Seth @setheatonAS

$AMD channel checks, Q3 2026: demand is strong Digging into @AlphaSenseInc channel checks on $AMD, drawing on roughly two dozen expert calls with distributors, server OEMs, integrators, and AI cloud providers. The signal is another beat for AMD, but the story is demand-positive and supply-constrained, not pricing-led. Key debates around component availability and the Helios ramp remain top of mind going into the quarter. Full Breakdown ⬇️ research.alpha-sense.com/company/TK9034… $NVDA $MU

We’ve officially launched Channel Check Intelligence The best new source of Idea Gen AlphaSense began structured channel checks a bit over a year ago, already scaled to 3k per month (compliance reviewed, no embargo). Already much more than anyone could read but high signal if you can make sense of it. Channel Check Intelligence makes sense of it —> what sectors, companies are inflecting, pricing / invy better or worse etc. Not only the numbers, but the why. CCI is another form of pre-compute where we use continually use LLMs to structure the data once, for everyone. Soon, when you build your Earnings Previews with SuperAnalyst, the system will know to bring in CCI - and even use as an input to the assumptions in your model - without needing to rebuild the analysis from scratch (accuracy, time, tokens) We are investing aggressively in scaling and development -- it's going to get pretty crazy in a year.

@AlphaSenseInc channel checks on $NOW show a healthy demand backdrop: renewals are strong, expansion is robust, and AI driving pipeline. But experts see a push on pricing and packaging (new Foundation, Advanced, and Prime tiers, plus consumption models) just as budget scrutiny and data readiness are in focus. Full Breakdown ⬇️ research.alpha-sense.com/company/TK5950… $MSFT $TEAM $CRM

$SKHY is riding an AI-driven memory supercycle, how long is that cycle? @AlphaSenseInc channel checks show demand for high-end memory far outstripping supply, fueled by hyperscaler capex, sovereign data center builds, and next-gen AI accelerators like $NVDA’s Blackwell and Vera Rubin. SK Hynix holds a technology lead in HBM3E and HBM4, but the debate into earnings is its defensibility as Samsung and Micron tighten the race, while Chinese competitors gain ground in commoditized segments. $NVDA $MU Full breakdown ⬇️ research.alpha-sense.com/knowledge-work…

@ConorPowerAS Good note in retrospect!

Dig into what our experts are saying ahead of $LRCX fiscal 1Q earnings below

michelle brophy @michbrophy

3 weeks ago

Lead times at $LRCX are stretching, and AI is the reason. Lam is at the epicenter of a multi-year AI infrastructure super cycle driving capacity expansion. @AlphaSenseInc channel checks are capturing what experts are seeing: stretched lead times for advanced AI and HBM, and firm

1 1 6 1K 4

$NBIS robinhood:0x5f10a1c971b69e47e059e1dc91901b59b3fb49c3 - are neoclouds a viable alternative to hyperscalers in the long term? robinhood:0x5f10a1c971b69e47e059e1dc91901b59b3fb49c3 $25B+ of new commitments signed just this quarter. $NBIS run-rate $3B in Q2 with 2 px increases last three months. On the flip side, carrying high debt to finance $NVDA GPU fleets and capacity. AlphaSense is watching: → First 12-18 month deal renewals coming in '27. → Debt coverage →Pricing power trends as supply catches up Broke down the key debates using @AlphaSenseInc latest research. 👇

$TXN $ADI $SMH @AlphaSenseInc channel checks are tracking TI's positioning across AI infrastructure, industrial automation, automotive, and aerospace/defense. The picture that emerges is a company betting big on scale: TI built inventory while peers destocked, is transitioning to 300mm wafers for a structural cost edge, and is riding explosive AI data center demand (some experts cite >100% growth). But it's not without risk. Internal-assembly model means real fixed-cost exposure if AI spend slows, and China's local push has the potential to reshape the competitive map. Here's what AlphaSense channel checks are saying this quarter, and what to watch next 👇 research.alpha-sense.com/knowledge-work…

