Flare Web Design

A React-driven web development & design agency. We create high-quality, dynamic, personalized websites for brands.

[Flare Web Design @flarewebdesign]

@businessbarista @da_fant I’ve been working on this, it’s extremely tough, but very fun - even if it doesn’t gain traction 🫡

https://t.co/OJuCGyoLJo

[Flare Web Design @flarewebdesign]

@garrytan I’ve been working on this for a few months now, it’s very similar to your GBrain. It’s called “Agent Big Brain,” or ABB for short.

A cognitive architecture, runtime, and has a knowledge graph.

https://t.co/b6Cs4zxMQw

[Brian Armstrong @brian_armstrong]

People are capable of far more than they think, on far shorter timelines. Problems expand to fill the time you give them.

[Flare Web Design @flarewebdesign]

@gdb I’ve been building Agent Big Brain! A governance-first cognitive runtime for autonomous agents.

https://t.co/b6Cs4zxMQw

[Flare Web Design @flarewebdesign]

@jimcramer Can you?

[Flare Web Design @flarewebdesign]

@garrytan True

[Alex Lieberman @businessbarista]

Someone is going to build a worldclass “Brain” for enterprises & make a stupid amount of money.

Why? As @da_fant said, “coding w ai is solved bc all context is in the git repo. knowledge work is difficult bc context is spread out. an ai system that creates a git repo w all context for a knowledge worker will be able to 100% automate the work.”

When companies talk about being data ready for AI, this is what they’re implicitly saying.

Engineering has been prepared for this moment for a long time because of the deterministic nature of code, the centralization/versioning of data (read: GitHub), and AI tools that are largely build by engineers for engineers.

But for the rest of white collar work, there’s a TON of catching up to do to properly harness the power of the technology.

The big challenge here, and why no one has truly cracked the code for "an ai system that creates a git repo w all context for a knowledge worker" is because unlike code, most knowledge is 1) distributed, 2) unstructured, and 3) unverifiable.

It's distributed: transcripts live in Granola. Documents in Notion. Customer Data in Hubspot. ERP. Emails. Slack messages. Random spreadsheets. SOP docs. Etc. Etc.

Building an ingestion engine that connects to all of your disparate data sources and auto-updates based on the shelf-life of the data is the first, and frankly, easiest step of the process.

Next, it's unstructured: let's say I want to create a proposal for a potential client. To nail the proposal, I want it to pull important information from a variety of sources. The specific asks & background from our initial sales call. Previous proposals to anchor ourselves to a proven format. And completed sprint boards from Linear, so the pricing & timeline in the document is grounded in truth.

Whether it's a thoughtful filesystem (a la Obsidian) or an OpenClaw-esque memory structure, the brain needs to be great at self-organizing in a thoughtful schema. This is very hard, especially if you want to build a generalizable brain that can be shaped to an array of different enterprises.

And finally, most knowledge is unverifiable: writing a function, running a unit test, and seeing if the code works is easy. It works or it doesn't. Using AI to accelerate your content creation process is highly subjective. What is a good/bad idea? Is the content in your voice or not? Does it feel like slop or novel? Answering these questions are both difficult and non-verifiable.

That same system described above doesn't just have to be great at organizing & forming coherent relationships, but it also has to be great at self-improving based on feedback from the user. Memory systems (like those introduced by OpenClaw) are great to a point, but as you scale the corpus of data within your company's brain, things like compaction and cleaning become wildly important to avoid the needle in the haystack problem.

Someone is going to figure out how to solve this problem, and when they do, not only will they make a shit ton of money, but they'll be robinhood for knowledge workers, enabling non-engineers to enjoy the sort of leverage that only technical folks have felt for the last few years.

[Flare Web Design @flarewebdesign]

@businessbarista @da_fant I’ve been working on this, it’s extremely tough, but very fun - even if it doesn’t gain traction 🫡

https://t.co/OJuCGyoLJo

[Flare Web Design @flarewebdesign]

@garrytan I’ve been working on this for a few months now, it’s very similar to your GBrain. It’s called “Agent Big Brain,” or ABB for short.

A cognitive architecture, runtime, and has a knowledge graph.

https://t.co/b6Cs4zxMQw

[Flare Web Design @flarewebdesign]

@garrytan Oh, and here’s the Deep Wiki (although it may be slightly out of date):

https://t.co/bAK7IAQFuR

[Flare Web Design @flarewebdesign]

@garrytan I’ve been working on this for a few months now, it’s very similar to your GBrain. It’s called “Agent Big Brain,” or ABB for short.

A cognitive architecture, runtime, and has a knowledge graph.

https://t.co/b6Cs4zxMQw

[Flare Web Design @flarewebdesign]

@BitcoinArchive Satoshi.

[Flare Web Design @flarewebdesign]

@daviddorg No, you just want to be free from your desk :)

[Reid Wiseman @astro_reid]

I choose to believe this fortune I received tonight. Perhaps the Moon or a #JourneyToMars

[Flare Web Design @flarewebdesign]

@sama Thanks!

[Marques Brownlee @MKBHD]

Ok last one: the rarest solar eclipse of all time. Only 4 people have seen this with their naked eyes. The sun is fully behind the moon. The only faint light hitting the near side is reflecting off of earth, 250,000 miles away. And the stars and galaxies in the background, sheesh

Nikon Z9
f/2.0
2 second exposure
ISO 1600

@NASA: https://t.co/twBqbUEDs2

[Savanah Tujague @savanah2j]

I NEVER WANNA HEAR A SINGLE PERSON EVER TELL ME MANIFESTATION ISNT REAL

[comma @comma_ai]

Open source will win

[Three.js @threejs]

https://t.co/GuM0rhBCPe

[Mustafa @oprydai]

become a generalist.

specialization makes you efficient. generalization makes you dangerous.

what it actually means:
• learn across domains → math, physics, software, economics, biology. patterns repeat across fields.
• connect ideas → innovation happens at the intersection, not inside silos.
• adapt fast → when one field shifts, you don’t collapse, you pivot.
• see systems → specialists see parts, generalists see the whole
• build end-to-end → from idea → design → implementation → delivery

the world rewards specialists in stable environments.
it rewards generalists when things are changing.

right now, everything is changing.

don’t just go deep.
go wide, then stack depth where it matters.

[Pawel Nolbert @pawelnolbert]

Still the best splash screens of them all. #nostalgia

[Garry Tan @garrytan]

If you hate codegen and it's April 2026, well all I can say to you is:

Have fun coding at 1x speed