Tech Observer

Previously S&J Investments. AI Sales Exec. Hunting asymmetric opportunities. Focus on AI infrastructure, energy & compute. Research & 90-second breakdowns.

[Tech Observer @J5jayfive]

https://t.co/rwuLk1MaTQ

[Tech Observer @J5jayfive]

But but but…..

Theres no more financing for the AI bubble unless you’re $SPCX!?

[Beth Kindig @Beth_Kindig]

Nebius $NBIS says its has secured a $3.5 billion financing facility from Citi to help fund GPU purchases and its AI data center buildout, with the facility maturing next year.

$CRWV $NVDA

[Tech Observer @J5jayfive]

I think in a market where $BE gets punished 15% for going cash flow negative…. While dropping a massive beat on Rev and EPS with expanding margins and improving eps…

You have to ask if the RR is worth it on most of the neocloud sector.

I think $NBIS is the only one worth owning and I actually don’t own it right now.

Also the photonics sector has been beat up so bad you can finally grab some of those at attractive prices. Again, playing same theme but FCF positive.

[Tech Observer @J5jayfive]

I love $NBIS but this is a great take.

$BE rides the same compute demand wave as neoclouds with none of the long term economic question marks.

I am bullish $NBIS but otherwise I would rather just own $BE and ride the rising tide.

[Feroce Research @FeroceResearch]

Bloom Energy is a better compute/energy play than any neocloud out there

If your belief is that we simply do not have enough compute to power the growth of AI, you are likely to see more success through $BE moving forward versus a basket of neoclouds

Same reasoning behind both baskets, but vastly different investor confidence between both

[Tech Observer @J5jayfive]

@tilmancompounds Expound please. What’s the goal of the tool? Where do you think you’re behind.

[Tech Observer @J5jayfive]

I’ll be real.

Stressful month with that insane drawdown, was worse than July becuase July was coming off the peak.

Emotionally good to see some relief today in the market.

I work at an Anthropic competitor, but right now we are all rooting for them.

[Tech Observer @J5jayfive]

$BE is ripping

I covered the selloff and business overview in this video last week.

Get caught up in 2 minutes. ⬇️📜

[Tech Observer @J5jayfive]

$BE

What the F&CK just happened to Bloom Energy!?

Lets talk about what Bloom actually does, earnings, why it fell off a cliff, the bull case and the bear case.

Is it a Buy? Or Further to fall....

2 min video

[Tech Observer @J5jayfive]

$AXTI reports this week

It is the backbone of the photonics movement.

It’s currently 60% off its high after an insane quarter.

Potentially one of the best opportunities in the market but also one of the most volatile stocks.

I made a full breakdown video attached below.

[Tech Observer @J5jayfive]

I spent the last few days digging into $AXTI and the photonics chain.

I made a video overview of everything you need to know heading into earnings this week.

Revenue projects to go from $100M to $700M by 2028

Still a tiny company at $3b market cap but supplies almost every major photonics player and has essentially no competition.

After the October AI pullback, its actually pretty cheap if you believe their projections.

Video covers how $AXTI is upstream from $LITE, $COHR, $AAOI, $FN and others.

I started making these videos a few weeks ago, production quality and speed are rapidly improving. I plan to keep kicking them out.

Follow me if you find these helpful... more on the way.

[Tech Observer @J5jayfive]

@rg807 Interesting…. I wrote a post about the adoption cycle earlier.

I somewhat agree. People expected magic bullet.

https://t.co/Ono5ki8oSs

[Tech Observer @J5jayfive]

This headline sounds unbelievable bearish… if you don’t understand where we are in the tech adoption cycle.

The article goes on to say:

“Since 2022, revenue per employee figures have skyrocketed for tech companies — rising from $550,000 to nearly $800,000 today.”

It’s not because tech companies are the only ones who get value from AI, it’s because tech companies are about 24 months ahead of everyone else in their adoption and implementation of AI systems.

I work at a Mag 7 company and I sell AI and work on ai implementation for a living. The way we operate internally is lightyears ahead of the companies I am selling to.

Even if they sign a deal and start spending, the implementation timeline to see real payoff is closer to 12-18 months than it is to a quarter.

In fact, one thing I’m hearing from clients more and more is that employees are frustrated because their tech stack at home is significantly more advanced than their tech stack at work. They are working on things for hours at the office that they could accomplish at home in a few minutes.

