I

I spent 4 years bootstrapping a financial planning tool to 30k MAUs

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I spent 4 years bootstrapping a financial planning tool to 30k MAUs

Hey everyone! I'm back with an update on this post [0]. Last year, I quit my corporate job and went full-time on ProjectionLab, the long-term financial planning app I've been building for the past 4 years, which some of you may recognize. The decision to go all-in felt like a huge leap. But it was the right call, and it's been a good year. And without the HN community, it would not have happened. As I mentioned last time [0], the feedback on my original Show HN is THE reason I'm still here working on this. I'm really grateful for that. And I hope the way I’ve grown PL -- staying bootstrapped and focused on users -- resonates with the early supporters who helped to shape it. For now I'm still the only engineer, burning the candle at both ends, but luckily I'm not feeling burnt out myself! It's been a fun and memorable year: - 6,139 commits, 221,484 insertions, 116,255 deletions - Shared my story on the ChooseFI podcast [1] (one of the original sources of inspiration for this project) - Started building a team (2 team members for customer success, 1 leading growth & marketing) - Doubled our customer base - Took no external funding, keeping our interests as aligned with users as possible Okay, but what did I actually do since last time? [2] Here's a quick cross-section: - Compare mode upgrades to explore what-if scenarios overlaid on the same chart with visual deltas/diffs - Launched ProjectionLab for Employers [3]: offer PL as a benefit, or get your employer to pick up the tab - Major tech stack migrations: Vue 2 -> Vue 3, Vue CLI -> Vite, Vuetify 2 -> Vuetify 3, Vuex -> Pinia, Jest -> Vitest, Firebase Namespaced API -> Modular API, Vike + SSG for marketing site - Advanced visualization features (1-click-plot any metric, interactive event icons in charts, etc) - Improved tax estimation & tax analytics - Simultaneous editing on multiple devices - MFA support - Rebuilt the help center, added more educational content and YouTube tutorial videos - Made it possible to book a 1-on-1 session for educational/training purposes - Converted ~65% of the codebase from JavaScript to TypeScript - And more! [2] I never saw myself as an entrepreneur/founder type. But apparently I've now spent 4 years turning a side project into a real business. I couldn't have done it without the initial support from this community, and I'd love to hear what you think of the updates and where you'd like to see things go from here. --Kyle [0] https://news.ycombinator.com/item?id=36849502 [1] https://choosefi.com/podcast-episode/projectionlab-kyle-nola... [2] https://projectionlab.com/changelog [3] https://projectionlab.com/employers

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Indie HackersFits the IH revenue-focused audience · Strong signals: started, ios · Missing: supports, reddit linkedin, podcasting
94%94% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: user, new, visual · Missing: mac, agents, macos
75%75% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
60%60% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: ios, video, users · Missing: mobile apps, personal, entrepreneurs
44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive
32%32% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: growth, training, bootstrapped · Missing: arr, mrr, revenue
20%20% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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