The Other Bubble
We recorded 26 claims from this post. 13 were checked against evidence. 13 can’t be checked. 15 more are held. Read the post at its source.
Claims from this post (26)
In the order they appear in the post. Each quotation is the speaker’s words in this post. A label such as “Supported” or “Can’t be checked” is the claim’s current assessment; its page has the evidence and the reasons.
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“Because, let’s face it, every generative AI product we’ve seen from Big Tech has been underwhelming.”
Our reading: Every generative AI product we have seen from Big Tech has been underwhelming.
No horizon
Scope: products we've seen from Big Tech
Assessment: Can’t be checkedSaid
Forecast
“As organizations build their own AI integrations — through either paying for compute for their own purpose-built solutions or by integrating OpenAI's GPT — there is likely to be some revenue growth in cloud providers.”
Our reading: Cloud providers will likely see some revenue growth as organizations build their own AI integrations.
No horizon
Qualifier: as organizations build their own AI integrations
Assessment: ContradictedSaid
Observation
“That being said, we're yet to see this actually happen, outside of OpenAI's alleged $3.4 billion of yearly revenue (it still loses $5 billion a year), and generative AI's multi-billion dollar contribution to Amazon Web Services revenue over an indeterminate amount of time.”
Our reading: Outside of OpenAI's alleged $3.4 billion of yearly revenue (while it still loses $5 billion a year) and generative AI's multi-billion dollar contribution to AWS revenue over an indeterminate period, we have yet to see revenue growth for cloud providers from organizations building their own AI integrations.
No horizon Evidence as of
Limitation: Microsoft's reported AI-services contribution does not separately quantify customer-built integrations; the assessment depends on the contract's broader reading [e1].
Assessment: Can’t be checkedSaid
Observation
“If I had to guess, it’s about as deeply unprofitable as a SaaS company has ever been, and there is no real turning that around.”
Our reading: If he had to guess, Glean is about as deeply unprofitable as a SaaS company has ever been, and there is no real turning that around.
No horizon
Qualifier: if I had to guess
Assessment: UnresolvedSaid
Causal claim
“And the reason I've so agonizingly explained it is that I believe the current generative AI boom is almost entirely fueled by the hunger of the Software As A Service parasite for growth...and the slow collapse of growth in tech's favorite business model.”
Our reading: The generative AI boom is almost entirely driven by the SaaS industry's need for growth and the slow collapse of SaaS growth.
No horizon Evidence as of
Limitation: Corporate explanations may be selective.
Assessment: UnresolvedSaid
Causal claim
“The answer is simple: the tech industry's desperate attachment to artificial intelligence is largely fueled by the SaaS industry, because AI is the first meaningful new "thing" they've had to flog to customers in quite some time”
Our reading: The tech industry's attachment to AI is largely driven by SaaS companies needing a new product to sell to customers.
No horizon Evidence as of
Limitation: The announcements do not establish a prior shortage of meaningful new SaaS offerings or measure the causes of industry-wide AI commitment [e1, e2].
Assessment: UnresolvedSaid
Observation
“It doesn't really matter that these agents are basically the same "chatbot-that-connects-to-large-database-of-information" thing we’ve seen a million times, but this time connected to a Large Language Model.”
Our reading: Salesforce's Agentforce agents are essentially the same database-connected chatbots seen before, now connected to an LLM.
No horizon Evidence as of
Limitation: Vendor descriptions establish the proposed design, not its reliability.
Assessment: UnresolvedSaid
Observation
“Every company promising "AI agents" is really just trying to rebrand the concept of chatbots and provide a front-end to let you connect them to data sources and give them guardrails so they don't scream curse words at your customers or write poetry about how bad the company is.”
Our reading: Every company promising 'AI agents' is really just trying to rebrand chatbots and provide a front-end that connects them to data sources and gives them guardrails.
No horizon Evidence as of
Limitation: This assessment tests functional substance, not private marketing motives.
Assessment: UnresolvedSaid
Observation
“These "agents" are branded to sound like intelligent lifeforms that can make intelligent decisions, but are really just trumped-up automations that require enterprise customers to invest time programming them.”
Our reading: Enterprise AI 'agents' are not intelligent decision-makers but automations that customers must spend time programming.
No horizon Evidence as of
Limitation: No-code is not equivalent to no configuration.
