
GP @GTMfund - early stage fund w/ 350+ GTM Exec LPs - backing @Armada_ai, @ollama @Get_Writer, @Owner, @TrustVanta, @paid_ai, and more.
San Francisco, CA
Joined July 2011
- Tweets14.8K
- Following776
- Followers12.2K
- Likes28.8K
Max Altschuler retweeted
gm @gtmfund
Max Altschuler@HackItMaxOct 16United States
United StatesConnected via United States App StoreAccount-level information, not a live location or per-post device.
GP Paul Irving dropping knowledge on the state of the market and metrics at the @gtmfund AGM
🎙️ Watch now: debut podcast available on all platforms.
Episode 1. Satya Nadella on “Confession with Ali Partovi”
– The interview question he still thinks about decades later
–"We won the browser war, only to lose the web"
– His son Zain and how his empathy journey began
… and much more with Microsoft CEO @satyanadella.
(0:00) “You need more empathy”: a job interview gone bad
(0:27) Welcome to Confession
(1:06) Growing up in India
(4:13) “See the world through his eyes”: the birth of his son Zain
(11:27) “I didn’t care. I didn’t listen”: failing as a manager
(16:07) “It haunts me”: lacking the courage to speak up
(19:50) “We didn’t understand that the economic value is all in search”
(26:19) Ali: “I was essentially fired… I’ve never told anyone”
Max Altschuler retweeted
T-Mobile CTO in new post on @SpaceX acquiring nationwide low-band spectrum to help turn Starlink into a major U.S. mobile carrier:
"Some are calling it the "last critical piece" needed to compete with the national wireless carriers. I can tell you there's a big difference between owning spectrum and delivering a great mobile experience to millions of customers.
A few things worth keeping in perspective:
1) Spectrum is just the starting point.
The Grain transaction involves approximately 14 MHz of spectrum that T-Mobile previously divested because it was no longer central to our network strategy. Even with this acquisition, @Starlink Mobile would have roughly 80 MHz of spectrum, some of it uplink-only. Compare that to T-Mobile's nearly 400 MHz of mid-band and low-band spectrum holdings.
We used 800 MHz spectrum as a single 5 MHz uplink/5 MHz downlink channel for LTE years ago. Today, we're operating a nationwide 5G Standalone network, launched nationwide 5G-Advanced, and are already helping shape the path to 6G, all using channels that are much wider. The industry has moved forward and so have the expectations of customers.
2) Physics still applies.
A satellite hundreds of kilometers above Earth faces approximately 50 dB more path loss than a terrestrial cell site just a kilometer away. Moving from 2 GHz to 800 MHz recovers only a few dB of that enormous disadvantage.
Lower-frequency spectrum can help improve satellite connectivity, but it doesn't change the fundamental physics. A satellite signal traveling hundreds of kilometers simply faces challenges that a nearby cell tower doesn't.
3) Indoor coverage is where the real test begins.
More than 70% of mobile traffic takes place indoors. Think about where you use your phone most: at home, in the office, inside a store, or at a crowded venue.
That's where terrestrial networks have a fundamental advantage. Buildings, walls, and other obstacles make it much harder for signals traveling from space to reach customers reliably. Direct-to-Cell technology can extend connectivity to outdoor places traditional networks don't reach, but delivering a consistent indoor mobile experience is a very different challenge.
4) Capacity matters just as much as coverage.
One satellite beam can cover an area served by hundreds of terrestrial cell sectors. Those terrestrial sectors provide the network density needed to support millions of customers streaming video, making calls, working, gaming, and using data simultaneously.
Covering a geographic area is one thing. Delivering the speed, responsiveness, and capacity customers expect from a modern 5G-Advanced network is another.
Direct-to-Cell has an important role to play in extending coverage. But it is a complement to terrestrial networks, not a replacement for the capacity of a dense 5G-Advanced network.
5) Building a great network takes more than capital. It takes time and experience.
