"We are initiating coverage of Infleqtion with a Buy rating and a $22 price target, implying ~70% upside from Wednesday’s close. Every qubit fights the same battle: holding a fragile quantum state together before heat, vibration, or measurement itself destroys it.

Quantum computing is a war against entropy. Infleqtion, like everyone else, is engaged in that war, but it also does what no public peer can: it sells the other side. The same environmental sensitivity that ruins a qubit makes a quantum sensor exceptional, and Infleqtion monetizes it today through atomic clocks, RF receivers, and inertial navigation sold into defense and aerospace. Infleqtion’s dual model anchors our Buy.

We like the Infleqtion story for four key reasons: INFQ’s neutral atom approach offers compelling scaling and error-correction flexibility. Neutral atoms have practical advantages. Scale is achieved by trapping more atoms with lasers, not by fabricating more chips, so growth is an optics-and-control problem rather than a manufacturing-yield one. Every atom of a given element is exactly identical, so unlike solid-state qubits there is no chip-to-chip variation to engineer around.

Sensing is a key differentiator and a primary beneficiary of the June 22 executive order. Infleqtion is one of very few public names with a commercial sensing portfolio across timing, RF, and inertial navigation, with live defense programs across all three AUKUS partners, a first-of-kind Tikker demonstration aboard a Royal Navy uncrewed submarine, and a NASA Cold Atom Lab supplier relationship.”

- Analyst: Kingsley Crane

$META is reportedly developing a cloud business to sell access to excess AI compute, per Bloomberg.

The internal initiative is called Meta Compute.

The plans being considered:

AI model access hosted on Meta infrastructure, similar to AWS Bedrock

Raw AI compute capacity, closer to CoreWeave

Developer access to Meta’s data centers, chips, and models

Napkin math for potential revenue here for META:

1GW of compute capacity
$20B revenue per GW
$20B total revenue
85% operating income margin
$17B operating income
$14.6B net income
$5.69 EPS
16.3% accretion to FY27 consensus EPS

$OKLO's Groves Isotope Test Reactor received DOE approval for its Documented Safety Analysis.

This is the final safety basis approval that follows the earlier Nuclear Safety Design Agreement (NSDA, approved March 2026) and Preliminary Documented Safety Analysis (PDSA).

With the DSA now approved, the project shifts from the documentation/design-construction phase into DOE’s final pre-startup activities: readiness review, startup approval, fuel loading, and first criticality.

Oklo is targeting July 2026 for first criticality.

CEO Jacob DeWitte highlighted that Groves is the first advanced reactor project to receive DSA approval on privately owned land.

The Groves facility is essentially a pilot project focused on domestic isotope production for medical (cancer diagnostics/treatment), industrial, research, space, and national security uses. It aims to reduce reliance on overseas or aging sources while generating operational data to support future commercial reactors.

Qualcomm $QCOM plans to bring parts of its new data-center chip architecture to smartphones, PCs and cars, per Semafor.

Their High Bandwidth Compute architecture stacks memory & compute vertically to improve data flow, potentially enabling more local AI models and always-on agents on mobile devices.

Based on their investor day presentation, it seems to me like they’re aggressively diversifying away from their traditional smartphone (handset) chips business to becoming a broader AI platform company across the entire compute spectrum imo. This includes on-device inference/edge AI to data centers, automotive, industrial systems, robotics, etc.

This is expected to drive massive new demand for efficient inference compute, both on devices (personal agents) and in data centers (scaling those agents), plus “physical AI” in cars, robots, and factories. They announced huge diversification targets including $40B non-handset revenue by FY29 (up from $22B prior), over $15B from data center AI by FY29, $5B data center revenue in FY27, and EPS above $18 in FY29.

According to $QCOM, the combined TAM for these opportunities is roughly $1.7 trillion by 2030. Important to note that these are long-term targets (not immediate quarterly guidance). They reflect management’s view of secular tailwinds from distributed AI compute over the next 3–5+ years.