These are your best employees. And eventually these people find companies that have kept up with AI adoption.

Google, Microsoft, Meta, NVDA etc… made themselves patient zero for ai workflow implementations, they didn’t wait for it to be consensus. They started working on this day one, and now they see the results.

That’s not bearish, it means we are incredibly early on the S curve.

A few examples of areas that give employees time back:

- Every system / app I work in can talk to each other. I don’t even have to open them to get what I need from inside them

- All corporate information and documentation is indexed and searchable from one place.

- I can identify any resource or person I need from across the company for a project instantly.

- Document review and auditing

- Large scale information extraction and insight finding across structured and unstructured data.

That’s just the easy stuff, doesn’t even go into more strategic workflows or processes that are virtually fully automated requiring human review.

The problem is giving your employee access to ChatGPT enterprise and not doing the foundational work to make sure it’s built into company data sources doesn’t actually provide much value.

Most companies are currently scoping out their Ai strategy or in early stages of strategic implementation.

My honest POV is that this stat shows just how early we are in the cycle, and the Mag7 have proved how much value there is to be gained here if you do the work to get it right.

[Tech Observer @J5jayfive]

Either we are approaching the end of the AI buildout and hedge funds timed this perfectly.

Or every ai infrastructure stock is incredibly cheap right now.

[Tech Observer @J5jayfive]

@tilmancompounds $SPCX and $META announced $135 billion in financing for AI buildout in the last 48 hours….

Market is acting like this is over.

Elon and Zuck, two guys famously behind on next gen tech.

[Tech Observer @J5jayfive]

@tilmancompounds $SPCX and $META announced $135 billion in financing for AI buildout in the last 48 hours….

Market is acting like this is over.

Elon and Zuck, two guys famously behind on next gen tech.

[Tech Observer @J5jayfive]

@JonahLupton My thoughts as someone who does this for a living… they don’t understand the tech adoption cycle.

https://t.co/Ono5ki8oSs

[Tech Observer @J5jayfive]

This headline sounds unbelievable bearish… if you don’t understand where we are in the tech adoption cycle.

The article goes on to say:

“Since 2022, revenue per employee figures have skyrocketed for tech companies — rising from $550,000 to nearly $800,000 today.”

It’s not because tech companies are the only ones who get value from AI, it’s because tech companies are about 24 months ahead of everyone else in their adoption and implementation of AI systems.

I work at a Mag 7 company and I sell AI and work on ai implementation for a living. The way we operate internally is lightyears ahead of the companies I am selling to.

Even if they sign a deal and start spending, the implementation timeline to see real payoff is closer to 12-18 months than it is to a quarter.

In fact, one thing I’m hearing from clients more and more is that employees are frustrated because their tech stack at home is significantly more advanced than their tech stack at work. They are working on things for hours at the office that they could accomplish at home in a few minutes.

These are your best employees. And eventually these people find companies that have kept up with AI adoption.

Google, Microsoft, Meta, NVDA etc… made themselves patient zero for ai workflow implementations, they didn’t wait for it to be consensus. They started working on this day one, and now they see the results.

That’s not bearish, it means we are incredibly early on the S curve.

A few examples of areas that give employees time back:

- Every system / app I work in can talk to each other. I don’t even have to open them to get what I need from inside them

- All corporate information and documentation is indexed and searchable from one place.

- I can identify any resource or person I need from across the company for a project instantly.

- Document review and auditing

- Large scale information extraction and insight finding across structured and unstructured data.

That’s just the easy stuff, doesn’t even go into more strategic workflows or processes that are virtually fully automated requiring human review.

The problem is giving your employee access to ChatGPT enterprise and not doing the foundational work to make sure it’s built into company data sources doesn’t actually provide much value.

Most companies are currently scoping out their Ai strategy or in early stages of strategic implementation.

My honest POV is that this stat shows just how early we are in the cycle, and the Mag7 have proved how much value there is to be gained here if you do the work to get it right.

[Tech Observer @J5jayfive]

@HireWorkforceAI I had that convo with an executive of a fortune 50 financial services firm last week. He has a team of PHDs who are increasingly frustrated with how they have to work at work….. vs what they can accomplish at home. He’s worried is about to become a human capital problem.

[Tech Observer @J5jayfive]

This headline sounds unbelievable bearish… if you don’t understand where we are in the tech adoption cycle.

