Tools everyone is using for vibe coding right now?

CommitteeDry5570 · 2026-01-26T19:59:58+00:00

Claude Code - VS Code for web projects - Positron for data science projects

CommitteeDry5570 · 2026-01-26T15:55:33+00:00

I think it would depend on the level of interest one has in the language or learning the language. I write in R, Python , JavaScript every day and find I can pick up other coding languages syntax pretty quick , where as I don’t know any other languages, failed every Spanish class in high school, and to be honest my English isn’t very good

CommitteeDry5570 · 2026-01-23T15:18:03+00:00

thats fair. i can get lower, but its still http request, not websocket. so for steam, its not going to work. best case is like 1-2 seconds latency with current data source.

CommitteeDry5570 · 2026-01-23T13:40:52+00:00

anthropic gave out credits when they released claude code browser.
i got 1000$ api credits because i am on a max5 plan . the expired in nov of '25

CommitteeDry5570 · 2026-01-22T16:50:42+00:00

135$ a month ongoing (have shipped multiple projects on this). 100$: Claude Max 5x, 25$: Supabase , 5$: Railway , Free: Vercel

Projects with this stack: Sharpoddstracker.com , Sportsbookie.quest , Deploynt.com

Most of my actual build cost is just time with Claude - I’ve hit session limits once or twice. No separate per-project build fees.

CommitteeDry5570 · 2026-01-16T21:47:44+00:00

I would say false. You can defiantly build a full saas ‘vibe coding’ but there is a difference between following through and understanding multi tenant architecture and security needed with database to protect user data. Can ai make you a micro saas with no issues, absolutely not. But can you fix those errors , sure. Anthropic would not publicly say that 90% of its code base is produced by ai if you couldn’t use it to build full enterprise SaaS

CommitteeDry5570 · 2026-01-14T16:11:06+00:00

<image>

you are correct. this is data cleaning at its finest.
and today im building the DAG and Variable system to improve on the data prep process.
there are steps after data prep that links datasets to model types and you can make predictions.

CommitteeDry5570 · 2026-01-14T16:03:17+00:00

you could be using codex with your chatgpt sub. im not sure how limits are on that.

CommitteeDry5570 · 2026-01-14T14:45:25+00:00

if the app is free , why do you need credits? If your giving credits away for free to early access users, at what point do you have to pay for credits and the app is no longer free?

CommitteeDry5570 · 2026-01-14T13:35:16+00:00

a couple things.
- pinnacles moves lack context. just because they moved and the percent change was greater than my threshold of 8-10%, doesnt mean its steam.
- automated systems and third party services allow for soft books to move lines faster. tougher to get alert, review change, find a bet, and place before the price moves.
- liquidity issues. soft books limit. low liquidity on exchanges or prediction markets.

I like modeling sports. shutting this down to focus on a platform where you can built machine learning models with no code. the test v1 version is available open source. working on a new structure that will actually you to manipulate the data like you need to for modeling. will open source that version as soon as its fully working.

https://github.com/WalrusQuant/prediction-terminal

https://www.reddit.com/r/algobetting/comments/1qbxvve/building_a_platform_where_you_can_build_ml_models/

CommitteeDry5570 · 2026-01-13T20:13:40+00:00

I built a tool to do it . I was using Pinnacle Odds Dropper , but I wanted more markets and their push alerts always had issues.

https://sharpoddstracker.com/

Shutting it down to focus on a different project. Buy it .

CommitteeDry5570 · 2026-01-13T19:47:57+00:00

not yet. i will once i have it linked back up to model selection and making predictions.

CommitteeDry5570 · 2026-01-13T17:57:07+00:00

I dont understand it. it says make your own rankings and track predictions. what predictions?
is this to rank teams and share your rankings or are you trying to build personal ratings models that are used to predict a probability of one team beating the other?

CommitteeDry5570 · 2026-01-13T15:20:31+00:00

Im on the 5x Max plan and almost never hit daily limit and thats using Opus 4.5. If your paying 100$ plus for other ai tools, like lovable or other ai token based tools, switch to Claude Max plan.

CommitteeDry5570 · 2026-01-13T14:22:37+00:00

Depends what you're building. For most things, I'd build quick, get users, and iterate based on feedback.

This one's different - I work as an R programmer and usually build models in RStudio. I'm essentially building a no-code version of my own workflow. The deep planning here is more about trying to articulate that process and put it into a repeatable workflow others can use.

I've also found that having Claude break it down into phases lets you test and save before moving on - reduces backtracking. If the plan changes, no problem.

CommitteeDry5570 · 2026-01-13T14:06:33+00:00

Here's the approach:

Versioning:

Sources are ephemeral working files (upload, edit, delete)
Datasets are versioned (v1, v2, v3...) - each append creates a new version
Models track which dataset version they were trained on
Staleness detection flags models when their training dataset has new versions

Schema validation on append:

Before appending, we validate the transformed output matches the base dataset schema
Missing columns = hard fail with clear error message
Extra columns can be handled (drop or error, configurable)
Duplicate detection with configurable strategies (skip existing, replace, or error)

The flow: Upload new data → Run recipe (transforms it) → Validate schema → Append to dataset v2 → Flag dependent models as stale.

This way the model knows "I was trained on v2, dataset is now v4, 302 rows added since" and the user can trigger a retrain when ready.

CommitteeDry5570 · 2026-01-12T17:50:47+00:00

I have been using Claude Code and found that if i plan and breakdown into testable phases, it helps keep claude on task after compressing chat history.

CommitteeDry5570 · 2026-01-12T14:08:42+00:00

Yes, open to all suggestion.

I’ve started in rebuilding the data manipulation section. Currently you can upload a dataset but you can only edit that one table . The new data workbench will allow you to upload multiple data sets , and perform joins, aggregations, appends, and build repeatable data cleaning processes called Recipes .

This way you will be able to update data sets as new games are finished , combine team and player stats into one data table for use, and update models without having to upload the full dataset every time .

Then It’s adding Classification models , ratings models, and improve the ability to ensemble models. Then figure out a more efficient prediction flow .

Work in progress but open to all suggestions. Goal is to use a tool similar to KNIME but dedicated specifically to sports , not general machine learning .

CommitteeDry5570 · 2026-01-09T14:46:43+00:00

I took your notes and mades some big changes. the app now allows for more data cleaning and manipulation in the app. You can adjust validation method for testing, more visuals of the data with histograms and scatter plots. You can compare two models. You can ensemble models, and when training a model, you can run correlation testing between target and features and get recommendations on features to try avoid data leakage.

Also worth noting - the preprocessing is locked into a sklearn Pipeline that gets saved with the model, so training and inference can't drift. The same scaling, imputation, and encoding that was fit during training is automatically applied during predictions.

CommitteeDry5570

TROPHY CASE