A Korean tech news outlet (ET news) published the article today, June 25, 2026, reporting that Samsung had published their research (an IEEE paper titled “Analysis of System-Level Thermal Characteristics of Hybrid Cu-Bonded HBM with 2.5D Advanced Packaging”) showing the thermal management advantages of their Hybrid Copper Bonding (HCB) technology over traditional Thermo Compression Bonding (TCB) for next gen HBM4E memory.

Samsung’s HBM4E and hybrid bonding plans already existed with HBM4E and Hybrid Copper Bonding (HCB) tech showcased at Nvidia GTC in March 2026, but this system-level thermal validation from the IEEE paper is new and exciting to me. In the IEEE study, they used multi-scale modeling and test chips in server-like conditions. They showed clear benefits like lower hotspot temperatures, reduced thermal interference between memory stacks and logic, more than 15% thinner stacks, and better power budgets for 16+ layers of HBM. This supports higher power budgets and reliability in servers under air-cooling conditions.

Infographic explaining Samsung's Hybrid Copper Bonding (HCB / hybrid bonding) advantages for HBM4E. Made by Nanobanana

The broader trend I’ve noticed in the industry is a gradual shift toward hybrid bonding (direct Copper-to-Copper and dielectric bonding, DBI for short) for advanced packaging in HBM, chiplets, and 3D integration (HBM-on-GPU). It replaces or augments traditional thermo-compression bonding (TCB) / micro-bumps for finer pitches, better thermal & electrical performance, and thinner stacks. Major players like Samsung, SK hynix, TSMC, Intel, and Micron, are advancing this. In my opinion a the true winner agnostic beneficiaries of this are companies that provide equipment, metrology, IP, testing, and specialty manufacturing.

I’ve owned and continue to own $ONTO, $COHU, and $RMBS, specifically to get exposure to the Hybrid Bonding supply chain. All these stocks have more than doubled for me and I believe this theme/narrative is just starting to develop. There is another angle that seems very attractive to me right now. I'll talk about the stock and my thesis behind it in Part 2 if people are interested.

$IBM just unveiled research-stage sub-1nm chip technology using a 0.7nm “nanostack” 3D transistor design.

The company says it could pack nearly 100 billion transistors on a chip the size of a fingernail — delivering up to 50% more performance or 70% better efficiency vs. its 2nm node.

I wrote part 1 of my thesis on solar as a sector on another subreddit, but I don’t think people were interested in reading the research as much there :(. I broke down the trend we’re seeing with additional utility-scale generating solar capacity being brought on by U.S. developers and power-plant owners, how solar had one of the largest power generation requests based on Texas ERCOT’s February 2026 generator-interconnection queue, how California has already shown the possibility with solar and much more. If you’re interested in the detailed research you can find it on my page easily or not (totally up to you).

In this post I wanted to share with you guys (cause I think people actually appreciate reading and understanding the research here more) which solar names I’m interested in and why.

Potential Good Risk-to-Reward Exposures (In My Opinion)

One thing to note about the case I’m making here is that I’m not claiming “Solar will power data centers.” My claim is specifically, “Data center load growth is forcing the U.S. power grid to add capacity quickly, and solar + battery storage should capture a significant share of that incremental capacity.” With this distinction made, we can determine the supply chain:

- Utility-scale solar
- Battery storage
- Electrical balance of systems
- Grid interconnection
- Domestic manufacturing
- Power electronics
- Transformers, switchgear, cabling, and substation infrastructure
- Behind-the-meter and near-site power systems for hyperscalers

Last year my best picks in this supply chain were battery storage players. I bought $ENS at ~$120/sh and $AMPX at ~$9/sh. Both those plays have done quite well and I still continue to like both of them, but in terms of solar specific names the two names I like are, $SHLS and $TE. Let’s talk about why…

Shoals Technologies

Shoals Technologies is not just a solar-panel story. They sell Electrical Balance of System (EBOS) infrastructure. This includes the components that move current from solar panels to inverters and ultimately to the grid. Shoals describes EBOS as mission-critical infrastructure, including cable assemblies, fuses, combiners, disconnects, recombiners, wireless monitoring, junction boxes, and their plug-and-play system architecture.

