AI coding agents for side projects
Side projects are one of the places where AI coding agents make the most sense.
You don't necessarily need an AI coding tool every day. You might work on a project for a few hours, leave it for a week, then come back and continue where you stopped.
That makes the usual setup a little awkward. Paying for a monthly subscription can feel excessive, while setting up API keys and local models adds another layer of friction.
We built Clixad around this use case.
Clixad is a cloud-based AI coding agent that runs in the terminal. It can inspect an existing project, read files, make changes, run commands, test the result and fix errors based on what it finds.
Because the models run in the cloud, there is no need to run an LLM locally or have a high-end GPU. Users also don't need to bring their own API key.
The pricing model is designed around lighter usage too. Clixad provides free credits, with additional credits available through advertiser-funded offers, forms and surveys rather than requiring a monthly subscription.
We also made the five cheapest models free within their daily limits. That gives side-project builders a way to work with an actual coding agent without immediately paying for every interaction.
This is especially relevant for people who build small SaaS products, prototypes, personal tools or weekend projects and don't need the same amount of AI coding usage as a full-time developer.
AI coding agents don't have to be all-or-nothing tools where the choice is either an expensive subscription or setting everything up yourself. There is room for a model built around occasional project work too.
The hardest part of reviving an old side project is remembering why you stopped. I'd show someone reopening it, asking Clixad to inspect the code, make one change, and run tests.
That would resonate with developers who want progress without another monthly commitment.
This is great work — reminds me of some of the calls I've had to make building Xstream4K. What would you do differently if you started over?
Interesting—AI coding agents are most useful when they’re constrained enough to be boringly reliable.
A few things I’d focus on for side projects (and where I’ve seen agents either shine or get messy):
The agent should always produce a patch/diff first, not “just run and hope”.
If you don’t gate on tests, the agent will get you to a green check occasionally, but you’ll lose time debugging the “almost” cases.
For existing projects, the failure mode is usually “it saw too much / too little”.
Practical approach:
Xis the source of truth”).If the agent can do arbitrary shell commands, it’ll eventually do something that breaks the environment or changes unrelated stuff.
Good constraints:
test/typecheck/lint, maybegit diff.A lot of people judge agents by “it worked once”. For side project reality, you want benchmarks like:
If you don’t instrument these, you can’t tell whether improvements actually help or just look good in demos.
The best early wins I’ve seen aren’t “rewrite the whole app”.
They’re things like:
Those have clear boundaries and make evaluation straightforward.
---
Curious: what’s your current “happy path” task scope for the agent? (e.g., “small refactors”, “new feature in an existing module”, “tests generation”, etc.) And how do you handle cases where checks fail—do you auto-iterate, or do you stop and ask for a human decision?
The intermittent use observation is right and it has a consequence for the credit model. Somebody returning after a week has a narrow window of motivation, and that is exactly when you would be asking them to complete an offer or a survey to top up. That is the highest friction moment in the entire cycle. Credits that accrue quietly while they are away, or a small one off pack they can buy in ten seconds, both protect the return. Otherwise the pricing taxes precisely the behaviour you designed the product around, which is coming back after a gap.
Side projects sit quiet for days then spike for a few hours, so a monthly seat is a bad fit for that rhythm. The part I would check is memory across the gap. If the agent forgets which files you already decided to leave alone, you burn the cheap credits fixing its rewrite. Free low end models help until a bug needs the expensive one halfway through the session.