I’m building an app on a limited budget and need free AI tools for coding, debugging, UI design, testing, and marketing. I’ve tried a few options, but most have strict limits or require paid upgrades. Which free AI tools are genuinely useful for indie app developers?
Don’t build your workflow around five separate free tiers.
For coding and debugging, GitHub Copilot Free is useful for everyday completions, while ChatGPT Free works better for explaining errors, reviewing a small function, or suggesting an implementation. If cloud limits keep getting in your way and your computer has enough RAM, Continue with Ollama gives you a local setup without per-message quotas, though smaller local models are slower and less reliable on large codebases.
For UI work, Figma’s free plan has limited AI credits, while Penpot is a solid open-source alternative if you care more about unrestricted design files and developer-friendly layouts than automatic design generation. For testing, skip dedicated “AI testing” subscriptions at first. Have your coding assistant generate Playwright tests, then run and inspect them normally. For marketing, ChatGPT can draft store listings, onboarding text, and email variants, while Canva Free handles basic social graphics and includes a limited AI allowance. Keep secrets and customer data out of prompts, and never trust generated tests unless you have seen them fail when the app is intentionally broken.
Pick one feature from your backlog and run it through a fixed toolchain before installing a dozen assistants. My low-cost setup would be Gemini CLI for repo-level coding help, your normal linter and type checker for catching basic mistakes, Playwright plus axe-core for browser and accessibility tests, and Penpot for UI work. For quick mockups, Figma’s AI credits are fine, but I would save them for specific screens rather than repeatedly generating whole app concepts.
I slightly disagree with @0xwidget4 about avoiding several free tiers. Using separate tools can preserve your coding quota instead of wasting it on ad copy or image generation. The important distinction is that none of them should become required infrastructure. Your app should still be buildable, testable, and deployable when every AI limit is exhausted.
For marketing, any decent free chat assistant can rewrite store copy, emails, and release notes. Feed it actual support questions, search terms, or user comments rather than asking it to invent a target audience. That usually produces more useful copy than switching between five “marketing AI” products. Keep private repositories and customer data away from free cloud tools unless you have checked their current data-use settings.
Your laptop specs matter more than most free-tool lists admit. If you have enough memory, Ollama paired with Continue gives you a useful local coding assistant without a monthly quota, and your code can stay on your machine. The tradeoff is slower responses, weaker repo-wide reasoning, and some setup hassle. On a basic laptop, GitHub Copilot Free is probably the less frustrating option for completions and occasional debugging, though its monthly allowance is limited.
I would avoid hunting for a separate “AI testing” product. Have the assistant suggest edge cases and draft test files, then let deterministic tools execute them. AI-generated tests can be confidently wrong, especially when they mock away the bug. The same applies to UI generation: Penpot is a solid free workspace, but manually building a small component library will save more time than repeatedly generating screens.
To stretch free quotas, keep requests narrow. Give the assistant one failing test, the related function, and the expected behavior instead of dumping the entire repository into every chat. Save local or general chat models for store descriptions, release notes, and support replies. That setup is less flashy than having five specialized AI subscriptions, but it keeps working when a free tier changes its rules.
Create a throwaway feature branch and make every tool prove it can save you time there before giving it access to the real project. “Free” software gets surprisingly expensive when it produces three hours of cleanup and a component named FinalButtonNew2.
My shortlist would be Gemini Code Assist or Copilot Free for coding, whichever behaves better with your language and editor. Use it for small, reviewable changes: explain this stack trace, write the parser for this format, add validation to this endpoint. For debugging, require it to state the likely cause and suggest a way to reproduce the bug before generating a fix. Otherwise it tends to edit random nearby code until the error message gets bored and leaves.
For UI, Penpot is a sensible workspace, but I would use AI more as a critic than as a designer. Give a multimodal chat tool a screenshot and ask it to identify unclear hierarchy, cramped touch targets, inconsistent spacing, or confusing labels. That is often more useful than generating an entire interface that looks polished until you notice it has seven primary buttons and no loading state. Keep your actual components in Storybook if you are building for the web. A small, reusable component set will outlast whatever free design generator is popular this month.
Testing depends on the app. Playwright plus axe-core covers a lot of web testing. For a mobile app, Maestro is worth considering for readable UI flows. Let the assistant draft cases, but include boring failures such as expired sessions, empty results, interrupted requests, duplicate submissions, and denied permissions. Those are the screens users eventually find for you, usually in a one-star review. @devhub4503 is right that the execution layer should remain deterministic. The AI can propose tests, but your test runner decides whether anything works.