In the last quarter (Q1 2026), they reported almost 75% revenue growth YoY, $140.6 million, from $80.4 million. Adjusted EBITDA rose to $21.1 million, and backlog plus awarded orders reached a record $758 million, up 17.5% YoY. Management guided Q2 revenue to $150–170 million and raised full year 2026 guidance to $600–640 million of revenue and $118–132 million of adjusted EBITDA. This imo is the cleanest evidence of my original thesis and I think a really good exposure. It shows, in my view, that solar and a solar company can grow even through the political noise.

Their data center angle is what’s attractive to me. Shoals says their solutions support utility-scale solar, battery storage, and data-center power systems, and they market their prefabricated plug-and-play architecture as useful for mission-critical infrastructure. The reason this matters is that data-centers are becoming more like utilities when it comes to power in my view. They need large electrical yards, battery systems, high-current DC architecture, rapid deployment timelines, and extreme reliability requirements. EBOS, I believe, is directly relevant wherever large solar and storage systems are being built to support data center load.

Their current enterprise value is ~$1.85B, and the stock trades roughly at 3x sales, ~15x forward EBITDA, ~19x trailing EBITDA and with ~$170M in debt. Using peers as benchmark, $NXT trades at ~28x, $APH trades at ~27x, and $ARRY trades at ~18x, trailing EV/EBITDA. With the specialized niche they offer with EBOS and the 50-70% guided revenue growth, backlog converts, stabalizing tariffs, and margin recovery, $SHLS looks like a good risk-to-reward play for me to express my solar thesis.

The main risks in my opinion are: gross margin pressure, tariffs, legal/warranty overhangs, project timing, competition, customer concentration, and whether data center demand translates into actual orders rather than just broader sector demand.

T1 Energy

T1 Energy is a different and very interesting kind of bet, in my opinion. This is a crowd favorite name, recently Leupold disclosed his stake in it too. T1 is trying to build an integrated U.S. solar and battery supply chain. They operate the G1 Dallas solar-module facility and is pursuing vertical integration, including domestic solar-cell manufacturing.

In Q1 2026, they reported $177.6 million of net sales, up from $53.5 million in the prior year period. Management maintained 2026 G1 Dallas production guidance of 3.1–4.2 GW and said customer demand for G1 and G2 production in 2027–2028 covered more than 100% of their planned capacity.

The G2 Austin cell facility is the strategic asset for them in my view. They’ve said that Phase 1 is designed for 2.1 GW of solar cell production, with initial cell production targeted for Q4 2026. If successful, I think it would reduce reliance on imported cells, improve domestic positioning, and potentially make T1 more valuable under U.S. supply chain and tariff regime.

They announced acquisition of KORE Power which I think gives them exposure to data centers and battery storage. They’ve said that KORE gives them an entry point into BESS integration, software, and a renewables & infrastructure division that has supported more than 1,100 BESS projects globally. They expect the acquisition to contribute $15–20 million of EBITDA in 2027, assuming the deal closes and performs as expected. This is a plausible pivot that makes them interesting to me. Solar modules alone are more commoditized, but solar + domestic cells + energy storage integration + data center infrastructure says a much better story in my opinion.

But there are risks here. T1 energy is capital intensive, manufacturing execution is not the easiest of tasks, and the balance sheet is a bit complicated. As of Q1 2026, T1 reported $123.7 million of cash, cash equivalents, restricted cash, and restricted cash equivalents, but only $46.4 million of that was unrestricted cash. They also had meaningful debt and liabilities in my opinion.