The U.S. wireless industry has invested more than $250B in network infrastructure since 2018. That’s on top of more than $200B in spectrum auctions over the past decade, plus the stores, care, and distribution that support customers every day. And that investment represents only part of what it takes to deliver a great wireless experience.
You can acquire spectrum in a single transaction. You cannot acquire a nationwide, high-performing wireless network overnight.
If this is truly the beginning of a new wireless provider in America, we welcome competition. It's good for innovation, good for the industry, and most importantly, good for customers.
But great wireless networks aren't built with headlines or spectrum licenses alone. They're built site by site, neighborhood by neighborhood, in subway tunnels, office buildings, stadiums, and communities across America.
Spectrum is an essential ingredient. But it takes a network to deliver on its promise."
Max Altschuler retweeted
cancer treatment in 2025:
find the tumor, cut it out, poison the rest with chemo, hope the patient survives
cancer treatment in 2026:
sequence the tumor's DNA, identify the exact mutations driving it, design a treatment built around those mutations specifically, train the patient's own immune system to hunt them down
it's coming fast, bio/acc.
100 GTM leaders in one room is something special.
Thank you everyone who joined yesterday evening for the GTM Leader Happy Hour!
A big thanks to our event partners for helping to make it happen: @BainCapVC, @zapier, @useactively.
More @gtmfund events coming soon...!
Max Altschuler retweeted
Absolutely incredible…
Mark Cuban: "California is run terribly. The taxes are insane. That’s why people keep moving to Texas."
Mark Cuban (10 minutes later): "Vote for James Talarico. Turn Texas blue. What have Republicans ever done for the state."
Max Altschuler retweeted
There’s so much to unpack here, but it’s a huge lesson for startup founders AND for their customers.
For background, ServiceTitan announced that they are no longer integrating with Podium and customers (which it seems like there are ~1,000) have 3 weeks to find a replacement.
This is the definition of platform risk.
Not because one company is necessarily right or wrong, but because it exposes a truth that both founders and customers routinely underprice.... an integration is not a product feature. It is a revocable treaty between two companies whose incentives can (and will) change.
There are a few important lessons here:
1/ Platform risk is an incentive problem, not an API problem.
Founders worry about uptime, rate limits, documentation, and technical stability.
But the largest risk is strategic and has nothing to do with the tech.
An integration remains safe only while the two companies are complementary. The moment the partner begins owning a valuable adjacent workflow, more customer data, or the customer relationship itself, it can (and will) become a competitor.
This happens all the time, and is exactly what is happening in the Podium / ServiceTitan relationship.
2/ The system of record owns the veto.
A partner can have the better product, stronger customer love, thousands of users, and signed annual contracts.
But the platform controlling the system of record still controls the access point.
In platform markets, the company creating the most value is not always the company with the power to decide whether that value may continue flowing.
3/ Platform dependent ARR is contingent ARR.
So many startups I talk to sell customers annual contracts while relying on platform access that can be changed in hours/days/weeks.
Long-term obligations built on short-term permission is a nightmare.
If a meaningful percentage of your revenue depends on one company’s API, you do not just have partner concentration. You have a giant liability inside your business model.
Investors will evaluate platform concentration the same way they evaluate customer concentration.
Not all ARR has the same durability. Although you may be able to grow quickly being a platform partner, the risk and valuation aren't worth it.
4/ Marketplace ecosystems follow a predictable arc.
A platform recruits partners to fill product gaps.
The partners discover demand, educate the market, and build new categories.
The platform watches which categories become strategically important.
Then it decides whether to continue partnering, acquire, restrict, replace, or build.
The ecosystem is often most open before the platform knows which adjacencies are valuable.
Amazon is the king of this.. but it's the same playbook over and over.
5/ Customers ultimately inherit the vendor conflict.
An “integrated stack” feels modular until one vendor can sever the connection and leave the customer with overlapping contracts, stranded workflows, retraining costs, and a rushed migration.
The important procurement question is not merely:
“Does it integrate?”
It is: “Who can revoke the integration, what breaks if they do, who owns the data, and how quickly can we recover?”
At the end of the day it comes down to this..
