to isolate and fix. This case study highlights that while A.I. is a powerful tool for documentation and logic checking, the human engineer must remain the primary driver to ensure system integrity and prevent security vulnerabilities like SQL injection.

Key Insights

• The initial system maintained an ~80% success rate for critical sales data, which directly impacted marketing and sales strategy accuracy.
• A.I.-driven architecture resulted in over 50 data points being tracked through nested for loops and individual API calls instead of efficient batch processing.
• Pipedream’s feature of saving request payloads for 30 days enabled rapid debugging by allowing developers to replay exact failure events on demand.
• The original implementation contained textbook SQL injection vulnerabilities by using raw template literals for database queries instead of parameterized inputs.
• Refactoring verbose if/else chains into a CURRENCY_MAP lookup and using Promise.all for parallel data fetching significantly optimized execution.

Working Examples

The refactored EventHandler utilizing a connection pool, parallel HubSpot data fetching via Promise.all, and parameterized SQL queries.

import { Pool } from 'pg';
const pool = new Pool({
user: process.env.DB_USER,
host: process.env.DB_HOST,
database: process.env.DB_NAME,
password: process.env.DB_PASSWORD,
port: process.env.DB_PORT,
});
const CURRENCY_MAP = {
us: 'USD',
ca: 'CAD',
au: 'AUD',
};
export default async function EventHandler() {
try {
const orders = await fetchShopifyOrders();
const cleanedOrders = orders.map((order) => ({
orderNumber: order.details.orderNumber,
currency: CURRENCY_MAP[order.details.country] ?? 'USD',
price: order.details.discountPrice ?? order.details.price,
delivered: order.details.deliveredStatus === 'delivered',
hubspotId: null,
hubspotOwner: null,
}));
const hubspotResults = await Promise.all(
cleanedOrders.map((order) => fetchHubspotData(order.orderNumber))
);
const enrichedOrders = cleanedOrders.map((order, i) => ({
...order,
hubspotId: hubspotResults[i].id ?? null,
hubspotOwner: hubspotResults[i].dealOwner || null,
}));
const client = await pool.connect();
try {
const results = await Promise.all(
enrichedOrders.map((order) =>
client.query(
`INSERT INTO DEALS (orderNumber, currency, price, delivered, hubspotId, hubspotOwner)
VALUES ($1, $2, $3, $4, $5, $6)
RETURNING id`,
[order.orderNumber, order.currency, order.price, order.delivered, order.hubspotId, order.hubspotOwner]
)
)
);
return results.map((r) => r.rows[0].id);
} finally {
client.release();
}
} catch (error) {
console.error('EventHandler failed:', error);
throw error;
}
}

Practical Applications

• Use Case: Transitioning from sequential awaits to Promise.all in Node.js to parallelize external API calls and reduce total pipeline latency.
• Pitfall: Hardcoding database credentials and using template literals in SQL queries, which leads to security vulnerabilities and maintenance difficulties.
• Use Case: Implementing a shared database connection pool and reusing connections across batch inserts to prevent resource exhaustion and connection leakage.
• Pitfall: Relying on A.I. to drive development without manual code review, leading to runtime errors such as calling async functions without the await keyword.

References:

• https://dev.to/blocool/debugging-refactoring-spaghetti-code-the-ai-special-55be