Hacker News: wespiser_2018

Church of the TigerBeetle: A Look at Tech Evangelism

wespiser_2018 — Fri, 21 Aug 2026 19:35:17 +0000

Article URL: https://www.wespiser.com/posts/2026-08-03-church-of-the-tigerbeetle.html

Comments URL: https://news.ycombinator.com/item?id=49392877

Points: 18

# Comments: 9

Church of the TigerBeetle

wespiser_2018 — Mon, 03 Aug 2026 15:50:57 +0000

Article URL: https://www.wespiser.com/posts/2026-08-03-church-of-the-tigerbeetle.html

Comments URL: https://news.ycombinator.com/item?id=49157401

Points: 1

# Comments: 0

New comment by wespiser_2018 in "Faster binary search: from compiled code to mechanical sympathy"

wespiser_2018 — Fri, 17 Jul 2026 18:44:58 +0000

let middle = min_idx + ((max_idx - min_idx) / 2);

Respect!

Salience-Driven Development

wespiser_2018 — Mon, 13 Jul 2026 14:47:06 +0000

Article URL: https://www.wespiser.com/posts/2026-07-13-salience-driven-development.html

Comments URL: https://news.ycombinator.com/item?id=48893546

Points: 2

# Comments: 0

New comment by wespiser_2018 in "Startups as Reality Contact Machines"

wespiser_2018 — Tue, 30 Jun 2026 21:17:50 +0000

Author here: I'm curious if anyone has run into similar observations: founders that sounds great, are talented/ambitious, but their purpose for building is more aligned with internal satisfaction than external reality.

Startups as Reality Contact Machines

wespiser_2018 — Tue, 30 Jun 2026 21:14:38 +0000

Article URL: https://www.wespiser.com/posts/2026-06-30-reality-contact-machines.html

Comments URL: https://news.ycombinator.com/item?id=48739285

Points: 2

# Comments: 1

New comment by wespiser_2018 in "Finding the best dog treat with statistics"

wespiser_2018 — Tue, 23 Jun 2026 19:34:11 +0000

It's pretty interesting, but Bebop is barely treat motivated, and mostly inside. Once you take him outside, especially in open areas, he becomes more interested in tracking movement and chasing things.

I believe it's explained by the job we've asked Greyhounds to do: see movement, get released, run after it. Once you let go, that's it, the dog needs to be motivated enough by the running animal or lure, and there's no chance to reinforce the loop once it starts!

New comment by wespiser_2018 in "Finding the best dog treat with statistics"

wespiser_2018 — Tue, 23 Jun 2026 19:31:56 +0000

If I repeat this experiment, I'll be a lot more careful about that, or also alternate which direction I'm standing in.

I didn't realize R/L preference was biased until I did the data analysis, and during the trials he was picking from both hands often enough that I perceived it as roughly 50% depending on the treats!

New comment by wespiser_2018 in "Finding the best dog treat with statistics"

wespiser_2018 — Tue, 23 Jun 2026 19:28:00 +0000

With Bebop, it's dead birds! He also finds them, then checks the same spot for months afterwords!

New comment by wespiser_2018 in "Finding the best dog treat with statistics"

wespiser_2018 — Tue, 23 Jun 2026 12:29:29 +0000

Author here, yes, that's correct.

The initial set-up was to do 3 comparisons of the 5 treats (30 trials), alternate between right and left hand, then write a quick python script to randomize the order.

A bit more than halfway through the experiment, I ran the model and realized that A/D/E were the only contenders left, so I removed the B/C trials and added more A/D/E trials.

New comment by wespiser_2018 in "Finding the best dog treat with statistics"

wespiser_2018 — Mon, 22 Jun 2026 23:41:13 +0000

That's awesome! Thank you!

New comment by wespiser_2018 in "Finding the best dog treat with statistics"

wespiser_2018 — Mon, 22 Jun 2026 17:50:14 +0000

Author here: I did a quick experiment with my Greyhound, Bebop, to figure out the treat he prefers best using pair-wise comparison analyzed with the Bradley-Terry model. Same tech as Elo scores in chess, and several other places! Enjoy!

Finding the best dog treat with statistics

wespiser_2018 — Mon, 22 Jun 2026 17:46:48 +0000

Article URL: https://www.wespiser.com/posts/2026-06-19-best-dog-treat.html

Comments URL: https://news.ycombinator.com/item?id=48633410

Points: 142

# Comments: 57

New comment by wespiser_2018 in "The AI Productivity Trap"

wespiser_2018 — Thu, 28 May 2026 16:54:54 +0000

Hi Folks, author here! Curious if people have run into the same issues, or heard the same things.

The AI Productivity Trap

wespiser_2018 — Thu, 28 May 2026 16:54:32 +0000

Article URL: https://www.wespiser.com/posts/2026-05-28-ai-productivity-trap.html

Comments URL: https://news.ycombinator.com/item?id=48311754

Points: 3

# Comments: 1

Swatch Royal Pop: A Grotesque Spectacle of the Absurd

wespiser_2018 — Sat, 16 May 2026 19:49:45 +0000

Article URL: https://www.wespiser.com/posts/2026-05-16-spectacle-absurd.html

Comments URL: https://news.ycombinator.com/item?id=48163186

Points: 1

# Comments: 0

New comment by wespiser_2018 in "The Traveling Salesdog Problem"

wespiser_2018 — Fri, 08 May 2026 02:04:05 +0000

Practically speaking, Bebop is very excited to go out, and vetos are most common going home.

A plan with options might handle that, but that makes it trickier to satisfy the novelty constraint if each days plan needs to account for what was made on the previous day. Could be interesting to see what a plan with optionality looks like!

New comment by wespiser_2018 in "The Traveling Salesdog Problem"

wespiser_2018 — Tue, 05 May 2026 19:31:25 +0000

Author Here: I wrote this about using numerical optimization to solve problems in my daily life. I'm interested if anyone else has done the same, and what worked for them!

The Traveling Salesdog Problem

wespiser_2018 — Tue, 05 May 2026 19:30:35 +0000

Article URL: https://www.wespiser.com/posts/2026-05-04-traveling-salesdog.html

Comments URL: https://news.ycombinator.com/item?id=48027346

Points: 26

# Comments: 6

New comment by wespiser_2018 in "AI Can Find the Code. It Didn't Know How the System Worked"

wespiser_2018 — Tue, 28 Apr 2026 13:40:26 +0000

Author here: I wrote this article about a failure I had applying LLM to an enterprise codebase, and ran a quick pilot study on a similar repo to understand the failures better.

I'd interested to know, are folks seeing the same things?