Brian Elbert

Driving Go-to-Market Success for Life Science Startups | AI-Powered Marketing Strategist | GTM Partner

[Andrej Karpathy @karpathy]

We're starting to leave the territory where you'd test an LLM by e.g. "create an svg of pelican on a bicycle". As one idea to generalize it, I was interested what Opus 5 would do if I gave it the first paragraph of the Lord of the Rings, a 1M token budget (~$10) and asked for three js render of it. Opus went off for ~2 hours and wrote 5500 lines of code that (procedurally) rendered the story. It's kind of janky but fun. But it's a bit mindboggling that the LLM has to place and orchestrate various polygon assets in (x,y,z) coordinates and write code that animates it all, and that it even does anything at all.

I also like this kind of examples because no one in their right mind would ever spend the time to write something this custom but LLMs have all the stamina and patience in the world, so it's an example where we go from "no one would ever do this" to "sure, why not, it's ~free". There might be a lot more. But I'm excited about creating hyper custom worlds that you can imagine dropping players into, e.g. here to participate in the LoTR story as a spectator NPC, or one of the characters, or etc. Something like an ephemeral GTA of X on demand.

Last thought is that the domain of worlds/games exposes a weakness in LLMs: they can't easily audit their work because they aren't able to efficiently and natively perceive videos or play games within them. Here, Opus 5 had to very slowly and painstakingly take screenshots at different points, and it messed up a few times and created a bunch of jank. An example of raw capability (multimodal, gameplay) that I think is still quite lacking.

[ericosiu @ericosiu]

In twelve months, EVERY company will be running a Company Brain.

The teams who build it this year will spend the next year compounding. Everyone else is going to play catch up.

Here's what it actually is. You connect your Slack, your GitHub, HubSpot, all your tools into one intelligence layer, then build the org chart around it: a main brain up top, a fleet commander running the agent fleet, specialist sub-agents handling execution.

The reason it works is change management basically disappears. Your team already lives in Slack. You're just adding agents to the room they're already in.

You NEED to start building yours now. In a year this will stop being an advantage and will become table stakes.

[ClaudeDevs @ClaudeDevs]

Claude Managed Agents can operate in a sandbox you control, on your own infrastructure or with any provider you choose.

Today we added new guides for @blaxelAI, @e2b, @googlecloud, @namespacelabs, and @superserve_ai, so you can choose the best fit for your use case.

[Siddhartha Saxena @siddsax]

Anthropic onboarding day: Michael Scott introducing Karpathy like he just signed Wemby in free agency.

[Jaynit @jaynitx]

Mark Cuban says AI will split every company into 2 categories within 3 years

"When it's all said and done over the next 3 years, there's going to be two types of companies. Those who are great at AI and those who went out of business"

"The biggest challenge for a company is going to be for the CEO to make that decision that we're going to have to blow up a lot of what we do to recreate our company"

"We hear a lot of stories about huge public companies that spend a lot of money to try to implement AI and it doesn't really get them a return on investment."

"Because you already are running your business the way you've always run it."

"The things you've considered outsourcing, your customer call centers, AI agents are perfect for. The stuff you would give to an intern, AI agents are perfect for"

"But to really take advantage of AI you have to reformulate your business completely to build it on AI"

[TFTC @TFTC21]

Ken Griffin went home on a Friday "fairly depressed" after watching AI agents at Citadel do work that used to take teams of PhDs in finance months to complete. Done in days.

His words: "These are not mid-tier white collar jobs. These are extraordinarily high skilled jobs being automated by agentic AI."

This is the head of one of the most successful hedge funds in history saying the people he pays seven figures to analyze markets and structure deals are being replaced by software that works in hours instead of months. Not theoretically. In his own office. Right now.

The Coatue deck we covered earlier this week called agents "the biggest unlock" in AI. Griffin just confirmed it from the buy side. The shift from copilots to agents is not a future event. It is already happening at the highest levels of finance.