For marketing, save yourself the tour of twenty “AI growth” sites that are mostly the same model wearing different colors. A general chat assistant can turn your feature notes into store copy, release notes, onboarding text, FAQ answers, and several headline options. Canva Free is enough for basic graphics. The important input is real material from your app. Give it the actual benefit, audience, limitations, and screenshots. If you provide vague hype, it will return industrial quantities of vague hype.
The bigger filter is exportability. Keep generated code in Git, store design assets in formats you can move, and never let a free app builder become the only place your project can be edited or deployed. Free tiers change, products disappear, and quotas get “improved” in the traditional direction. AI output should be disposable assistance, not a dependency your app needs in order to compile.
The biggest quota is not the same as the best free tool. Compare assistants by how much cleanup they create. Give Copilot Free and Gemini Code Assist the same small task, such as fixing a failing test or adding validation, then keep whichever produces the clearer patch with fewer invented dependencies. A larger allowance is worthless if you spend the saved prompts repairing its code.
I would separate the stack by whether the output can be verified cheaply. Coding and debugging assistants are useful because Git, tests, linters, and type checks can catch mistakes. For UI, Penpot is a better free foundation than relying on generated mockups, since you retain editable designs and can build around real constraints. Use a multimodal assistant for screenshot criticism, but do not treat its visual opinion as an accessibility review.
Testing is where the comparison becomes easy: Playwright and axe-core cost nothing, produce repeatable results, and remain useful after an AI quota expires. Maestro fills a similar role for mobile UI flows. Let the assistant write a first draft, but manually add cases involving bad connections, stale data, repeated taps, permission denial, and interrupted sign-in. @matrixspark7531’s throwaway-branch suggestion makes sense here because you can deliberately break the feature and confirm that the generated test actually catches it.
For marketing, the differences between free chat assistants matter less. Use whichever still has quota to turn real feature notes and customer wording into store copy, FAQs, or email variants. Canva Free is enough for straightforward graphics. I would spend the evaluation time on coding tools instead, because a weak headline is easy to replace while a plausible-looking code change can quietly become part of the product.
Don’t install every free AI extension into your main editor and grant full repository access. Start with pasted, redacted snippets in a general chat tool, then enable repo indexing only after checking its data settings and excluding secrets, logs, and customer files.
If you’re on something niche like Rust, Elixir, or a less common mobile framework, half this advice shifts. The free assistants are noticeably stronger on JavaScript and Python than on anything with a smaller training footprint, so the ‘just pick whichever gives the cleaner patch’ comparison @j.collins suggested is smart, but rerun it every couple of months. Free tiers quietly swap the model behind the scenes, and the winner from your test in spring can be the worse one by summer without any announcement.
The context window is the thing nobody flagged directly. Keeping requests narrow isn’t only about stretching quota like @foxhq said, it’s that most free tiers cap how much you can paste before they truncate or choke. So you’re forced into small, focused prompts anyway. That actually lines up with good practice, but it means the ‘dump the repo in’ workflow people imagine isn’t even on the table for free.
Honestly I think marketing is getting more attention here than it deserves. Any free chat tool writes passable store copy in one sitting, and you’ll rewrite it after launch once you see what users actually search. I’d stop optimizing that part and put the saved effort into the boring failure cases everyone listed for testing. That’s where a free stack either holds up or quietly ships bugs.
Don’t assume free means your code stays yours. A few of these free tiers reserve the right to train on what you send, and the settings that turn that off aren’t always on by default or even available on the free plan. @capt_falcon already flagged the redaction habit, which is the right instinct, but I’d go further and actually read the data terms for whichever assistant you settle on before you point it at anything you plan to ship or sell. That matters more for a solo dev than for someone at a company with lawyers.
The thing nobody’s really pricing in here is your own review time. Everyone’s comparing quotas and patch quality, and @j.collins is right that a bigger allowance is useless if you clean up after it, but even a clean patch costs you attention. On a limited budget your scarcest resource isn’t prompts, it’s the hours you have to read every suggestion carefully enough to trust it. That’s the hidden tax on running four assistants at once. You end up context-switching between their quirks instead of building.
So my actual suggestion is pick one coding assistant and stick with it long enough to learn where it lies to you. You’ll ship faster knowing one tool’s failure modes than juggling five you half understand. I’d agree with @techbear5640works that marketing is soaking up too much of this thread. Any free chat tool handles store copy fine, and you rewrite it after launch anyway. Spend the saved energy on the boring test cases, because that’s the part that actually decides whether your free stack holds up.