So $TE is not a simple “solar is undervalued” story. I view them closer to an industrial policy/manufacturing ramp with meaningful operating leverage. If G1 ramps, G2 qualifies, customers convert, and KORE gives credible storage exposure, the upside can be meaningful, in my opinion. The risks here are finances tightening, policy shifts further against domestic credit monetization, and/or manufacturing margins disappoint. This, in my view, is definitely a higher-beta and more speculative story than $SHLS, but for me I like the risk-to-reward.

With that I thank you for reading my thoughts and opinions. I’m typically a micro-economic guy, meaning I post about individual stocks and sectors that I think are interesting. I tend to do a lot of research (more than what I posted here) and build my conviction. I hope this research helps you understand these industries better, and gives you an insight on how I look at equities/investments.

Please remember that I can be wrong and make mistakes. I am a human, I do often miss key facts and once they are know I will change my views. Please do not use this as financial advice. This is NOT FINANCIAL ADVICE! I’m just some guy on the internet who likes to research companies and industries. You should use what I write here as educational or entertainment, nothing else. I’m not a financial advisor. Do your own research before making any investments.

$MU Revenue: $41.46B (Est. $35.5B)
Adjusted EPS: $25.11 (Est. $20.4)
Adjusted Gross Margin: 84.9% (Est. 81.8%)
Adjusted Net Income: $28.86B
Adjusted Operating Income: $33.68B
Adjusted OpEx: $1.52B
Investments in CapEx, net: $7.1B
Cash, marketable investments, and restricted cash: $30.2B

Q4 Guidance looks fantastic imo:

Revenue: $50.0B ± $1.0B (Est. $43.4B)
Adjusted EPS: $31.00 ± $1.00 (Est. $24.3)
Gross Margin: Approximately 86% (Est. 83%)
OpEx: Approximately $1.65B
Operating Cash Flow: $25.39B
Adjusted FCF: $18.3B

Commentary from CEO, “Micron’s record fiscal Q3 financial results and even stronger outlook for Q4 reflect the strategic value of memory in the AI era.”

HBM4: In high-volume shipments for lead customer platform; qualification samples shipped to multiple end-customers

HBM4E: Volume production expected in calendar 2027

G9-based PCIe Gen6 high-performance SSD: In high-volume production

High-capacity 245TB QLC SSD: Shipments commenced

Based on this, it makes $MU the top 5 company based on revenue lol.

Nokia ($NOK) is advancing autonomous networks by running its Autonomous Network Fabric on AWS. This will give telecom operators access to advanced AI and cloud-based tools designed to reach Level 4 network autonomy, with availability targeted for later in 2026.

The platform brings together intent-based service orchestration, AI-driven anomaly detection, root cause analysis, automated closed-loop resolution, digital twins, and agentic AI capabilities.

Separately, Nokia has completed a PoC with Databricks to create a unified, cloud-agnostic telecom data platform. The goal is to channel real-time network data directly into AI agents for faster, automated decision-making across different network domains.

Nokia notes that its existing autonomous networks portfolio has already delivered strong results for operators, including automation rates above 90% and up to an 85% reduction in the time required to roll out network slices.​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​

I wrote a lengthy article on why I think select software names might be unreasonably getting sold off due to AI related pricing power headwinds. In that article I wrote my thesis on $FIVN (there are more names I like in this space as well, just haven’t had a chance to condense my research in a publishable format yet :/) and why I think there is a big opportunity for earnings growth and gross margin expansion.

This morning at Customer Contact Week / CCW in Las Vegas, Five9 announced a major new release of their Voice AI Agents, positioned as the next evolution of agentic self-service. It runs on a brand new, purpose-built architecture designed specifically for the “agentic era,” moving far beyond traditional scripted bots and legacy Interactive Voice Response (IVR) systems.

These agents are built to reason, take real actions, and solve complex customer requests while enabling smooth, contextual handoffs to human agents when needed.

