There’s been a lot of noise about AI replacing jobs, but for indie hackers, it’s the opposite. AI is a force multiplier. When combined with the right scripts, it can handle the fuzzy parts of your workflow that are too complex for a simple ‘if this then that.’ Let’s talk about how to use it without losing your sanity.
First, identify the tasks that are almost automatable but have too many variables. For example, you might want to categorize support emails by urgency. A script can fetch emails, but deciding whether one is ‘urgent’ often requires reading context. That’s where a language model comes in. You can write a script that sends the email text to an AI API and asks it to pick a category. It’s not perfect, but it’s good enough for 80% of cases.
Another use case: generating a first draft of a response. Instead of writing each reply from scratch, you can have an AI draft a few options, and you just pick the best. This is especially handy for sales inquiries or onboarding emails. I’ve seen people cut their email time in half this way.
But here’s the thing: AI is not a replacement for a well-structured script. You still need deterministic logic for things like data validation or API calls. The sweet spot is a hybrid: a script handles the routine, and an AI handles the judgment calls. This gives you speed without losing control.
Let me give you a concrete example from my own workflow. I have a script that monitors my Stripe account for failed payments. It used to just log them, which meant I had to manually follow up. Now, the script triggers an AI to generate a gentle reminder email, personalized with the customer’s name and the product they bought. It then sends it via my email service. The result? A recovery rate that went from 10% to 30%, just by making the follow-up prompt and polite.
Of course, there are pitfalls. AI can hallucinate facts, so never let it write anything that could be harmful or misleading without review. Always set clear boundaries on what the AI is allowed to do. And watch your API costs — they can add up if you’re not careful. Set a budget and log usage.
To start, you don’t need to build a whole new system. Pick one task that you hate, and that has some element of ‘judgment.’ Write a script that pulls the necessary data, calls an AI API with a well-crafted prompt, and outputs the result. Test it on a handful of examples, and iterate.
There are also tools that make this easier. Zapier and Make.com already have AI integrations, and you can combine them with your scripts. But if you want full control, writing a little Python is often simpler than wrestling with a GUI.
In the end, AI-assisted automation isn’t about doing less work; it’s about doing the right work. It’s about taking the 20% of your day that’s repetitive and turning it into a five-minute review. That’s a win in my book. If you’re curious, our [AI Email Triage Script] in the library is a great starting point — it uses OpenAI’s API to categorize and draft replies, and it’s fully documented.