@tibo_maker asked on X
What Founder Success Patterns Stand Out the Most?
53 responses analyzed
The biggest takeaway from a recent Twitter poll on founder success patterns is that people find the analysis "insightful." Tibo Maker (@tibo_maker) analyzed 129 Starter Story interviews to identify 19 success patterns and asked for feedback. Here's how the votes shook out:
| Response | Votes | Conviction (๐ฅ/๐/๐ด) |
|---|---|---|
| It is insightful. | 9 | 0/8/1 |
| The work is a masterpiece. | 4 | 3/1/0 |
| The analysis is a major dataset and valuable. | 2 | 0/2/0 |
| The presentation is easy to digest. | 2 | 0/1/1 |
| A founder filter should be added. | 2 | 0/2/0 |
| More real cases explaining the practice would be beneficial. | 2 | 0/2/0 |
| Failure patterns are more consistent than success patterns. | 1 | 0/1/0 |
| The 'Ask the Advisor' aspect is useful. | 1 | 0/1/0 |
| The analysis would have saved time and effort. | 1 | 0/1/0 |
| Execution is still the most important factor. | 1 | 0/1/0 |
| It would be useful to filter the data by year. | 1 | 0/1/0 |
| The approach is simple and effective. | 1 | 0/1/0 |
| "Validate before building" and "niche down" are essentially the same. | 1 | 0/1/0 |
| Survivorship bias is a concern. | 1 | 0/1/0 |
| An email capture should be added to access the information. | 1 | 0/1/0 |
| The organized format is helpful. | 1 | 0/1/0 |
| The value lies in the founders' stories, not just conclusions. | 1 | 0/1/0 |
| The AI automation insight is notable. | 1 | 0/1/0 |
| The time-stamped video mentions are appreciated. | 1 | 0/1/0 |
| The UI is clean. | 1 | 0/1/0 |
Some interesting replies included:
- @aspidoff: "dude this is major dataset, thank you"
- @Amy0xFF: "Interesting that failure patterns are more consistent than success patterns across founders. Everyone fails differently until they find th..."
- @dudufolio: "U should add a email captur to access this , its too good"
Analysis
While "insightful" received the most votes, the "masterpiece" responses showed the strongest conviction, with more passionate supporters, so maybe it resonated more deeply with a smaller group. Several people suggested ways to filter the data, indicating a desire to dig deeper into the patterns. Overall, the reception seems positive, with actionable feedback for improvement. The dataset seems valuable, the presentation is easy to digest and the advice would have saved people time and effort.
This exercise proves that sharing your work early and asking for feedback is a recipe for success.
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