Cliffe

Solutions Consultant @ PRESHai I Helping IT solution providers turn AI into revenue, automation and operational leverage.

[Google @Google]

After years of research, Project Suncatcher is scheduled to embark on its first test in orbit, launching a prototype satellite to evaluate how Google Tensor Processing Units (TPUs) perform in space. Learn more about the science behind this moonshot. ⬇️ https://t.co/GGTH2tZOHZ

[SpaceXAI @SpaceXAI]

Welcome to the SpaceXAI team!

Cursor will help us move faster on the path to the world's most useful AI, starting with software engineering and expanding into knowledge work.

[Cliffe @CliffeLife]

2036 will be unrecognizable.

[Elon Musk @elonmusk]

That was 10 years ago

Imagine 10 years from now

[Cliffe @CliffeLife]

Evolution within a few months.

[Praveen Neppalli @praveenTweets]

As our CFO @_balaji_km mentioned at earnings today, we’re seeing some very interesting trends on AI costs. I think it’s another signal that we’re coming to the end of the so-called ‘tokenmaxxing’ era.

Here’s what’s been happening behind the scenes.

Since the beginning of the year we’ve more than quadrupled the number of people using frontier AI tools. That’s thousands of engineers using them every single day. During that same period, our cost per token has declined.

You might expect costs to rise as adoption accelerates. We've seen the opposite. Not because we've restricted access, but because we've treated efficiency as an engineering problem rather than a budget problem. A few examples:
• Caching and reuse: We use optimizations to improve our prompt cache hit rate that reduce our input token spend.
• Better defaults and tooling: We tuned default model settings, context sizes and developer workflows so teams get the same results with fewer tokens and lower-cost inference.
• Visibility drives efficiency: We gave engineers real-time visibility into their AI usage and costs per hour.
• Experimenting with open-weight models: we continuously evaluate new models and deploy the best option for each use case.

This is the future of applied AI at enterprise scale. The next phase, whatever we call it, will not be characterized by who spends the most tokens, but about how people use them as efficiently as possible.

Credit to all the engineers at @Uber who are helping to build this future. 🚀

[Cliffe @CliffeLife]

Cursor will go down as one of the best companies in human history.

[Cursor @cursor_ai]

Introducing Cursor Router, our intelligent model router that selects the right model for the task at hand.

Router delivers frontier-quality results at 60% lower cost.

[Cliffe @CliffeLife]

CheckMate.

[Chamath Palihapitiya @chamath]

Elon’s original vision of an open, American AI was right.

He could still flip Grok to open source which could be checkmate.

Why?

If you flip Grok open source, you necessarily move all margins out of the model layer and down into the infrastructure (chips + CSPs) and above to apps.

He owns a massive data center build, owns next gen inference AI and owns the most used app (Cursor). So arguably he would make *more* margin by doing this. Then moving the DCs to space makes even more sense.

[Robotaxi @robotaxi]

Robotaxi now in Tampa & Orlando!

[Cliffe @CliffeLife]

Good point.

[Bill Gurley @bgurley]

If you are on the verge of AGI or ASI, why isn’t your model smart enough to recognize espionage distillation in real time? You say “cure cancer in a few years.” Isn’t sniffing illicit distillation quite a bit easier than curing cancer? Why write letters to DC? Just use AGI.

[@jason @Jason]

Given token economics, we really need @apple’s new ceo to go all in on workstations that can run local, open source models

Ideally, with a router that can flip between local models and frontier models when the former gets stuck.

And America needs an open source champion — we really should not be comfortable with the Chinese owning the open source LLM market to the extent they do

[Peter Steinberger 🦞 @steipete]

Here’s your monthly reminder that you shouldn’t be prompting coding agents anymore.

You should be designing loops that prompt your agents.

[PRESHai @preshai]

MODEL BEHAVIOR EP2: Always-on agents, identity governance & the implementation land grab.

@chrismcgovern20, Paul Radcliffe & Archer Preshly (one of our internal general purpose AI agents) break down the week:

-- Microsoft Scout: why identity is the whole ballgame
-- "Digital workers" = employee-shaped risk surface
-- Anthropic's recursive self-improvement paper
-- Build your own harness or get locked in

(0:00) Cold open
(1:07) Microsoft Scout & why agent identity is everything (5:15) Digital workers and the blast-radius problem (16:04) The implementation land grab: Anthropic & OpenAI go to channel
(22:10) Vendor lock-in & why you build your own harness
(28:25) Where agent memory actually lives
(30:23) Recursive self-improvement & the 4-month doubling
(40:10) "Voluntary" government AI oversight
(49:34) The system is the product, not the agent
(50:23) Archer's Corner

[Cliffe @CliffeLife]

AI is no longer a future conversation for the IT channel, it’s an execution problem. PRESHai is here to help partners turn AI into real business impact. Proud to be part of what’s next.

[Chris McGovern @chrismcgovern20]

https://t.co/yvxIyZzp84

[Cliffe @CliffeLife]

Coach, see u on Sunday!!!

[Jon Gruden @BarstoolGruden]

TAMPA BAY!!!! WE WILL SEE YOU FOR GAME 7 ON HOME ICE LET’S GO!!

[Cliffe @CliffeLife]

Playoff HOCKEY!!!!!

[Paul Bissonnette @BizNasty2point0]

Boom. https://t.co/ePzs8FyPTY

[Cliffe @CliffeLife]

@jayRecher Dude is a such a fucking beauty.

[Jon Gruden @BarstoolGruden]

TAMPA BAY!!!! HOCKEY TOWN!!!!

[Cliffe @CliffeLife]

This will always be a core memory. Bolts in 6 🤙🏾

[Austin Reid @austinreid21]

XRP trading is on fire.

We've seen 10x growth in volume at FalconX between the first and second halves of Q4.

This isn’t just retail action—institutions are driving the momentum.

[Cliffe @CliffeLife]

@ZssBecker Squirrel 🐿️

[Cliffe @CliffeLife]

@ZssBecker Dude is legit.