$ASML sits at the center of the AI infrastructure buildout, and @AlphaSenseInc channel checks make one thing clear: demand continues to outrun supply in a big way. EUV system demand is outpacing supply, with lead times stretching toward two years. Demand is increasingly driven by AI, HBM and leading-edge node transitions, with 70-80% of new orders tying back to these applications. AlphaSense channel checks are tracking these trends across ASML and the broader semicap sector this quarter: research.alpha-sense.com/knowledge-work… $TSM

$NET $FSLY $AKAM The market is focused on GPU spend for AI infrastructure. There's a shift happening one layer over, at the edge and @AlphaSenseInc Channel Checks are picking it up. As AI agents, crawlers and automated M2M traffic multiply, they're hitting security, compute and API layers hard enough to show up as real, incremental budget.

$PANW reports earnings this week. AS channel check experts are bullish on their current qtr PANW-related business w/ 19/21 experts indicating meeting or exceeding expectations, driven by intensifying demand for AI security and a successful platformization strategy taking shape

michelle brophy @michbrophy

3 months ago

$PANW's platformization strategy is resonating per @AlphaSenseInc checks: deal sizes growing YoY, CIOs cutting vendors, AI evals up YoY in enterprise. Question into earnings: can they keep growing deal size while defending a px premium vs. cheaper rivals?

1 1 5 359 0

This aged well… $NVDA reported record F2Q rev of $96.22B and forecasted 70% growth for FY28. Healthy mix of contributions from both hyperscalers and ACI&E. Fun comments from Jensen about AGI as well 👀

Seth @setheatonAS

2 months ago

AS channel checks point to a solid beat quarter for NVIDIA, even against elevated investor expectations, with 13/13 experts meeting or beating their NVIDIA-related business in F2Q, driven in part by current Blackwell demand and Rubin demand following suit in 2H. EC incoming…

0 0 1 258 0

AS channel checks point to a solid beat quarter for NVIDIA, even against elevated investor expectations, with 13/13 experts meeting or beating their NVIDIA-related business in F2Q, driven in part by current Blackwell demand and Rubin demand following suit in 2H. EC incoming…

$WDAY heading into Q3: AI leading to net positive picture per @AlphaSenseInc checks: ✅ 50% YoY quota growth reported by some, Sana landing well as AI "front door," AI deals ~50% larger, 25-30% of accounts piloting agents ⚠️ Cycles stretching due to budget, ICVs down, discounting up to 25%, Flex Credit transition creating friction Swing factor: pilot-to-paid conversion

