Clint Sharp

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Clint Sharp

Clint Sharp

@clintsharp

CEO and Co-Founder at @cribl_io.

Oakland, CA Bergabung Mart 2007
1.1K Mengikuti2.2K Pengikut
Clint Sharp
Clint Sharp@clintsharp·
You state these like facts but they’re far from certain. From my perspective I don’t see a huge appetite for enterprises to spend more. I also don’t think the limiting factor in the number of companies in the market has ever been the production of the software. The question to answer is how these 10x more companies can solve the problems in a unique and better enough way long enough that the entrenched competitors won’t just copy, giving these new companies the time to achieve anywhere near the scale that would allow most enterprises to consider them a trusted option. Let’s check back in 5 years and see what’s happened.
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Guru Chahal🇺🇸
Guru Chahal🇺🇸@guruchahal·
@clintsharp Enterprises will spend way more on tech (a part of which was served by traditional SaaS). AND there will be 10x competition in SaaS which’ll impact those business models. These aren’t mutually exclusive no?
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Clint Sharp
Clint Sharp@clintsharp·
This just makes absolutely zero sense. There already isn’t a lack of supply in enterprise software. For any given category there are already dozens of choices. There are already funded and bootstrapped in every category. There are free and open sourced alternatives in nearly every category. So what is the limiting factor that drives spend to a handful of category leaders? Trust. Trust is in very short supply. How do I solve this problem for my employer in a way that does not introduce new risk and get me fired? Buyers are not buying just a software package they are transferring risk from them to the vendor. Software is a people business. I’m going on record that a burgeoning supply of dozens of new competitors will do little to change the dynamics of where money flows in enterprise software.
Guru Chahal🇺🇸@guruchahal

.@nicbstme does a great job capturing the rapidly shifting sands in vertical SaaS! This right here is the key… AI is arming the hordes - and they are coming for their cut of enterprise SaaS spend!

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Clint Sharp
Clint Sharp@clintsharp·
Both predictions can't be true: SaaS is dead, categories are going to shrink, and AI will enable tons of new competitors. There will be downward pressure on prices because enterprises are not going to allocate more money to software, but it is very unlikely that categories are suddenly going to flooded with new entrants and buying behaviors are going to suddenly change because of AI. Enterprises already do not opt for smaller competitors, and having dozens more smaller ones attempting to compete for a shrinking pie isn't a path to success for anyone. I'll go on record that the opposite will actually happen. AI will enable software companies to be more efficient. Margins will improve. SBC is dead. It will no longer be a path for a mediocre exec to make millions. But, it will be even harder for startups to enter these categories. The door is shutting and incumbents will be cemented.
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Guru Chahal🇺🇸
Guru Chahal🇺🇸@guruchahal·
@clintsharp Those analysts will now have a lot more choices in recommending vendors that are perfect for that enterprise.
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Clint Sharp
Clint Sharp@clintsharp·
@guruchahal Enterprises aren’t looking for more choice. They already pay analyst firms to tell them what to buy so they don’t have to spend time surveying the market. It’s not that nothing will change but the surface level analysis of AI impact on enterprise software is wrong.
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Guru Chahal🇺🇸
Guru Chahal🇺🇸@guruchahal·
@clintsharp Trust helps. But increased competition at the app layer is coming. And that will given enterprises choice - which will degrade pricing power of that trust.
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Clint Sharp
Clint Sharp@clintsharp·
@guruchahal In most enterprise software companies less than 25% of the people are involved in actually building the software. This is a stupid take. Nobody’s going to replace their mission critical software with something built by bootstrapped hobbyists.
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Guru Chahal🇺🇸
Guru Chahal🇺🇸@guruchahal·
100% this 👇🏼
signüll@signulll

i’m absolutely loving the saas apocalypse discussions on the timeline right now. to me the whole saas apocalypse via vibe coding internally narrative is mostly a distraction & quite nonsensical. no company will want to manage payroll or bug tracking software. but the real potential threat to almost all saas is brutalized competition. i.e. ai doesn’t need to magically recreate salesforce. it just needs to make it trivial for tiny teams to deliver functionally equivalent outcomes at a fraction of the cost. once that happens, pricing power potentially collapses. imagine payroll… today you’re paying a fat margin for “trust + compliance + saas software” that increases prices so fucking often. like we have a startup & everyone is charging us up the ass for everything on a per seat basis. you can imagine tomorrow a 2 person shop empowered by ai can ship the same output, hit the same regulatory checkboxes, & charge 70% less because their cost structure is basically nil. today saas margins exist because: - engineering was scarce - compliance was gated - distribution was expensive ai nukes all three in many ways, especially if you’re charging significantly less & know what the fuck you are doing when using ai. if you go to a company & say we will cut your fucking payroll bill by 50%, they will fucking listen. the market will likely get flooded with credible substitutes, forcing prices down until the business model itself looks pretty damn suspect. someone smarter than me educate me on why this won’t happen please.

