In short: RPK: a software "have" — "not only [not] hurt" by AI, "actually probably in really good competitive positions," the kind of name that migrates back into the momentum basket and stays there.
Earlier this year investors dumped software stocks on fears that AI would replace them. RPK says the market is now sorting survivors from victims: data platform Snowflake looks strongly placed, and Twilio's story has improved while its valuation stays reasonable. Adobe, in his view, is still on the losing side. Because software has become one of the market's recent leaders ("short-term momentum") while few investors own it, these winners could keep attracting money.
26:11So there's that dynamic where you could have some of, say, the opticals, which look a little better, that might still look okay and stay within the momentum basket, where other things fall out of the momentum basket. Similarly in software: Adobe still sucks, but others — we're learning Snowflake, other things in that software basket, not only are not hurt, they're actually probably in really good competitive positions — or Twilio, where the narrative has
In short: Avoid, despite acknowledging the bull case (agents use products like Snowflake; product revenue has accelerated three quarters running). "I sort of have a cardinal rule of I don't want to fight the hard battles. Snowflake doesn't fit into any of those three buckets within software that I feel comfortable about" — security, system of record/database, and video games. With OpenAI + Anthropic run-rate revenue up from $29B to $105B this year, "that spend has got to come from somewhere and some of that has got to be software." "It's a great company, but" not a name he's interested in.
Snowflake sells cloud software for storing and analysing company data, and its stock is up about 50% this year. Niles admits the bull case — AI agents will use tools like Snowflake, and its revenue growth has sped up for three straight quarters. But he has a rule: don't fight the hard battles.
His reasoning is budgets. Companies' spending with OpenAI and Anthropic has jumped from $29 billion to about $105 billion a year, and finance chiefs have to cut elsewhere — some of it from software. He thinks only three kinds of software are safe: cybersecurity, "system of record" databases companies can't rip out, and video games. Snowflake isn't in any of them, so he passes.
39:35And over the last three quarters, you've seen revenues, the product revenues actually accelerate. And so, to your point, they seem to be one that's really benefiting right now. I sort of have a cardinal rule of I don't want to fight the hard battles. Snowflake doesn't fit into any of those three buckets within software that I feel comfortable about.
In short: Reports Wednesday. Wapner's framing is that it is the software name that never broke: "that's been key because it bucked the trend when software was going through a malaise… the stock's up almost 30% in three months" and "has also been a nice helper in the comeback of this trade — it's up more than 11% in a month." No committee position stated.
In short: One of the nine selective non-AI growth names attracting Q2 buyers — data-platform exposure bought individually rather than as part of a software re-rating.
In short: Bought with ServiceNow out of the systematic software selling — one of the names "we think have some moats." He adds the caveat that after the squeeze he no longer has "the confidence to own software in the same size."
Snowflake stores and organizes company data in the cloud — the layer AI systems have to sit on top of, which makes the "AI kills software" story a strange fit here. Bought alongside ServiceNow out of the same short-hedging sell-off. His honest caveat after the squeeze: he no longer has the confidence to own software "in the same size" he did before.
8:27Even Palantir, although we don't own it, rallied about 40% on earnings. And for those of you who don't know what happened, in late July of 2026, Ken Griffin acquired the public equity portfolio of Situational Awareness, which was the AI focused hedge fund run by the former OpenAI researcher Leopold Aschenbrenner after he suffered heavy losses.
In short: Josh Brown's final trade: "Snowflake, SNOW."
In short: Market color: up 7.5% last week and at a 52-week high today in the software squeeze. No individual committee call.
In short: A new 52-week high, up 11% on the week and ~20% in three weeks. Link: "product revenue growth accelerated last quarter, and given all the new products they have it's actually going to do another 30 to 34% in product revenue growth. RPO and bookings are also growing double digits, and margins still have upside as they cut costs in some areas and they have pricing power in others."
Snowflake stores and analyses corporate data in the cloud, and it hit a 52-week high — up 11% this week and around 20% in three. Stephanie Link's case is that growth is accelerating rather than fading: product revenue growth picked up last quarter, and with new products she expects another 30–34%. Committed future contracts ("RPO," remaining performance obligations) and bookings are growing double digits, which is the visibility part, and margins can still improve as it trims costs in some areas while raising prices in others.