The article goes on to say:

“Since 2022, revenue per employee figures have skyrocketed for tech companies — rising from $550,000 to nearly $800,000 today.”

It’s not because tech companies are the only ones who get value from AI, it’s because tech companies are about 24 months ahead of everyone else in their adoption and implementation of AI systems.

I work at a Mag 7 company and I sell AI and work on ai implementation for a living. The way we operate internally is lightyears ahead of the companies I am selling to.

Even if they sign a deal and start spending, the implementation timeline to see real payoff is closer to 12-18 months than it is to a quarter.

In fact, one thing I’m hearing from clients more and more is that employees are frustrated because their tech stack at home is significantly more advanced than their tech stack at work. They are working on things for hours at the office that they could accomplish at home in a few minutes.

These are your best employees. And eventually these people find companies that have kept up with AI adoption.

Google, Microsoft, Meta, NVDA etc… made themselves patient zero for ai workflow implementations, they didn’t wait for it to be consensus. They started working on this day one, and now they see the results.

That’s not bearish, it means we are incredibly early on the S curve.

A few examples of areas that give employees time back:

- Every system / app I work in can talk to each other. I don’t even have to open them to get what I need from inside them

- All corporate information and documentation is indexed and searchable from one place.

- I can identify any resource or person I need from across the company for a project instantly.

- Document review and auditing

- Large scale information extraction and insight finding across structured and unstructured data.

That’s just the easy stuff, doesn’t even go into more strategic workflows or processes that are virtually fully automated requiring human review.

The problem is giving your employee access to ChatGPT enterprise and not doing the foundational work to make sure it’s built into company data sources doesn’t actually provide much value.

Most companies are currently scoping out their Ai strategy or in early stages of strategic implementation.

My honest POV is that this stat shows just how early we are in the cycle, and the Mag7 have proved how much value there is to be gained here if you do the work to get it right.

[Tech Observer @J5jayfive]

I spent the last few days digging into $AXTI and the photonics chain.

I made a video overview of everything you need to know heading into earnings this week.

Revenue projects to go from $100M to $700M by 2028

Still a tiny company at $3b market cap but supplies almost every major photonics player and has essentially no competition.

After the October AI pullback, its actually pretty cheap if you believe their projections.

Video covers how $AXTI is upstream from $LITE, $COHR, $AAOI, $FN and others.

I started making these videos a few weeks ago, production quality and speed are rapidly improving. I plan to keep kicking them out.

Follow me if you find these helpful... more on the way.

[Tech Observer @J5jayfive]

@bonjae3 It’s not whether I believe him, it’s whether he will have a material impact on these stocks.

Long term, the facts will take care of it. Near term he can move markets, especially when they are already weak at the moment due to macro.

[Tech Observer @J5jayfive]

$NBIS $IREN

It really feels like Elon wants to drive down the neocloud sector and buy them for cheap.

We know he has massive compute ambitions on a very short timeline.

His voice is powerful enough that this could be a real headwind in the current environment.

[Elon Musk @elonmusk]

@Yuchenj_UW I think we’re going to see a lot of stranded compute in partially complete data centers

[Tech Observer @J5jayfive]

Agree with that but I think he’s saying you need to cast some doubt on projections as projects will stall due to materials and power bottlenecks. Thus potentially discounting forward growth numbers.

He’s not bearish ai and compute. He’s bearish on execution and calling out risk.

[Tech Observer @J5jayfive]

So many thoughts about this:

1. Retail was very early to the ai move and a ton of retail reaped rewards.

2. It does feel like hedge funds have decided the ai bubble popped before it actually popped.

3. In the last few years retail has been greatly rewarded for buying fear…

[Shay Boloor @StockSavvyShay]

JPMorgan says retail investors just bought a record ~$540M in tech stocks over five days.

Pretty interesting seeing retail rush back into tech while hedge funds cut exposure despite AI demand and earnings continuing to grow.

[Tech Observer @J5jayfive]

@filamentico What’s your interpretation?

[Tech Observer @J5jayfive]

@mlee_walsh @tilmancompounds Appreciate you.

[Tech Observer @J5jayfive]

$BE

What the F&CK just happened to Bloom Energy!?

Lets talk about what Bloom actually does, earnings, why it fell off a cliff, the bull case and the bear case.

Is it a Buy? Or Further to fall....

2 min video