Vi

Vis Pro – A Formula-Based Workout Program Editor

Hacker News

Vis Pro – A Formula-Based Workout Program Editor

Hey HN, About 5 years ago, I built a weightlifting app for 5/3/1 that got me on the front page of HN [0]. After that, life happened. I had kids and so decided to get a job and put that project on ice. Eventually I grew too disappointed with my job, and decided to try building something again. The biggest feedback I kept getting from users was simple: “Let me create my own programs.” That’s how Vis started. The initial idea was to create a B2B platform where gyms and trainers could build programs using formulas (e.g., percentages of 1RM) and reusable blocks instead of spreadsheets. I built what I still think is the best workout editor out there, but I quickly found out that B2B sales is hard (or maybe I just suck at it). It also just didn’t feel like a big enough sell for gyms. So I pivoted. I focused on the iOS app for a while [1], and now re-packaged the editor so individuals can use it directly. With Vis Pro, you can: - Define programs using formulas (e.g., 0.85 * SQUAT_1RM, or even better: RPE(8, SET_REPS) * SQUAT_1RM) - Build workouts by re-using pre-defined or even custom blocks - Share your programs and workouts with others The core idea is that programs are parametric instead of static. Change your 1RM and the entire program recalculates automatically. You can try it out without an account at https://vis.fitness/pro/try/create-program The whole thing is built with NextJS, using Chevrotain (surprisingly solid) for the formula engine. It's been super interesting using Codex since late Dec. It's been a huge force multiplier, enabling me to ship really cool features like formula autocomplete and syntax highlighting in a couple of hours. I'm used to reviewing a lot of code from my time at Google, so that hasn't been a problem, but it's interesting to feel that the review speed is now the limiting factor. Though the codebase would become unmaintainable real quick without that. The next step is building an MCP server to allow users to create programs using LLMs and have them show up directly in the editor (and your phone). Would love feedback, whether you even lift or not! [0] https://news.ycombinator.com/item?id=31508009 [1] https://apps.apple.com/us/app/vis-next-generation-workouts/i...

Share card

Actual performance

1points
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Indie HackersFits the IH revenue-focused audience · Strong signals: started, para, ios · Missing: supports, reddit linkedin, podcasting
96%96% 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: apple, mcp, google · Missing: mac, agents, macos
83%83% 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
67%67% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoStrong fit for a featured deal · Strong signals: platform, users · Missing: plus, intuitive, reviews
57%57% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: ios, apps, google · Missing: mobile apps, personal, entrepreneurs
48%48% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
19%19% 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.

Incorrect prediction on native model

Similar products

Bug Out
Bug Out39%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Substack-Powered Workout Program

Indie Hackers
My
My first recursive program in x8665%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

My first recursive program in x86

Hacker News2
I
I wrote a maze traversal program in Clojure63%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

I wrote a maze traversal program in Clojure

Hacker News91
My
My brother wrote this program from jail74%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

My brother wrote this program from jail

Hacker News48
Pr
Program Synthesis for Ruby61%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Program Synthesis for Ruby

Hacker News82
Pr
Program Microcontrollers from Your Headphone jack55%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Program Microcontrollers from Your Headphone jack

Hacker News107
LA
LAN-based drawing program in Lua (via Love2d)75%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

LAN-based drawing program in Lua (via Love2d)

Hacker News1
7m
7min Workout with Rdio39%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

7min Workout with Rdio

Hacker News76
ForgeSport
ForgeSport36%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Your workout program adapts itself every week automatically

Product Hunt+2
Lu
Luastatic – Build an executable from a Lua program76%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Luastatic – Build an executable from a Lua program

Hacker News44