In short: Spyglass Growth Strategy: a top contributor kept as a core position. First-quarter results "exceeded consensus expectations for both revenue and earnings," and the specific tell they cite is attribution — "Snowflake saw enough traction with one of its early AI products to raise guidance while attributing the increase specifically to that product," which is a harder claim than generic AI optimism. "We believe Snowflake's long-term potential remains misunderstood by most investors." They trimmed on share-price appreciation but it "remains a core position."
Snowflake sells software that lets a company keep all its data in one place in the cloud and ask questions of it. Spyglass calls it a top contributor and a core position.
The detail they single out is unusually concrete for an AI claim: Snowflake raised its guidance and said explicitly which new AI product was responsible. Most software companies talk about AI in general terms; being able to attribute a guidance raise to one product is evidence rather than narrative. They trimmed the position because the shares had run, but still think the long-term opportunity is misunderstood.
Full passage: premium transcript (PDF).
In short: Jason owns it and a Citi software top pick (with MDB, PLTR): a strong last quarter (EPS +68%, revenue +33%), 30% growth North Star, a new AWS deal; consumption model can be lumpy, but data-warehousing + the whole-ecosystem CapEx makes it "worth owning." +21% YTD — proof software ex-cyber weren't all dogs.
Snowflake runs a cloud "data warehouse" — where big companies store and analyze their data — which is central to AI, since models need well-organized data to work on. Jason Snipe owns it and notes Citi just named it a top software pick. After a slow start to the year it reported a strong quarter (earnings up 68%, revenue up 33%) and targets 30% revenue growth, helped by a new deal with Amazon's cloud.
One quirk he flags: Snowflake charges by usage ("consumption"), so results can be lumpy quarter to quarter. But with all the AI-driven spending flowing through data infrastructure, and the stock up 21% this year, he thinks it's clearly "worth owning" — a reminder that not all software outside cybersecurity has been a dog.
In short: Named with IBM and Synopsys as one of the out-of-favor "mission-critical software" names where the relative value sits now that software (IGV) is down 17% while the SOXX is up 85%.
Snowflake runs the "data cloud" — software companies use to store and analyze huge amounts of data, increasingly to feed AI. Link lists it alongside IBM and Synopsys as an out-of-favor, mission-critical software name. The pitch isn't about Snowflake specifically so much as the category: with software badly lagging chips this year, she's hunting in the names whose product is hard to replace.
In short: Santoli: up ~5% in the same "suspect" software-name snapback.
In short: Counter-example to Palantir's word-of-mouth: Snowflake (with Databricks) had ~70% of staff in sales — heavy selling as a sign of weaker organic product pull.
12:23Palantir at six, they had about three people in their sales team. Meanwhile, you had Snowflake and Databricks, and basically about 70% of the people in the company are sales people. And so, word of mouth spread is indicative as to the true value of a product.
In short: The consumption winner. Product rev +34% to $1.33B (accelerating from +30%, beating its own projection by 7pp); FY product guide raised to $5.84B (+31%); a 5-yr $6B AWS commitment (Graviton + custom AI accelerators) supports a 75% product gross margin. Q rev +33% to $1.39B ($70M beat), non-GAAP EPS $0.39 ($0.07 beat), NRR 126%, 46 customers >$1M (vs 26 a year ago). Cortex Code >7,100 accounts; Natoma (MCP) acquired to govern what agents DO (acting agents consume far more compute). RPO +38% to $9.21B but missed $9.43B — backlog matters less for consumption. "Agents increase the need for governed data — exactly where Snowflake sits."
Snowflake sells a cloud "data platform" — companies pour their data into it and pay based on how much computing they use to query and analyze that data. That last part is the whole thesis: it's a consumption business. You're not buying a fixed number of seats (logins for people); you're billed for usage. So when AI agents start running queries around the clock, Snowflake's revenue goes up — the harder the AI works, the more the customer pays. That's the opposite of seat-based software, where AI doing the work might mean a company needs fewer human logins.
Two details make the quarter strong. First, the AWS deal: Snowflake committed $6 billion over five years to Amazon's cloud, using Amazon's own efficient chips (Graviton CPUs and custom AI accelerators) to lower its computing costs — which is how it protects a fat 75% gross margin on its product. Think of it as locking in cheap raw materials. Second, the Natoma acquisition: "MCP" (Model Context Protocol) is a standard way to let AI agents safely connect to company systems, and Natoma helps govern what those agents are allowed to do, not just what they can read. Agents that take actions consume far more compute — so better governance literally drives more billable usage. App Economy's read: as AI agents multiply, every company needs governed, secure, scalable access to its data, and that's exactly the spot Snowflake occupies.
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