KalskiTheDan

3 ms·

1. 1.▲
   by KalskiTheDan 6mo ago

   > everyone gets a power drill > more holes in more walls > none of them in the right place Getting the drill wasn't the hard part, knowing where to drill is
2. 2.▲
   by KalskiTheDan 6mo ago

   I ran into this building data pipelines for LLMs. Kept feeding structured JSON with numbers and the model would do bizarre arithmetic on them. The moment I shifted to computing the analysis upstream and describing results in plain english,
3. 3.▲
   by KalskiTheDan 6mo ago

   I'd bet that still to this day, most interview questions test recall (of XYZ) and recall is what LLMs are best at. "Explain the difference between X and Y" or "what would you do in scenario Z" are search queries now
4. 4.▲
   by KalskiTheDan 6mo ago

   >> AT some point, you get conviction, this will work and worth pursuing full-time even though 0 revenue to begin with. My conviction was seeing myself using what I built growing from a few times a week to everyday use. Then when one r
5. 5.▲
   by KalskiTheDan 6mo ago

   I'm a solo dev; 6 months in the making. I built a financial context API that returns pre-analyzed market briefings for AI agents (on-chain, macro, regime classification), then ran 7 controlled experiments to find out if it actually hel
6. 6.▲
   Why Linguistic Context Outperforms Raw Data for LLM Decision-Making(prereason.com)

   4 points by KalskiTheDan 6mo ago|1 comments