
Brandon Bodine
100 posts

Brandon Bodine
@BrandonHBodine
Chop wood Carry water


@bytebot Advertising that you use a bigger competitor (and not an alternative - either you use Codex or Antigravity!) to Antigravity suggests both that it's subpar (devs don't dogfood Antigravity) and that production was sloppy (no one watched the video to catch this part)


Introducing Antigravity 2.0, a new standalone desktop application that delivers fully on that original glimpse of a truly agent-optimized experience. Rebuilt from the ground up with multi-agent teams, scheduled tasks, native voice and one-click integration with other Google products. Learn how to get started with Antigravity 2.0 👇



Did a very different format with @reinerpope – a blackboard lecture where he walks through how frontier LLMs are trained and served. It's shocking how much you can deduce about what the labs are doing from a handful of equations, public API prices, and some chalk. It’s a bit technical, but I encourage you to hang in there - it’s really worth it. There are less than a handful of people who understand the full stack of AI, from chip design to model architecture, as well as Reiner. It was a real delight to learn from him. Recommend watching this one on YouTube so you can see the chalkboard. 0:00:00 – How batch size affects token cost and speed 0:31:59 – How MoE models are laid out across GPU racks 0:47:02 – How pipeline parallelism spreads model layers across racks 1:03:27 – Why Ilya said, “As we now know, pipelining is not wise.” 1:18:49 – Because of RL, models may be 100x over-trained beyond Chinchilla-optimal 1:32:52 – Deducing long context memory costs from API pricing 2:03:52 – Convergent evolution between neural nets and cryptography











lol we might accidentally have timed it perfectly for @aiDotEngineer to be the ultimate Deep Research conference - @AarushSelvan + Mukund on how they built Deep Research - @OpenAI Deep Research Agent - @vagabondjack's "Deep Research for Finance" - competitors at Jane St, BlackRock, Bloomberg - @barry_zyj on Anthropic's agents design patterns I think Deep Research Agents are actually the right form factor for where we are in the maturity cycle: - read only, so ~no side effects, low chance of mistakes - maturing @browserbase / @expandai_ / @firecrawl / @ExaAILabs ecosystem to connect LLMs to the web in various ways - llms need longer CoT/tool/usereflection/multiagent feedback to arrive at insight for now, so make them async





Claude Skills are awesome, maybe a bigger deal than MCP simonwillison.net/2025/Oct/16/cl…













