Public markets + late stage VC investing @OctahedronCap. Previously same @ Tencent 腾讯投资. 🇺🇸🇨🇳🇮🇳 since birth. NerdNation 🌲 @Stanford is home.
San Francisco, CA
Joined April 2009
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Chris Huskey retweeted
Ali Ghodsi never wanted to be CEO. In 2015, he was interviewing for a professor job at Berkeley when the @Databricks board handed him the interim title. Revenue that year was $1.5M.
This episode with @alighodsi will go down as one of my favorites. 10 things I took away:
1. Focus the entire company, orders of magnitude of attention, on its single biggest bottleneck. Like a laser, almost to an extreme. The cycle is 1-3 years, not weeks. If your focus changes weekly, then you’re just in firefighting mode.
2. There is nothing worse than a conflict-averse CEO. They are wonderful people, but they are in the wrong job. Conflict is the gym for a CEO: nobody likes it, but everyone has to go.
3. Study your enemy carefully, understand their weaknesses and apply your strengths to those weaknesses. Snowflake had 2x his revenue. He didn’t copy them. He found three weaknesses (proprietary, no AI, expensive) and hammered them account by account for four years. Watch the competition, never follow it.
4. The concept of a Lakehouse was ridiculed internally and online. No one wanted to market with this new term. So he made the whole company religious about it anyway, killed the ads that converted better without the word, and put it in the sales comp plan. It worked. All hands on deck, no exceptions.
5. Be willing to take a step back for a much bigger vision, even when the company is already succeeding. At multiple hundreds of millions in ARR, he was unhappy, because the vision he pitched investors wasn’t the company he was running. So he took one step back to go ten forward.
6. On the flat org, player-coach model that a lot of people have talked about this year: “it’s BS.” Separate how the company thinks (AI, ontology) from how the humans get managed (they are after all, still humans). His staff meets 3x a week. I asked if it could just be coordinated in a Google doc. His answer: do you meet your wife and kids, or coordinate that in a Google doc?
7. His test for a sales leader: can they build the car, or just drive it? Ron Gabrisko, the Databricks CRO, had seen $0→50M and $50→100M+, and hadn’t changed jobs in 10 years prior to joining. Now he has been the CRO for over a decade. He built and drove the car the whole way. That almost never happens.
8. Hire execs ahead of the curve because by the time you need them, it’s too late. A real search takes 6-12 months. The extra time helps you increase false negatives and decrease false positives. Do an insane number of backdoor references because 80% of ‘front door’ references are bs.
9. The best salespeople are not super technical, so stop trying to force them to be. Square peg, round hole. The best win with professional aggression, high EQ, and mapping the real power base (how decisions get made high up in an organization), not technical depth.
10. Yes, your best AEs will annoy people. One of the first at Databricks got a meeting nobody could get, but got banned from the customer’s building for it. He told Ali, “what are you complaining about? I got the meeting.” Professionally aggressive is the bar.
One bottleneck, zero wussing out. He reminds me of @elonmusk that way.
Chapters
0:00 – Introduction
1:22 – The secret CEO search and why the board bet on a founder
4:11 – Professor or CEO? Always taking the harder option
8:18 – Pour everything into one bottleneck
12:16 – Killing PLG and learning what great enterprise sellers actually have
19:09 – Hiring ahead of the curve: sales leaders, execs, and back-door references
27:02 – The Snowflake rivalry: study your enemy, never copy them
33:22 – Lakehouse: conviction, ridicule, and the case for second acts
41:02 – The killer instinct and why conflict-averse CEOs fail
44:10 – Dunbar's number and rethinking the org chart around AI
48:00 – AGI is already here — enterprises just use it as a chatbot
52:55 – Does he still code? Two days for a connector vs. three quarters
57:18 – A day in the life, and why the Monday meeting isn't theater
1:04:53 – Why Databricks will go public, just not yet
1:08:09 – Get over conflict aversion, or don't be CEO
1:11:07 – Brian's takeaways
Link to more in the comments.