NEW EVENT: AI Investing Forum, NYC Sep 17th Since our first AI webinar nearly two years ago, I have had the opportunity to have many conversations with builders at the intersection of investing & AI. It has been a fascinating project and a fun endeavor for me personally (I love teaching young investors, but the 56th time explaining a P/E ratio doesn't particularly scratch my itch for adventure). And my conviction is growing that we are at a key inflection point for AI in the investment process due to three evolving & reinforcing curves: 1) Capability: of frontier models, shifting from answer engines to work engines, and the Fable/Sol/Kimi diffusion moment that is currently happening (particularly around quantitative & Excel read/write capabilities) 2) Economics: of inference, and the ability to create ambient & persistent digital analysts leveraging open-source models with routing to frontier intelligence only where necessary (i.e. I don't need Fable to extract numbers from an 8-K). Throw latency / run-time improvements into this bucket. 3) Connectivity: of institutional-grade context, both external & internal, via the maturation of the MCP pathway, innovation of headless RMS systems, facilitating structures like knowledge graphs & ontologies, and the reducing friction around local model hosting & post-training that appears on the come. Enhanced by much better frontier model adherence to granular Skills. (It seems obvious to me for as well that the direct LLM approach for investors is structurally flawed and a very exciting application layer for investors is set to emerge, as it has in the legal profession, but that's a tweet for another day). For a lot of the last ~24 months, my unsatisfying counsel to funds that have sought it is that the best decision on implementing AI could be "wait and watch", stay nimble & ready to lift & shift, for risk of getting run over by Sutton's Bitter Lesson. Nearly every early adopter of AI in Investing has obsoleted early systems (generally with scar tissue of wasted time, money & wasted investor attention/credibility). I believe the time to "wait & watch" is nearing its end, and it is nearing the time to "build aggressively". In that spirit, I am founding a new business called Forward Fundamental to take what I'm good at (decomposing investment process, codifying investor taste & investor training and enablement) and help facilitate the emergence of the harness / application layer for investors (more on that later), leaning into our podcast Invest With AI, and working with leading vendors to collaborate on some exciting events & strategic partnerships. With that said, I am very excited to announce the AI Investing Forum, presented by Fundamental Edge and sponsored by AlphaSense. The AI Investing Forum is an off the record opportunity to hear from four leading builders at the intersection of AI & Finance: > Jack Kokko, CEO of AlphaSense > Dan Bookstaber, Head of Product at Freestone Grove Partners > Rich Falk-Wallace, CEO of Arcana (fmr Viking/Citadel) > Alex Izydorczyk, Partner at NX1 (fmr Coatue) I will kick off the event with a short "State of AI in Investing" presentation then guide the speakers through fireside discussions. While I expect that portion of the evening to be exceptional, I am really excited to get a group of builders together post firesides for networking, idea sharing & connection. I hosted a small AI mixer over the summer and we had overwhelming demand. It was an exceptional event, and it gave me the bug to think bigger and do more. So, here we go. This will be an invitation only event where you can request an invitation. Strong bias is towards attendees actively building AI processes on the asset management side, though we will consider all invitation requests. Thanks to the generosity of AlphaSense, this is a free event. If this is interesting, please register / request invitation via the link in replies. Thanks and hope to see you there! Brett

$PANW channel checks in AlphaSense - Strong 12/12 met or beat plan (Now synthesized w/SuperAnalyst Skill)

Hermès trades at ~40x earnings and analysts call it "justified." That's brand loyalty dressed up as a DCF. An ex-Prada board member and an LVMH exec gave me their read on luxury's valuations. Full report: alpha-sense.com/resources/repo…

$PANW's platformization strategy is resonating per @AlphaSenseInc checks: deal sizes growing YoY, CIOs cutting vendors, AI evals up YoY in enterprise. Question into earnings: can they keep growing deal size while defending a px premium vs. cheaper rivals?

@jeremie0117 The best analysts are more dangerous than ever. AI search across transcripts, filings, expert calls and market data means one person covers ground that used to take a team. Seeing this at AlphaSense every day.

Excited to announce Alphasense’s latest funding round and crossing $600m ARR. I’m also flat out giddy to officially announce SuperAnalyst, our agentic platform, along with the release. The first artifact I created came up with an est for KR SSS & GMs by pulling historicals from Canalyst models, building 2 year / 3 year stacks, sending an agent to go back through the last few years of results and annotate impacts (calendar, weather, etc), pulled the AlphaSense channel checks, and triangulated to est for the upcoming quarter. I then asked it to research key debates on HD and spin up subagents to research, loop, and weigh evidence on each of the top 3 debates. We’re able to automate the monitoring / push of new information coming out impacting those key debates due to our indexing of the data. Our vertical integration, architectural choices, and focus on context engineering allow this to be accomplished with high token efficiency. Efficiency is something you’ll hear a lot more. A 5-10x efficiency edge was nice in chat but compounds in long running tasks. With the explosion of agents, efficiency literally becomes intelligence. A more efficient system can run more searches, test more hypotheses, call more tools, and verify more claims. In multi-step agentic workflows, strengths compound just as quickly as weaknesses. As accuracy and comprehensiveness build across each step, so do errors and blind spots. That dynamic gives SuperAnalyst an exponentially widening advantage, powered by the market's leading search foundation. We’re using the capital to double down on investment in creating the most intelligent system. Building AI optimized tools and reinvesting our NNARR into our flywheel of expert calls to constantly close information gaps.