[The All-In Podcast @theallinpod]

“I am going to probably use $300M of Anthropic this year at Salesforce.” - Marc Benioff

“ These coding agents are awesome. Anthropic is awesome.

Coding, everything's going to be cheaper to make, it's more efficient.

I can do things that I just could not do before. I can go faster than ever before. I can implement my software and sell it at the same time. I've never been able to do that before. Today, I have humans, agents, and headless platforms all interoperating, never before.

So the opportunity for my own company and the efficiency that I have in my own company, in service and support, in distribution and marketing, across the board, is unprecedented. What I can do for our customers, unprecedented.

And, to that point, my gosh, have you seen Anthropic? It is a rocket ship that will not stop.”

[Dilum Sanjaya @DilumSanjaya]

Fun interactive science app ideas | Part 3

Played around with generating 3D biological structures and made an app to explore them interactively

UI Design
GPT Images 2

Code
Gemini 3.1 Pro

More demos ↓

[Julian Goldie SEO @JulianGoldieSEO]

Claude Code just got an update nobody is talking about. And it replaced my entire video crew.

You type one simple sentence.

Claude writes the script.

It uses ElevenLabs to clone your voice.

It calls Remotion to build the scenes.

It grabs HeyGen to make your avatar talk.

Ten minutes later, you have a finished video.

You never even turn on a camera.

This changes how we make content forever.

[Mnimiy @Mnilax]

https://t.co/W4MxdOyUKD

[Aakash Gupta @aakashgupta]

Anthropic just shipped sleep into agents.

When you sleep, your hippocampus replays the day's neural sequences to the cortex during 150-220 Hz bursts called sharp-wave ripples. The replay runs about 20x faster than the original experience. A 10-second sequence gets compressed to roughly 500 milliseconds. Wilson and McNaughton showed this in rats in 1994. You ran this algorithm last night on whatever you did yesterday, whether you wanted to or not.

The replay does two things at once. It extracts statistical patterns: what mattered, what generalizes, which sequences predicted reward. And it reorganizes the memory trace from hippocampus-dependent storage into neocortex, which is why old memories survive hippocampal damage but recent ones don't. Disrupt sharp-wave ripples in a rat with optogenetics and the rat fails the next day's task. The replay is causal, not correlational.

Most "agent memory" today is a search engine. Past sessions get embedded, you retrieve relevant chunks at the next call. That works for facts. It does not extract patterns and it does not reorganize the trace. Which is why agents plateau. The memory volume keeps growing while real capability flatlines.

Dreaming reviews past sessions, extracts patterns, curates memories. That is the brain's actual three-step algorithm. They called it dreaming because dreaming is what the algorithm does, in roughly the same order, for roughly the same reason.

Agents that dream between sessions will compound. The ones still running on raw context window will hit the same ceiling humans hit when they pull all-nighters.

[Brian Elbert @elbertbe]

Kurzweil set 2029 for AGI. 2045 for the singularity.

The question isn't whether AI will transform life science commercial operations. It's whether your infrastructure is structured to benefit when it does.

[Brian Elbert @elbertbe]

Read Kurzweil's "The Singularity Is Near" a decade ago. Felt like science fiction.

Just finished the sequel. It reads like a status report.

Here's what exponential AI growth actually looks like when you use these tools every day. A thread.

[Brian Elbert @elbertbe]

Most life science companies still run 2015 playbooks.

The gap between first movers and everyone else isn't growing linearly. It's growing exponentially.

Every quarter you wait, the cost of catching up increases — because the tools on the other side keep getting better, faster.

[Charly Wargnier ♨️ @DataChaz]

Andrej Karpathy (@karpathy), OpenAI co-founder, ex-Tesla AI, "vibe coding" creator.

In just 4 mins, he explains why Claude Skills, MCP servers, and AI agents are past the hype and are now the new baseline for building.

Worth every second ↓