Assessment: ContradictedSaid
Observation
“Almost every one of these companies is claiming that these systems "reduce drudgery" or "enhances productivity," yet there's no real explanation as to how it might do so or what the drudgery is that's being relieved, nor any unassailable metrics on how productivity improves.”
Our reading: Almost every one of these SaaS companies with AI products claims the systems reduce drudgery or enhance productivity, yet there is no real explanation of how or what drudgery is relieved, nor any unassailable metrics on how productivity improves.
No horizon Evidence as of
Limitation: The contradiction is confined to the categorical absence of explanations.
Assessment: UnresolvedSaid
Causal claim
“Scenario 1 is obviously dangerous, offering a tool that costs a great deal of money to provide only a little value to customers for free, meaning that at best you'll have customers that lose you money every single time they interact with the product.”
Our reading: SaaS companies offering costly AI features for free will at best lose money every time customers use them.
No horizon Evidence as of
Limitation: No actual per-interaction cost records establish positive incremental expense throughout September 1–26, 2024.
Assessment: UnresolvedSaid
Observation
“As The Information reported a couple of weeks ago, Microsoft has categorically failed to turn Copilot for Microsoft 365 (a product line that makes at least $15 billion of revenue a year) into a meaningful revenue driver, with “between 0.1% and 1% of the 440 million existing users of Microsoft 365...paying for the new AI features" according to an equity analyst's estimation.”
Our reading: Microsoft has failed to make Copilot for Microsoft 365 a meaningful revenue driver, with only an estimated 0.1–1% of users paying.
No horizon Evidence as of
Limitation: The readable reports share the same underlying source.
Assessment: Can’t be checkedSaid
Observation
“While it's possible that Microsoft could have found ways to make Github Copilot more efficient, this seriously suggests that Microsoft 365 Copilot loses money in much the same way, though generating code is a little more compute-intensive.”
Our reading: Microsoft 365 Copilot likely loses money per user, as GitHub Copilot was reported to.
No horizon
Qualifier: unless Microsoft made Copilot more efficient
Assessment: UnresolvedSaid
Observation
“While this sounds like a lot, it’s actually a staggering reversal from the previous 30% quarter-over-quarter growth and suggests that momentum has rapidly slowed.”
Our reading: GitHub Copilot's rise from 1.3 million to 1.8 million paying users is a staggering reversal from its previous 30% quarter-over-quarter growth and suggests its momentum has rapidly slowed.
No horizon Evidence as of
Limitation: The spring disclosures do not measure the full period asserted.
Assessment: Can’t be checkedSaid
Observation
“One has to wonder if Microsoft365's "Copilots" are equally unprofitable. I'd wager they are.”
Our reading: Microsoft 365 Copilots are probably as unprofitable as GitHub Copilot.
No horizon
Assessment: Can’t be checkedSaid
Rhetoric
“As a result, generative AI kind of felt like the perfect SaaS snake oil, a magical new way to indefinitely charge customers for the thing that they already should have.”
Our reading: Generative AI kind of felt like the perfect SaaS snake oil, a magical new way to indefinitely charge customers for things they already should have.
No horizon
Qualifier: kind of felt like
Assessment: UnresolvedSaid
Observation
“These products almost always include some sort of half-hearted generative addition too — creating presentations or drafting emails or creating boilerplate content, all things that you can do for free with ChatGPT, Claude or whatever other Large Language Model you can find.”
Our reading: SaaS AI products almost always include some half-hearted generative addition, such as creating presentations, drafting emails or boilerplate content, all of which can be done for free with ChatGPT, Claude or another LLM.
No horizon Evidence as of
Limitation: The product population and prevalence threshold are unspecified.
Assessment: Can’t be checkedSaid
Observation
“In fact, I think they're doing their best to hide the fact that it isn't selling at all, and costs more money than it makes when it does.”
Our reading: He thinks SaaS companies are doing their best to hide that their generative AI isn't selling at all and costs more money than it makes when it does sell.
No horizon
Qualifier: I think
Assessment: SupportedSaid
Observation
“In essence, Amazon is benefitting from AI in much the same way NVIDIA is.”
Our reading: In essence, Amazon is benefitting from AI in much the same way NVIDIA is, by supplying the compute people need while working out what AI is useful for.
No horizon Evidence as of
Limitation: No infrastructure revenue share is established.
Assessment: Can’t be checkedSaid
Rhetoric
“As I hinted earlier, I see the enterprise and the SaaS market as the commercial real estate arm of the Subprime AI Crisis — an industry desperate for growth attaching itself to an unprofitable, unsustainable technology that they invested in in the hopes that it would fuel a decade or more of revenue growth.”
