Persistence is useful when it helps you learn. It is also reasonable to change or stop a project that no longer fits your evidence or circumstances.
Review three things.
Demand: What have potential customers actually done?
Feasibility: Can you deliver the outcome at a workable cost?
Fit: Does the work fit the time, energy, and resources you can commit?
Your next move
Write the strongest evidence for continuing and the strongest evidence against it. If one important question remains, set a limited experiment and a review date. If the constraints already rule it out, record what you learned and give yourself permission to choose differently.
Look more closely.
Also name the limit: the amount of time, money, or effort you can responsibly invest in this experiment. A boundary makes a checkpoint real. It helps you distinguish learning from repeating the same approach because stopping feels uncomfortable.
A working example
Before another round of work, write down the evidence you would need to continue. It might be a customer committing to a pilot, a delivery cost becoming workable, or enough protected time to run the next test. Use criteria relevant to your actual situation.
Questions for your notebook
- What evidence is strongest for continuing?
- What evidence is strongest against it?
- Is there one affordable test that could resolve the uncertainty?
- Does the project still fit what I want and can commit?
Keep the learning even if you stop.
Record the audience insight, the useful skill, the relationship, or the piece of work you would carry forward. Closing a project does not require dismissing everything it taught you. If you continue, write why; if you change direction, make the change explicit.
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