Their new research shows that 65% of organizations are now implementing/releasing at least one AI use case in CX. Self-service automation is a top priority (42%).

Early rollout exceeded containment targets, reduced handle times, and delivered more consistent human-like interactions. One of their customers, PODS, expects the agents to handle over 100,000 service calls by end of the year.

Analyst Maribel Lopez (from Lopez Research) highlights the industry shift from basic AI responders to true agentic systems that complete tasks, plus the critical need for governance and controls at scale.

Main Features & Capabilities of the New Agentic Platform

1. Human-like voice interactions: Low-latency streaming, natural turn-taking, interruption detection, multilingual support, and strong background noise handling.

2. Action-oriented AI (not just chat): Secure tool-calling to connect with enterprise systems. For example, authenticating customers, updating records, processing transactions, or completing tasks in real-time.

3. Seamless AI + Human collaboration: Full conversation context transfers instantly when the call is being transferred from an agent to human using Five9’s platform.

4. Enterprise-grade governance & trust: Built-in guardrails, automated post-call AI evaluations, LLM blinding (to protect sensitive data), and workflow verification.

5. New AI Agent Studio: Unified environment for building, testing, deploying, monitoring, and improving agents (includes call testing, versioning, rollbacks, and post-call analytics).

6. Platform advantage: Powered by the proprietary Agentic Voice Switch architecture, natively integrated into Five9’s carrier-grade telephony platform (no BS add-ons). Data, knowledge, and orchestration are shared across the full Intelligent CX Platform.

This is the quote from CEO Ajay Awatramani:

“Five9’s new Voice AI Agents represent a breakthrough in AI, delivering natural, human-like interactions with exceptional responsiveness, accuracy, and scale, seamlessly orchestrated with human agents on the Five9 Intelligent CX Platform.”

Conclusion

This, in my opinion, is a significant product announcement from them directly my thesis around production and deployment of agentic AI for voice self-service, with strong emphasis on real actions, human collaboration, and scalability.

People often think of Five9 as another chatbot customer service provider, but this goes against that narrative imo. In my view the market is severely mispricing their platform and the need for AI voice agents in customer service.

As always I can be wrong, I don’t have a crystal ball, but I’m at least putting my money where my mouth is lol. None of this is meant to be financial advice! I’m just a guy on the internet sharing my thoughts and opinions on the market.

During my undergrad years, I remember Photovoltaics (PVs) and solar were the talk of the town. I recall almost all of my professors and their students were working on designing solar cells that would yield high power conversion efficiency at low costs. That was how I was introduced to the world of semiconductors (back in 2018 lol). I worked quite a bit on Perovskite solar cells (unimportant to this discussion) as an undergrad and my first year as a PhD. I knew the capabilities AND limitations of solar back then and always thought of them as interesting, but limiting without Battery Storage Systems (BESS). So why am I sharing this now? “Who cares if you did your silly little solar project?”

Well based on recent trends seen in the U.S. power grid build out and the increase in demand for more data-center related power capacity, I think solar is setup for a significant re-rating.

The policy overhang is real

Over the past year and a half (since the election) there has been a significant overhang on Solar companies. The Trump administration has not been shy in showing their bias toward solar. The White House has explicitly framed wind and solar subsidies as market-distorting and directed several U.S. agencies to restrict support for solar credits where possible. The July 2025 executive order specifically called for enforcing the repeal or modification of wind and solar tax credits under the One Big Beautiful Bill Act.

The tax-credit regime has also become more hostile. The IRS Notice in 2025 restricted the use of the previously allowed 5% spending safe harbor, forcing larger projects (like wind and most solar >1.5 MW) to rely solely on the physical work test along with the foreign entity restrictions penalizing prohibited foreign entity (PFE) and Foreign Entity of Concern (FEOC) projects for receiving material assistance from restricted entities. Solar Energy Industries Association (SEIA) says that to qualify for the 48E and 45Y credits, many solar projects must either begin construction by July 4, 2026 or be placed in service by December 31, 2027, with additional FEOC restrictions beginning in 2026. Treasury and IRS also issued guidance on PFE restrictions affecting 45Y, 48E, and 45X credits.