Chris Huskey retweeted
disturbed by the confidently held opinions and lack of curiosity from tech leaders, politicians, vc’s on the pacing the frontier topic.
if you’re not building the frontier yourself, how can you possibly have a strongly held opinion on how bad the alignment problem is and what’s coming our way and what the right policies are?
now is the time to listen with big dumbo ears. i have been talking to research friends all weekend and the fear is sincere. i’m sure there are 4D chess moves and hidden motives, but the fear is sincere.
i for one don’t have a strongly held opinion, other than that now’s the time to listen with curiosity instead of judgment.
Chris Huskey retweeted
Imagine replacing every employee at American Airlines, Home Depot or Medtronic with a math olympiad who approached every task as a problem of discovery. Costs would not fall, but would rise rapidly and dramatically as every routine decision would be re-examined from first principles. The organization would drown in intelligence it cannot productively use or absorb
Chris Huskey retweeted
Okay, I keep trying to correct Claude's gratingly awful speaking style (a weird mix of over-dramatic wordiness + unnecessary terseness) and I can't. It seems to be too embedded in the model. How do all the people at Anthropic who work on this model use this thing all day??
Chris Huskey retweeted
SpaceX drops the hypiest IPO filing and says "we believe we have identified the largest TAM in human history", and you're like, my interplanetary east India company, what delectable spice have you decided to ship across the stars, and it's like... 22 trillion dollars of b2b saas
Chris Huskey retweeted
It took us 47 iterations to stop one of our AI SDRs from being too aggressive on pricing. Not 3. Not 10. Forty-seven.
Each iteration required reviewing outputs, adjusting prompt instructions, testing again.
That's not a bug in AI GTM. That's the job.
The companies failing with AI agents are the ones who expected 2 iterations. The ones winning expected 50.
Chris Huskey retweeted
Today, we're releasing Omma.
Create 3D, Websites, and Apps with AI agents.
Start now on omma.build
Follow @omma_ai
Chris Huskey retweeted
Takeaway from the Citrini backlash should not be that all marketplaces are immune to AI, just that DoorDash was a particularly bad example to choose.
Defensibility is largely a product of how far they are to the right on this spectrum.
The argument is "agents will just transact on your behalf and look for lowest price"
This is massively flawed for two reasons in the case of DD:
1. Price is function of network density. You must be able to optimize routes and batch orders to win
2. Even if someone else could win on price, customers care about many other things (selection, quality, service, all of which DD has invested in heavily)
So you can’t build a good agentic food delivery product without DD cooperation. And for obvious reasons, they will not cooperate.
But it doesn’t follow that this will play out everywhere.
The more heavily managed a marketplace is, the harder it is for someone else to cut in.
There are basically 4 levels of marketplace:
1. Lead gen: just a list of suppliers
2. Transactional: also handle payment
3. Managed: also take on risk (returns, net terms)
4. Heavily managed: also manage service delivery
Google has been trying to eat the marketplace profit pool for many years, and really only succeeded in taking most of it away from lead gen marketplaces.
LLMs are another aggregation layer like Google, but with two big differences: search is much better, and critically, they can transact on your behalf.
So LLMs should be able to push up one step farther in the stack, and take on transactional marketplaces directly.
But is Anthropic going to try to do the final two jobs of managing risk or managing service delivery itself?
Are they going to start accepting returns? Offering financing terms to buyers? Are they going to manage their own drivers or build their own logistics network. That seems very unlikely.
As a result, managed marketplaces are largely safe.
Marketplaces that do the hardest, most capital intensive, most scale-dependent stuff will get rewarded for it.
I wrote an essay on this here: danhock.co/p/llms-vs-marketp…
Chris Huskey retweeted
In order to have a sense of AI adoption right now, you really need to have one foot at the bleeding edge with the kids Wispr-ing through a mic at Devin all day and one foot in the 99% enterprise world where they’re still debating the merits of leaving “bundled-MSFT-ELA-Copilot”