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Clint Sharp
Clint Sharp@clintsharp·
The amount of people who are prognosticating with supreme conviction about the future of the software business while seeming to have little to no experience building software businesses is approaching COVID level faux expertise.
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Clint Sharp
Clint Sharp@clintsharp·
Sharp’s Law of AI markets: any sufficiently large market will attract the attention of the model builders, so choose a large market but not too large
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Clint Sharp
Clint Sharp@clintsharp·
If AI can generate all these SDR emails why can't Superhuman filter them out?
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Dev Ittycheria
Dev Ittycheria@dittycheria·
We will look back at this time and recognize that DeepSeek was the tipping point on focus moving from training to real-time inference. Cost of intelligence is quickly marching towards zero.
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Clint Sharp
Clint Sharp@clintsharp·
If you’re a product person and you’ve never really done sales, I mean really done it, then a) you’re missing out and b) you’re living a theoretical life that isn’t grounded in reality. Life is a negotiation. And I don’t mean negotiating with engineering.
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Clint Sharp
Clint Sharp@clintsharp·
@rauchg Meh. Maybe you’re not doing it right 😛
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Guillermo Rauch
Guillermo Rauch@rauchg·
Remote work is individual convenience at the expense of group effectiveness
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Ross Lazer
Ross Lazer@rosslazer·
We rebuilt anomaly detection at Splunk every few years. We even acquired a few companies despite our ML team's efforts to stop it. The most inroads I got to helping people understand its infeasibility was comparing it to trading. If someone had an algorithm that could predict a time series with only the time series, they would be making a killing in the stock market.
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martin_casado
martin_casado@martin_casado·
Systems ideas that sound good but almost never work: - DSLs - Live migrating process state - Anomaly detection - Control loops responding to system load - Multi-master writes - p2p cache sharing - Hybrid parallelism - Being clever vs over-provisioning .. What else?
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Clint Sharp
Clint Sharp@clintsharp·
There are advantages to DSLs for articulating for example how to work with different types of data versus SQL. On the other hand, there are numerous implemented languages which are complete that allow you to avoid writing your own. For us, we chose Kusto from Microsoft. Saved a ton of effort.
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martin_casado
martin_casado@martin_casado·
OK, on whether DSLs are a good idea. It comes down to the following: Either you're implementing a language, or you aren't. If you are, do it right (lex, parse, bind, opt, plan, interpret). And realize it's probably overkill, and has likely already done that better.
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Clint Sharp
Clint Sharp@clintsharp·
Excited to see @getmetronome unveil their latest updates in Metronome 2.0. We were an early adopter at @cribl_io, and Metronome is core to our cloud usage billing. The new capabilities are critical to new pricing structures we'll be rolling out next year. Proud to be an investor. Congrats to the team!
Metronome@getmetronome

✨Excited to announce Metronome 2.0! Over the past few years, we've learned a lot from powering billing for companies including @OpenAI, @AnthropicAI, and @databricks. We've productized those learnings into Metronome 2.0 to help companies launch new products and pricing faster.

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Clint Sharp
Clint Sharp@clintsharp·
@_cartermp @mipsytipsy There is no universal solution. No single engine can give everything. Thusly, it’s about how are the engines exposed to the user and do they need to learn a new experience for each engine or can that be abstracted. I believe you can unify experience at least.
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Charity Majors
Charity Majors@mipsytipsy·
Catching up and closing tabs on a month or so if missed blog posts, and here's another dandy: "The Observability CAP Theorem", by @_cartermp. Everybody wants: 1, fast queries 2, long retention 3, rich context 4, low cost You can pick two, *maybe* three. phillipcarter.dev/2024/09/14/the…
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