When should you give up on a project that doesn't work?
Side projects that stall or “don’t work” often raise a harder question than the technical challenges themselves: when to stop pushing and when to simply put them back on the shelf. Commenters argue that many unfinished projects are still valuable as learning tools, prototypes, or future building blocks, and that abandoning something can be healthy when it stops being fun, stops teaching you anything, or consistently fails basic tests with real users. A recurring theme is to define clear hypotheses and short, explicit success criteria upfront—so that ending a project becomes an informed choice about opportunity cost rather than a vague sense of personal failure.
Attitudes Toward “Giving Up”
- Many reject the phrase “give up”; they prefer “put on the shelf” or “on hold.”
- Projects can cycle: work → pause → revisit months/years later.
- Others argue it’s healthy to explicitly stop and move on, to avoid sunk-cost traps.
Value of Unfinished and Side Projects
- Unfinished work is framed as learning, experimentation, and joy, not failure.
- Small “scrappy” projects often seed later tools, libraries, or businesses.
- Several compare them to sketches in art; they build competence and confidence for larger efforts.
Testing Ideas and Hypotheses
- Distinguish user/market hypotheses (“is this fun/useful?”) from technical ones (“can this be automated?”).
- Suggested tactics:
- Fake or manually-curated prototypes in small domains.
- Time-boxed frameworks (e.g., 2 hours PoC → 2 days prototype → 2 weeks MVP, with exit points).
- Set explicit success metrics and “kill thresholds” in advance.
Feedback on the Wikipedia/Map Project
- Many liked the prototype and found nearby places of interest; they question calling it a failure.
- Main critique: ranking by pageviews surfaces sensational or irrelevant articles over local landmarks.
- Suggestions: better categorization (landmarks vs cities vs events), recency weighting, and clearer user personas (tourists vs locals).
- Some propose using ML/LLMs for relevance filtering; others note that preprocessing the entire corpus may be required.
When to Stop a Project
- Common criteria:
- It becomes a burden or “fake productivity” (tweaking infra instead of core problem).
- You’re no longer learning.
- Opportunity cost: it blocks more promising work.
- Clear, predefined goals or metrics are not met.
- Counterpoint: some argue persistence can pay off years later, and regret past abandonments.
Psychological and Emotional Factors
- Perfectionism and overfocus on polish are seen as major momentum killers.
- Some emphasize fun and intrinsic interest as primary guides, especially for non-commercial projects.
- Others highlight the tension between doing projects for joy vs chasing commercial success or “escape from 9–5.”