Residential solar is under even more direct pressure in my opinion. The IRS said the Residential Clean Energy Credit (RCEC) is not available for expenditures after December 31, 2025.

These are all the policy and political overhangs that, in my opinion, have suppressed valuations for lot of these solar companies. I believe they are trading with a “political risk” discount, and for a legitimate reason. The tax-credit uncertainty, FEOC compliance, tariff exposure, DOE hostility, permitting friction, all in my opinion fuel investor fear that the sector’s fundamentals are politically fragile. However, in the midst of all this bearish sentiment, the one thing that, in my opinion, is not being priced in is that the power grid data is not cooperating.

Capacity Additions Could Overwhelm the Political Narrative

The most important data point for me is national. The U.S. Energy Information Administration (EIA) expects U.S. developers and power-plant owners to add 86 GW of new utility-scale generating capacity in 2026. This would be the largest annual addition in EIA’s dataset so far. What’s more interesting is that solar is expected to be 51% of those planned additions, with batteries at 28% and wind at 14%. Developers plan to add 43.4 GW of utility-scale solar in 2026, up 60% from 2025. Texas alone accounts for about 40% of planned new solar additions, and Texas is no liberal state, at least in 2026 lol.

Source: EIA

This is the core of the bull/value case I’m trying to make; even under immense political pressure, there is increasing demand for additional solar capacity for the U.S. power grid.

SEIA and Wood Mackenzie’s Q1 2026 data strengthens the point. The U.S. installed 7.8 GW of solar capacity in the first quarter, and solar plus storage represented 91% of new electric generation capacity installed during the quarter. Their report also says that contracts for utility-scale solar increased 15% YoY, driven largely by, you guessed it, power demand for AI hyperscalers and data-centers. Notably, states that voted for Trump in 2024 accounted for 74% of solar capacity installed in Q1 of 2026.

That last point is important because it shows that solar adoption is no longer just a California or a liberal state climate based policy push. It is now pushed by power, interconnection, and time-to-capacity demand for AI advancement. Texas, Arizona, Florida, Ohio, Indiana, Michigan, and Mississippi are not building solar because they are trying to signal progressive energy politics. They are building it because, in my opinion, solar is fast, modular, cost-effective (this is debatable), and increasingly paired with batteries.

This is where, in my view, the political narrative and the bear case starts to break down. The federal government can get rid of the incentives for the sector, but grid operators, utilities, developers, and hyperscalers still need to bring on capacity. In fact, solar companies may no longer need those incentives or favorable policy narratives to show growth. There might be/already is a demand for them.

ERCOT is the Clearest Evidence

Texas is the most important case study because it breaks the notion that growth in solar companies is merely a blue-state subsidy artifact. As of Electric Reliability Council of Texas’s (ERCOT’s) February 2026 generator-interconnection queue, the system had about 453.6 GW of active generation requests. The largest categories were: Energy storage with 177.6 GW, Solar with 162.9 GW, Natural gas with 60.7 GW, and Wind with 47.8 GW. This shows that solar and energy storage represented more than 76% of power generation seeking interconnection.

EIA also expects solar power generation in ERCOT to surpass coal for the first time in history, in 2026, with solar producing about 78 billion kWh versus coal at about 60 billion kWh. From 2021 to 2025, solar generation in ERCOT rose from 4% to 12%, while coal fell from 19% to 13%. EIA explicitly ties rising ERCOT demand to data centers, crypto mining, industrial electrification, and oil & gas sector growth.

Data source: U.S. Energy Information Administration, Short-Term Energy Outlook, Table 7d

This, in my opinion, is the bull case for the sector. Data-center load is quickly growing in Texas, and the resources trying to interconnect are dominantly solar and storage.

