Best free AI coding assistant for a solo developer

Hey folks, I've been deep in the trenches lately trying to automate a pretty complex multi-service workflow, and I've been leaning heavily on AI coding assistants to speed up the boilerplate. The promise is huge for a solo dev, right? One set of hands, but with a "junior partner" to handle the tedious bits.

But I've hit a wall that's more common than I'd like to admit, especially when using the free tiers. I was working on a simple integration between Airtable and Google Sheets using Make (formerly Integamo). I needed to format dates in a specific ISO-like way for an API call in between. I asked the assistant (I'll keep it generic, but you know the usual suspects): "Generate JavaScript code to convert a date string like 'April 15, 2023' to '2023-04-15T00:00:00.000Z'."

Here's what I got back:
```javascript
function formatDate(dateString) {
const date = new Date(dateString);
return date.toISOString();
}
```

Looks clean, right? **This is where it fails.** The prompt `new Date('April 15, 2023')` has famously inconsistent behavior across different JavaScript engines (Node vs. various browsers). It *might* work in some contexts, but it's a parsing landmine, especially in a cloud automation tool which could run on any Node version. It's a silent, non-throwing error waiting to happen.

The **correct, reproducible answer** needs to handle the parsing explicitly:
```javascript
function formatDate(dateString) {
// Parse the specific "Month DD, YYYY" format
const months = {
January: 0, February: 1, March: 2, April: 3, May: 4, June: 5,
July: 6, August: 7, September: 8, October: 9, November: 10, December: 11
};
const parts = dateString.replace(',', '').split(' ');
const year = parseInt(parts[2], 10);
const month = months[parts[0]];
const day = parseInt(parts[1], 10);

// Construct the date in UTC to avoid timezone shifts
const date = new Date(Date.UTC(year, month, day, 0, 0, 0, 0));
return date.toISOString(); // Now this is reliable
}
```

The failure here isn't just a bug—it's a **hallucination of robustness**. The assistant gave me code that *looks* correct for the example input but ignores a critical, well-known cross-environment gotcha in date parsing. For a solo dev relying on this to build a backend workflow, this could lead to data corruption that's hard to trace.

My takeaway? Free AI assistants are fantastic for generating generic structure or reminding you of syntax, but they absolutely **fail** at edge-case and environment-specific reasoning. They'll often give you the *most common* answer from their training, not the *most correct* one for a production, multi-platform integration.

Have you run into similar "correct-looking but dangerously fragile" code from AI assistants, especially around API integrations or data formatting? What's your process for vetting their output?

-- Ian