Proofd – Free AI career risk score based on your tasks, not job title
Task-level AI risk beats job-title predictions, but methodology isn't transparent.

Optimizes for HN algorithms when the best strategy is just building something good.
Indie hackers and developers launching on Hacker News
Hacker News Algolia Search · HN Search
I built a tool that helps optimize your post for hitting the first page of Show HN.
How it works: I used a Hugging Face dataset of all Hacker News posts from the past 3 years and trained a model that predicts how successful your post might be. There's still a lot of randomness on HN, so nothing is guaranteed, but the tool helps optimize your post for higher odds.
A couple of interesting findings:
- GitHub repo links work x3 better than regular domains - Open-source tools have a steady virality rate (13.9% - one of the highest) - "I built" outperforms "We built" - Using parentheses and mentioning technologies (Lua, Postgres, Rust, etc.) helps a ton.
You can try the tool at wannalaunch.com or read the blog posts for more insights from the analysis. The model is also available as open source if you want to retrain it or look under the hood.
Happy to hear the feedback!
Task-level AI risk beats job-title predictions, but methodology isn't transparent.
Iran strike case study is compelling, but backtesting on three events is thin.
Cross-exchange prediction market data without scrolling six platforms; arbitrage finder included.
Transparent scoring formula beats black-box prediction market aggregators.
Uses KL divergence to give asymmetric moves the weight they deserve (a 5%→10% jump reads way louder than 50%→55%), then multiplies that by log-volume, historical SNR and trajectory consistency to surface genuinely interesting shifts. Practical engineering choices — persisted snapshots, rolling detection windows, cooldown dedupe and Telegram delivery — make this something you can drop into a trading workflow and actually rely on.
Polished bracket tracker but KenPom already does predictions without the agent buzz.