Filter Capital

Tweeting dumb thoughts | Not Investment Advice

[Filter Capital @Filter_Capital]

@shortbus_ace Has outperformed its benchmark net and a true pure play etf to get shareholder yield factor as part of a portfolio

[Filter Capital @Filter_Capital]

Instead of doomerism the labs should have said “Most companies are *not* talking about replacing jobs due to agents. The major use-cases for agents are things that the company wasn’t able to do before or couldn’t prioritize […]. More emphasis on ways to make money v/ cut costs”

[Aaron Levie @levie]

Another week on the road meeting with a couple dozen IT and AI leaders from large enterprises across banking, media, retail, healthcare, consulting, tech, and sports, to discuss agents in the enterprise.

Some quick takeaways:

* Clear that we’re moving from chat era of AI to agents that use tools, process data, and start to execute real work in the enterprise. Complementing this, enterprises are often evolving from “let a thousand flowers bloom” approach to adoption to targeted automation efforts applied to specific areas of work and workflow.

* Change management still will remain one of the biggest topics for enterprises. Most workflows aren’t setup to just drop agents directly in, and enterprises will need a ton of help to drive these efforts (both internally and from partners). One company has a head of AI in every business unit that roles up to a central team, just to keep all the functions coordinated.

* Tokenmaxxing! Most companies operate with very strict OpEx budgets get locked in for the year ahead, so they’re going through very real trade-off discussions right now on how to budget for tokens. One company recently had an idea for a “shark tank” style way of pitching for compute budget. Others are trying to figure out how to ration compute to the best use-cases internally through some hierarchy of needs (my words not theirs).

* Fixing fragmented and legacy systems remain a huge priority right now. Most enterprises are dealing with decades of either on-prem systems or systems they moved to the cloud but that still haven’t been modernized in any meaningful way. This means agents can’t easily tap into these data sources in a unified way yet, so companies are focused on how they modernize these.

* Most companies are *not* talking about replacing jobs due to agents. The major use-cases for agents are things that the company wasn’t able to do before or couldn’t prioritize. Software upgrades, automating back office processes that were constraining other workflows, processing large amounts of documents to get new business or client insights, and so on. More emphasis on ways to make money vs. cut costs.

* Headless software dominated my conversations. Enterprises need to be able to ensure all of their software works across any set of agents they choose. They will kick out vendors that don’t make this technically or economically easy.

* Clear sense that it can be hard to standardize on anything right now given how fast things are moving. Blessing and a curse of the innovation curve right now - no one wants to get stuck in a paradigm that locks them into the wrong architecture. One other result of this is that companies realize they’re in a multi-agent world, which means that interoperability becomes paramount across systems.

* Unanimous sense that everyone is working more than ever before. AI is not causing anyone to do less work right now, and similar to Silicon Valley people feel their teams are the busiest they’ve ever been.

One final meta observation not called out explicitly. It seems that despite Silicon Valley’s sense that AI has made hard things easy, the most powerful ways to use agents is more “technical” than prior eras of software. Skills, MCP, CLIs, etc. may be simple concepts for tech, but in the real world these are all esoteric concepts that will require technical people to help bring to life in the enterprise.

This both means diffusion will take real work and time, but also everyone’s estimation of engineering jobs is totally off. Engineers may not be “writing” software, but they will certainly be the ones to setup and operate the systems that actually automate most work in the enterprise.

[Filter Capital @Filter_Capital]

@Sleepysolcap Great read. Especially with the citrini circle jerk on the TL. One point that stuck with me - the hyper niche services (tax, legal, UHNW WM) will become more valuable/expensive while wide-brushed versions of these go to 0

[Filter Capital @Filter_Capital]

Biggest beneficiary from a fragmented, competitive AV industry is $UBER

[Sawyer Merritt @SawyerMerritt]

NEWS: NVIDIA just announced Alpamayo, what CEO Jensen Huang calls the world’s first thinking, reasoning autonomous vehicle AI, launching on U.S. roads later this year, starting with the Mercedes CLA.

Jensen: "It's trained end-to-end. Literally from camera in to actuation out; It reasons what action it is about to take, the reason by which is came about that action, and the trajectory."

Alpamayo introduces Vision-Language-Action (VLA) models, which enable self-driving systems to interpret what they see, reason about complex driving scenarios, and generate driving actions. The platform includes large reasoning models, simulation tools for testing rare and edge-case scenarios, and open datasets for training and validation.

NVIDIA says the approach improves transparency, safety, and robustness in autonomous systems, particularly in complex real-world environments, and supports progress toward higher levels of vehicle autonomy:

"With a 10-billion-parameter architecture, Alpamayo 1 uses video input to generate trajectories alongside reasoning traces, showing the logic behind each decision. Developers can adapt Alpamayo 1 into smaller runtime models for vehicle development, or use it as a foundation for AV development tools such as reasoning-based evaluators and auto-labeling systems. Alpamayo 1 provides open model weights and open-source inferencing scripts. Future models in the family will feature larger parameter counts, more detailed reasoning capabilities, more input and output flexibility, and options for commercial usage."

[sysls @systematicls]

https://t.co/FQe5bCBqW1

[Filter Capital @Filter_Capital]

@buccocapital Yes they will want to, but will it even work and how would they get do so? On anti trust or a tax increase? If they run on a tax increase will they even win?

[Filter Capital @Filter_Capital]

@buccocapital $DIS and $ABNB. Both spent last 4 years growing into valuations and reasonably priced also have tailwinds going into 26’

[Filter Capital @Filter_Capital]

@buccocapital Would of been epic if they released nano pro with a picture of generated photo of Demis and Sundar dancing

[Filter Capital @Filter_Capital]

Must read

[Gavin Baker @GavinSBaker]

https://t.co/boFKQfPb3G

[Sam Altman @sama]

Congrats to Google on Gemini 3! Looks like a great model.

[Filter Capital @Filter_Capital]

Where gemini was behind (coding, technical queries) they now are leaders.

Next step, full integration with all google apps and third party apps + iPhone to become the undisputedly best assistant model

[Sundar Pichai @sundarpichai]

Introducing Gemini 3 ✨

It’s the best model in the world for multimodal understanding, and our most powerful agentic + vibe coding model yet. Gemini 3 can bring any idea to life, quickly grasping context and intent so you can get what you need with less prompting. 

Find Gemini 3 Pro rolling out today in the @Geminiapp and AI Mode in Search. For developers, build with it now in @GoogleAIStudio and Vertex AI. 

Excited for you to try it!

[Filter Capital @Filter_Capital]

Can we get Sama on that Jack Ma vacation plan?

[Filter Capital @Filter_Capital]

Complacency kills returns. Even the best "compounders" can break.
And when they do, trying to "buy the dip" is a dangerous game. What looks cheap at -30% can get a lot cheaper.

[Long Equity @long_equity]

Sometimes compounders stop compounding. What lesson do you take away from this?

[Filter Capital @Filter_Capital]

Near extreme fears at 1% from ATH… bullish

[Markets & Mayhem @Mayhem4Markets]

The most amusing part about Karp's meltdown is that $PLTR short interest is in the low single digits... 🤦‍♂️

[Filter Capital @Filter_Capital]

@dividenddude At 0

[Filter Capital @Filter_Capital]

AI trade past couple of days