Baylor Adams

I'm excited to announce Posh’s $37M Series B, led by @FirstMarkCap. 6 years ago, people told us a better events platform was a solved problem. 8m users and $350M in GMV later, we're just getting started. For more on our vision and what's next: posh.vip/vision

@interaction !!!

Starting today, personal superintelligence is just one tap away. No download, no signup. Text Poke for free now: Poke.com 🌴 — 0:00 – What's Poke? 0:50 – Introducing Poke Recipes 1:25 –  Create a Recipe in 10 seconds 1:43 – Earn on Poke 2:44 – Build with npx poke 12:58 – Recap 13:36 – Parisian Love

@AvantePrice @FirstMarkCap Let’s go

@Dezash3 Will be there!

@0baylor Come to yhack if you’re at yale on the 28-29th!

Visiting Waterloo, Georgetown, UPenn, and Yale in the next two weeks comment/DM if around!

@cwamidon We need you chris

How long until somebody does convoy-escort-as-a-service with unmanned systems?

@mollycantillon Very cool

i read california's entire $498 billion budget so you don't have to the wealth tax is supposed to fix our deficit. instead its accelerating it

thank you @cory and the @zfellows team for coming over and talking with our builder community at hopkins!

@wellsdouraghy Soon

@0baylor Baylor I want to see your own articles

"Luck can be engineered in your favor. Learn to play the opportunity game, increase luck surface area, and stop calling yourself unlucky. Because you are already lucky. Just not aware of it."

Aaru recently reached a $1 billion valuation, making it one of a growing crop of hot companies led by people who have barely cracked their 20s on.wsj.com/4b4wunG

@beechinour godly.website

S-tier websites for creative inspiration: film/video → frameset.app imagery → savee.com imagery → cosmos.so video/transitions → eyecannndy.com film stills → fancaps.net film stills → shotdeck.com web design → awwwards.com web Design → curated.design landing Pages → landing.love saas Websites → saaspo.com mobile Apps → mobbin.com brands → rebrand.gallery design Systems → component.gallery objects → cosmos.so what am i missing?

Thank you to the @WSJ and @VranicaWSJ for writing the first page in the story of Aaru. More soon.

"So we had Viper, which is today a 6.5ft long vertical takeoff kind of miniature fighter jet. And so the job of Viper is to do everything a fighter jet would do as best as can be done, while being cheap enough to mass manufacture, cheap enough to seriously go and make a million, two million of these things and then be runway independent. And so several hundred mile range, like 600 miles an hour, can go and get up to these high altitudes, but only cost $100,000. And you and I could take it out of a pelican case and launch it with no ground infrastructure.” @ethanrthornton @Mach_Industries

"He planned parks on the assumption that San Francisco would eventually have 2 million residents, but said little about planning housing." Not much has changed in 120 years

loved hosting a 10pm fireside chat with @cory at hacktj (world’s largest HS hackathon)! incredible conversation on startups and building at a young age. definitely inspired lots of students to think differently about what they want to work on next. huge thanks as well to @0baylor and @g_kasten from @zfellows for joining the discussion!

@rushilkukreja @cory Great to visit y'all!

@lameburgett So cool

I'm extremely excited to announce that we've successfully inferenced π0.5 on our excavator! We've collected a massive corpus of real-world data with natural language labels from operators in the industry and are using it to create some really cool policies. Here's our first demo of it successfully completing a task with just 200 trajectories. More on the way :) Read our blog post: labs.actor/research/vla-e… @physical_int

@arshdilbagi This is great Arsh!

The hard part about LLM failures is that their outputs rarely look like failures. The demo “works.” The output sounds coherent. The user actively uses the product. And your dashboard looks normal. Meanwhile, the system can be wrong, unsafe, or quietly driving up token spend. And you won’t notice until the damage adds up. Prompts often serve as business logic (policies, safety, and product context). But many teams ship them without the basics, such as versioning, reviewable changes, end-to-end traces, and eval gates. In production, it doesn’t crash. It degrades via wrong answers, policy misses, and surprise spending. No crash. No error. No alert. I cover this exact issue in my @Stanford CS 224G guest lecture on AI Observability and Evaluations. Here are the core ideas: • If you only log the final output, you’re guessing. Full traces show where it broke. • Evals are feedback loops. Use clear pass/fail criteria tied to outcomes. • Run evals continuously on production traces and don’t wait for support tickets. The moat isn’t prompt cleverness. It’s a measured improvement. Full lecture + blog below 👇

@SarvasvKulpati Let's say bottom 10% can be demolished for new housing?

I've decided to touch grass and urban sketch more. But I only want to draw the *most* beautiful buildings So instead of, idk, going on more walks, I indexed ~10,000 buildings in SF and made a hotornot for sf Help me find the prettiest SF buildings! facademash.com