The Potential Midterm Elections Tailwind

Source: Polymarket

Recent prediction markets trends have supported a “blue-wave” during the midterm elections of 2026. A Democratic midterm win, or even a narrower Republican majority, could relieve some policy pressure on solar names in my opinion. The market would likely reprice the probability of further tax-credit erosion, harsher FEOC enforcement, anti-solar executive actions, or DOE funding hostility.

But I would not make that the primary thesis.

The stronger argument, in my view, is that solar is working despite a hostility from Trump administration. If the political backdrop improves, that is upside is an optionality. The base case, however, still rests on the power grid demand for me.

Prediction markets can move sentiment, but they are not a substitute for capacity data, backlog, interconnection queues, or earnings revisions.

Data Centers Turn Solar from a Climate Trade into a AI-Power Infrastructure Trade

The traditional narrative with solar companies has mostly been about decarbonization, subsidies, ESG, and residential adoption. Remember those Tesla Ads about solar roofs… That narrative got hit hard by higher rates, net metering changes, policy risks, and weak residential adoption. Don’t believe me, pull up a chart for most popular solar names, $RUN, $ENPH, $FSLR, $SEDG, $ARRY, etc. Notice where they’re trading relative to their all-time-highs.

I believe there’s a new narrative in town…

U.S. DOE (Department of Energy) and Lawrence Berkeley National Labs estimate that data centers in U.S. consumed roughly 176 TWh in 2023, which is ~4.4% of total U.S. electricity consumption. They project data center consumption could reach 325–580 TWh by 2028, roughly 6.7–12% of total U.S. electricity consumption. EPRI’s 2026 analysis is even more aggressive. They project data centers could consume 9–17% of U.S. electricity by 2030, up from 4–5% today.

That scale, in my opinion, changes the narrative. The issue is no longer whether policymakers like solar. The issue is whether the grid can add enough capacity fast enough. Solar and batteries are not perfect, but they are available, modular, and deployable right now. That is why solar keeps showing up in the capacity addition data in my opinion. So the new narrative for solar, in my view, is “The U.S. needs a massive amount of new electricity capacity, and solar is one of the few technologies that can be deployed quickly enough to matter.”

So now that we know the reasoning behind the speculation and why solar companies have potential to re-rate, where do I see the opportunity? That's saved for PART 2...

The entire reason KOSPI was down 10% yesterday, marking it the third biggest one day drop ever, was due to memory news from SK Hynix. SK Hynix is deliberately slowing their HBM4 production ramp by delaying conversion of some HBM3E lines to focus resources on commodity DRAM, which delivers higher operating margins than HBM due to supply shortages.

The strategy is to use their established 40%+ HBM revenue lead and strong position through 2026, while commodity DRAM ASPs have risen sharply and margins could potentially reach 90%, with analysts raising earnings forecasts on broader memory pricing strength.

SK Hynix and Samsung (making up ~54% of the index) got hit hard. $SPY, because of the $MU and overall AI supply chain, has become a lower-beta proxy to KOSPI at this point, which is why you’re seeing a selloff in premarket imo.

Not Financial Advice! Just sharing my thoughts/opinions on why I think we’re seeing a selloff.

BofA now expects the Fed to hike rates 3 times this year, shifting from its prior view of no changes.

BofA sees 25 bps hikes in September, October and December, taking rates to 4.25%-4.5% by year-end.

And expects the Fed’s first rate cuts to come in 2028.

Over the past 3 years we’ve seen a huge surge in AI related equities. Markets have absolutely rewarded anything that touches this trade ever since we had the ChatGPT moment back in 2023 (the good old days). One sector that has taken a significant hit recently is $IGV (software).

