Coding with AI without breaking the bank

Last updated: 2025-08-11

The subscription trap

After GitHub Copilot raised their prices and I started seeing my monthly tool costs approach $150, I realized I had a problem. Between various AI coding assistants, premium ChatGPT, and specialized development tools, I was spending more on subscriptions than my coffee addiction. So I decided to see how productive I could be with minimal spending. Turns out, pretty damn productive.

My current budget setup

Here's what I actually pay for these days:

• Claude API access (~$8/month): Pay-per-use pricing that scales with my actual needs. During busy months I might hit $15, but light months cost almost nothing.
• ChatGPT Plus ($20/month): My one "premium" subscription. The GPT-4 access is worth it for complex debugging and architecture discussions.
• Everything else: Free

Free tools that get the job done

The free tier ecosystem has improved dramatically over the past year:

• Codeium: Legitimately free autocomplete that works surprisingly well. Installation is straightforward and it doesn't nag you to upgrade constantly.
• Continue.dev: Open-source coding assistant that works with any API provider. I connect it to my Claude API for custom workflows.
• Cursor (free tier): Limited monthly usage but excellent for complex refactoring tasks when you need something more powerful than basic autocomplete.
• Local models via Ollama: Code Llama and Starcoder run locally for privacy-sensitive projects. Slower than cloud models but completely free after setup.

Strategic usage patterns

The key to staying under budget is being intentional about when to use expensive vs. free tools:

Free tools for routine work

Basic autocomplete, simple refactoring, and boilerplate generation work fine with free alternatives. I use Codeium for probably 70% of my AI-assisted coding – function completions, variable suggestions, basic patterns I've written hundreds of times before.

Premium tools for complex problems

Architecture decisions, debugging tricky issues, and understanding large codebases – this is where I break out ChatGPT Plus or make API calls to Claude. The quality difference is noticeable for complex reasoning tasks.

Local models for sensitive work

Client projects with NDAs or personal projects where I don't want code leaving my machine. Local models are slower but adequate for basic assistance without any privacy concerns.

The API pricing advantage

Most developers don't realize how much cheaper API access can be compared to subscriptions. My Claude API usage typically costs $5-12 monthly, even with heavy usage. Compare that to Cursor Pro at $20/month or other premium subscriptions.

The catch is you need to be mindful about usage. I've learned to batch questions, be specific in my prompts, and avoid using expensive models for simple tasks. But this constraint actually makes me a better prompter – I think more carefully about what I'm asking.

What I've learned to avoid

After trying various budget approaches, here's what doesn't work well:

• Relying only on free tiers: The usage limits are too restrictive for professional development. You need at least one reliable paid option.
• Using free tools for everything: Quality matters for complex problems. Spending 2 hours debugging something that GPT-4 could solve in 5 minutes is false economy.
• Ignoring local options: Setting up local models takes time initially, but they're incredibly useful for certain workflows and completely free to run.
• Not tracking usage: API costs can creep up if you're not monitoring them. I check my usage weekly.

The productivity question

Am I less productive than when I had all the premium subscriptions? Honestly, not really. The constraint forces me to be more intentional about when I need AI assistance versus when I can solve problems myself.

I've noticed that having unlimited access to AI tools can make you lazier. When there's a cost (even a small one), you think more carefully about problems and often discover you can solve them without assistance. This has actually made me a better developer in some ways.

Getting started on a budget

If you want to try this approach:

1. Start with one free tool: Install Codeium and use it for a week. See if basic autocomplete meets 80% of your needs.
2. Add one premium option: Either ChatGPT Plus for chat-based assistance, or Claude API access for more flexible usage.
3. Track your usage: Set up billing alerts and monitor what you're actually using vs. paying for.
4. Experiment with local models: Install Ollama and try Code Llama for privacy-sensitive work.
5. Optimize over time: Adjust your tool mix based on actual usage patterns, not theoretical needs.

When this approach makes sense

This budget-conscious setup works well if you're:

• A freelancer or solo developer paying your own tool costs
• Working on personal projects where costs matter
• Just getting started and want to experiment without major financial commitment
• Interested in learning to use AI tools strategically rather than as a crutch

It's probably not ideal if your company pays for tools anyway, or if you're working on time-sensitive projects where the premium features would genuinely speed you up.

The real lesson

Effective AI-assisted development isn't about having access to every premium feature. It's about matching the right tool to the right task and being strategic about when you need AI assistance versus when you can work independently.

I spend about $30/month total on AI tools now, down from $150+, and I'm roughly as productive. The difference is I'm more intentional about how and when I use these tools, which has made me both a better developer and a better prompter.