Vibe Coding Left Me With Too Many Side Projects
“Vibe coding left me with too many side projects, so I built one more” is a playful way to describe a familiar problem: coding tools that make prototypes quick can also make it tempting to start more projects than you can finish. The extra project is most useful when it helps organize, prioritize, or retire the others—not when it becomes another open-ended idea.
Why quick coding can multiply projects
Vibe coding generally means building software by describing what you want in ordinary language and iterating on generated code, often with an AI coding assistant. The phrase is informal rather than a precise software-development method. It usually emphasizes a conversational, exploratory workflow: ask for a feature, inspect the result, try it, and request changes.
That workflow can lower the friction of getting from idea to visible prototype. A small personal dashboard, a habit tracker, or a utility for renaming files may seem approachable when the first version can be assembled quickly. But producing a demo is not the same as delivering a dependable tool. Projects still need decisions about data, error handling, accessibility, testing, deployment, updates, and whether anyone actually wants to use them.
When the cost of starting feels low, ideas accumulate. A person might have a half-built recipe organizer, a browser-based reading list, and a weekend game prototype, each with just enough progress to feel worth returning to. The joke in the question is that the proposed solution to too many projects is, predictably, another project.
What the “one more” project could do
A useful meta-project can make the existing portfolio visible and help turn vague intentions into decisions. It does not need to be an elaborate project-management platform. A plain list or a small local app may be enough to record what each project is for, what state it is in, and what would count as a meaningful next step.
- Inventory: Give every project a name, a one-sentence purpose, and a link to its files or repository.
- Status: Use a few clear states, such as idea, active, paused, shipped, and archived.
- Next action: Write one concrete task, such as “add an export button,” rather than “make the app better.”
- Decision date: Set a point to review paused work instead of letting it remain indefinitely active in your mind.
- Definition of done: Specify the smallest outcome that would make the project useful, such as a working personal prototype or a shareable first release.
The tracker should reduce overhead. If maintaining it takes more effort than reviewing the projects themselves, a text file, spreadsheet, or issue list is likely a better fit than a custom application.
How to decide what deserves attention
Project selection is less about finding the objectively best idea than choosing what fits your time, motivation, and purpose now. A quick score can help compare options, but it should prompt judgment rather than pretend to measure creativity precisely.
For each project, consider the problem it solves, whether you or another person will use it, how much work remains before it becomes useful, and whether it teaches you something you care about. A tiny tool you need every week may be more valuable than a polished concept with no clear audience. Conversely, a playful experiment can be worth doing if learning is the goal.
- List every project, including ideas that have not been started.
- Choose one primary goal for the next few weeks: learning, personal usefulness, sharing, or exploration.
- Estimate the smallest useful version of each active candidate.
- Pick one project to advance and explicitly pause or archive the rest.
- Review the choice after a defined interval, rather than switching whenever a new idea appears.
Keeping multiple projects is not automatically a mistake. Some people use small experiments to explore different interests. The problem is usually unintentional commitment: treating every prototype as a future product and feeling obliged to complete all of them.
From prototype to something dependable
Generated code can make a first draft easier to produce, but the person building the software still needs to understand what it does and check whether it works. An attractive interface does not prove that the underlying behavior is correct. A feature that works for one sample input may fail on empty data, unusual characters, large files, or interrupted network connections.
Before sharing a project or relying on it, identify its important paths and test them deliberately. For a note-taking tool, for instance, check creating, editing, saving, reopening, and deleting a note. If data matters, find out where it is stored, how it can be exported, and what happens if storage fails. Avoid putting passwords, API keys, or private information into code or prompts without understanding how the tools handle them.
It is also worth reading changes instead of accepting them blindly. Ask for explanations of unfamiliar code, review the files being changed, and use version control or another backup so you can undo a bad edit. For a project used by others, test accessibility basics, document limitations, and make clear whether it is a prototype or a maintained service.
Common traps and practical limits
One common misconception is that fast code generation removes the hard parts of software development. It can speed up drafting, but requirements, debugging, security, and maintenance remain. Another trap is feature creep: asking for one more improvement each time can turn a small project into a permanent work in progress.
- Building the tracker instead of making a decision: Start with a simple list before adding dashboards, notifications, or automation.
- Confusing activity with progress: A busy stream of prompts is not necessarily closer to a usable result.
- Ignoring maintenance: A project that depends on external services or libraries may need updates even after it is “done.”
- Starting from novelty alone: A new idea can feel exciting because it is new, not because it matters more than current work.
- Overlooking ownership and data: Know where project files and user data live, and keep copies of anything you cannot afford to lose.
For a private learning exercise, a rough prototype may be perfectly adequate. For software handling other people’s data or supporting an important task, the standard should be higher. The appropriate level of testing and review depends on the consequences of failure.
Frequently Asked Questions
What does “vibe coding” mean?
It is an informal term for creating or changing software through natural-language prompts and iterative code generation. It describes a style of working, not a guarantee that the result is correct or production-ready.
Is it bad to have too many side projects?
Not necessarily. Side projects can be useful for learning and play. They become burdensome when you feel responsible for finishing every idea or cannot make time for the projects that matter most.
How many side projects should I work on at once?
There is no universal number. A practical limit is the number you can make real progress on with the time you have. Many people find it easier to keep one main project active and treat other ideas as a backlog.
Should I build an app to manage my projects?
Only if building it serves a purpose beyond avoiding the decision of what to do next. Start with a document or spreadsheet; make a custom tool when a repeated need is clear.
How do I know when to abandon a side project?
Pause or archive it if its purpose is no longer relevant, you cannot identify a useful next step, or another project is a better fit. You can preserve the code and notes without promising to resume it.
Can AI-generated code be trusted?
It should be reviewed and tested like other code. Generated output can contain bugs, misunderstand requirements, or introduce unsafe patterns, so check important behavior before relying on or sharing it.
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