Lot of investors look at software stocks and see “dead money.” In fact many of my friends whose opinions I value have been talking about never touching software names with “a 20 ft pole”, whatever that means… Valuations have come down significantly for a lot of software names from the pandemic highs, growth shows signs of slowing, and the market is skeptical that AI will completely diminish the pricing power of these companies and margins will be crushed. I get it, plenty of flashy AI stories have disappointed.

But I’m a contrarian at heart. There’s a reason why my Reddit has negative karma lol. I always play devil’s advocate and try to understand the “why” of something before attaching myself to an idea. So why am I interested in software? And which software company is speaking to me right now?

When you call a company for help, whether it’s your bank, internet provider, or retailer, you’re usually talking to someone (or now, something) in a contact center. These are the modern versions of old-school call centers. Companies track everything here: how long calls take, whether the issue gets solved on the first try, how happy customers are, and how productive their staff is. It’s one of the clearest, most measurable places where AI can deliver quick, obvious wins for businesses.

AI is capable of dramatically cutting costs for businesses here. Companies using these tools often see handle times drop by 2 minutes per call, calls fully handled by AI rise significantly, and overall operational savings in the 20-60%+ range depending on the use case. This reduces operational costs by a significant amount especially for smaller businesses.

Margin expansion for your customers, in my opinion, is one of the best win-win scenarios that can drive pricing power for a lot of companies. “Hey I know you’re spending hundreds of Billions on something you don’t really care about, but kinda sort need. I can offer you a solution that’s potentially better and 100x cheaper. Just pay me a little premium.” YES. PLEASE.

In my opinion, $FIVN is a great exposure here. Five9, in my opinion, is a clear leader in cloud based contact center software (or CCaaS). Their Genius AI suite includes a bunch of tools like AI agents that handle routine customer conversations (and smoothly hand off to a human when needed), AI that transcribes and summarizes calls, spots insights, helps agents in real-time, automates workflows, and more. It’s designed to make customer support faster, MUCH cheaper, and better.

What makes them more compelling is the fact that they own the underlying voice infrastructure that makes realtime Voice AI actually function properly. Their Global Voice network delivers low-latency calls worldwide with strong reliability and backup carriers. They also have VoiceStream, which lets audio and call data flow in real time to AI systems for things like sentiment analysis, coaching, or biometrics.

So they sell their own AI tools directly AND also help power other companies’ voice AI products. Forrester’s study of Five9 customers showed a 212% ROI and $14.5 million in net value over three years. These savings create strong customer demand: companies see clear margin improvements from lower support costs, so they’re eager to adopt and expand. That gives Five9 pricing power and stickier relationships as clients migrate from outdated on-premise systems.

On top of that, customer service hiring is growing faster than the overall job market right now. That means more demand for efficient tools to handle the workload without endlessly adding headcount.

The stock looks very attractive to me here on valuation basis with ~1.2x sales, ~6x free cash flow, 55% gross margins, almost no debt, and plenty of cash on hand. That’s cheap for a company with this kind of growth runway in my opinion.

Their latest earnings showed that AI revenue jumped 68% YoY (40% sequentially from prior quarter), now running at over $125 million annually and making up 13% of subscription revenue (up from 8% YoY). That’s tells me there’s a real inflection point here.

In short, my thesis here is that when AI handles more calls and reduces the need for human agents, the dollars don’t leave the contact center, they just shift from labor to software. Enterprises spend massively on customer support staff. Five9 sees the total opportunity as a $24 billion cloud software market plus a huge $210 billion labor arbitrage play through AI. In other words, companies won’t cut their support budgets; they’ll reallocate money to smarter tools like Five9’s platform. This, in my opinion, expands their total addressable market significantly, and the stock price at these valuations is, in my opinion, not reflecting it.

If you’re interested in more detailed breakdown you can checkout my Substack article here, where I go over some numbers and more in-depth of why I think this theme is interesting.

This is NOT FINANCIAL ADVICE! I’m just some guy on the internet who likes to research companies and industries. You should use what I write here as educational or entertainment, nothing else. I’m not a financial advisor.