Our reading: The enterprise SaaS market is the 'commercial real estate' of a Subprime AI Crisis, tied to an unprofitable, unsustainable technology.
No horizon
Assessment: Can’t be checkedSaid
Forecast
“Much like the feared commercial real estate bubble, SaaS may see its own series of dramatic price cuts to its AI tools as a means of competing and showing growth to the markets...despite the costs staying the same, or possibly increasing.”
Our reading: SaaS companies may engage in a race to the bottom with dramatic AI tool price cuts while costs stay flat or rise.
No horizon
Qualifier: costs staying the same or increasing
Assessment: Can’t be checkedSaid
Forecast
“Especially in the case of Microsoft, which will likely only ever make money from AI by selling compute.”
Our reading: Microsoft will likely only ever make money from AI by selling compute.
No horizon
Assessment: Can’t be checkedSaid
Conditional forecast
“For me to be wrong, there will have to be sudden, remarkable changes in either enterprise software spend, or the capabilities and costs of generative AI itself.”
Our reading: His thesis about SaaS and generative AI holds unless enterprise software spend or generative AI's capabilities and costs change suddenly and remarkably.
No horizon
Only if: absent sudden remarkable changes in enterprise software spend or generative AI capabilities and costs
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“And if Salesforce — considered the prize growth-pig of the SaaS hogs — isn't growing, then the rest of the market should be terrified.”
Our reading: If Salesforce is not growing, the rest of the SaaS market should be terrified.
No horizon
Qualifier: if Salesforce isn't growing
Assessment: UnresolvedSaid
Causal claim
“While these companies had costs before, generative AI is multitudes higher than regular cloud compute costs, meaning that any new revenue growth from this software will be burdened by leveraging an increasingly-expensive solution to a problem that most of them have trouble describing.”
Our reading: Generative AI costs many times more than regular cloud compute, so any AI revenue growth for SaaS will be weighed down by rising costs.
No horizon Evidence as of
Limitation: The investor observations disclose no representative sample or matched workloads.
Assessment: Can’t be checkedSaid
Conditional forecast
“And if the revenue never arrives, they'll be faced with the same problem as the rest of the tech industry — that they've run out of ideas to generate growth.”
Our reading: If AI revenue never materializes, SaaS companies will face having run out of ideas for growth.
No horizon
Only if: if AI revenue never arrives
Held from this post (15)
These records did not pass every check, so nothing about them is published. Held is not a finding.
- The record does not meet the current rules. Our reading, not assessed: Because most of these companies effectively have to double prices to offer AI, it is hard to imagine these features aren't already problematically expensive to maintain.
- The record does not meet the current rules. Our reading, not assessed: Hallucinations are not a bug so much as a feature of the transformer model that underpins generative AI.
- The two reviews read the claim differently
- The two reviews read the claim differently
- The two reviews read the claim differently
- The criteria are ambiguous. Our reading, not assessed: Google, Amazon and Microsoft are bankrolling the generative AI boom, including heavily subsidizing the compute rates OpenAI (and likely Anthropic) pay.
- The criteria are ambiguous. Our reading, not assessed: At some point, generative AI's poor margins will begin to eat into these SaaS companies' already-tenuous profitability, and he imagines this will lead some to vastly raise prices or drop the tools, assuming competition doesn't make keeping them necessary.
- The criteria are ambiguous. Our reading, not assessed: It feels like hundreds of companies have made AI summaries, generative features and search so commonplace that they are effectively commoditized, so everyone is expected to offer mediocre tools that cost too much to run, making them harder to sell at a premium.
- The two reviews read the claim differently
- The two reviews read the claim differently
- The two reviews read the claim differently
- The record does not meet the current rules. Our reading, not assessed: Nobody, including Microsoft, Anthropic, OpenAI or Google, is any closer to solving hallucinations.
- The two reviews reached different assessments. Our reading, not assessed: The SaaS business model, the main way that over a hundred multi-billion dollar companies and parts of several multi-trillion dollar companies make money, is potentially collapsing or at the very least contracting, likely because there just might not be that much left to sell.
- The two reviews read the claim differently
- The record does not meet the current rules. Our reading, not assessed: Other than Microsoft, which has barely been able to sell it, he can find no public SaaS company that appears to have attributed any meaningful revenue growth to generative AI.