Founders should build portability before they need it.
And customers should buy continuity, not just connectivity.
Because when platforms and partners divorce, the customer pays the breakup fee.
Max Altschuler retweeted
How easy it is to get someone on the phone for a reference is as much signal as the reference itself
Max Altschuler retweeted
Hosted a dinner last night with a group of IT leaders of large enterprises around agent adoption in the enterprise. Some quick notes:
* Change management remains one of the biggest topics for driving workflow transformation. Still most processes need to be upgraded to modern operating models to work with agents, which is a mix of technology, data, and human process change. Lots of emphasis on getting data (structured and unstructured) into a setup that can work with agents properly.
* IT teams are finding increasing success embedding full engineers into the business functions (essentially internal FDE) that go and implement agents into the internal workflows. There’s so much technical work to be done to make agents successful, that they can accelerate months or quarters of failed experiments by having someone technical in the workflow early.
* Consensus that the tech function is becoming more important than ever. It’s clear that the business could only expect automation to affect a minority of the business before (e.g. ERP) but now it can impact all of knowledge work. This means IT is becoming a more central role to the workflows across the company.
* Workflows are cross functional, and getting agents to work cross functionally is a complicated data modeling and permissions issue. Single users don’t have access to this. Which means you need to have agentic systems take on their own roles and have their own privileges, which is non-trivial given agents can’t keep things secure on their own.
* Huge variance in budgets between coding work and the rest of knowledge work. Some companies had a $1,000 a month budget for developers, and others had much higher amounts (like $5,000) that were merely triggers to notify the team vs. block them. Far smaller budgets for non-coding work at the moment.
* More companies are building their own multimodel systems for routing workloads by task to frontier and lower cost models. Lots of energy around open weights models, but still more in experimentation instead of at scale usage (some companies can’t due to perceived Chinese issue).
* Clear sense that all enterprise software must be headless in the future. Relief that they don’t need to train employees on hundreds of different apps. However, clear frustration with the traditional vendors that don’t play extremely nice (technically or cost wise) with agents in a headless fashion. Huge warning for existing software vendors.
* Mythos or mythos level-models are finding more and more sophsiticated security risks. The chaining together of vulnerabilities is what’s novel right now, and companies are coming up with long backlogs of what they need to go patch quickly.
Even more discussed, but just a few of the hottest topics.
Max Altschuler retweeted
I deeply resent that AI has forced me to eliminate em dashes from my writing for fear of signaling slop
Max Altschuler retweeted
Tom Brady reveals the brutally honest talk he had with a Michigan sports psychologist that turned him from a benchwarmer into the GOAT.
Brady's transformation started with one change: the way he thought.
"I sit on the bench my first year, and I really had—I would call it—a lot of self-defeating attitudes and behaviors. I always had an excuse. 'Coach doesn't want me in there.'"
"I had a sports psychologist. His name was Greg Harden. I would go into his office every Tuesday, and he would say, 'Tom, I like you. You work hard, but you have a shitty attitude.'"
"'How about you start worrying about what you can control and stop talking about the other quarterbacks, stop talking about the coaches not putting you in.'"
"If they give you three reps, you do the best with the three you get. Quit bitching about you only getting three or you going in there with the backup receivers. No one cares.'"
"'You treat practice like it's a game. If you throw a touchdown in the two-minute in practice, you celebrate like it's the game.'"
Brady never approached it that way before. Then "sure enough" everything changed.
"Mmy energy started getting way better. I was bringing juice; I had the right attitude."
"Then all of a sudden, I'm bringing the juice, man. Every day, boom."
"That [mindshift] really helped me get better."
The road to 7 Super Bowl rings didn't start on the practice field; it started in that very office…
Max Altschuler retweeted
White-boarding live with founders and execs building some of the fastest-growing AI companies on the most important topic right now. Can't wait!
Next Tuesday, I'm back in SF bringing together leaders to tackle one of the most critical challenges every company building and selling agents is facing: AI monetization.
Thrilled to be joined by Simon from Plain and Sudhee from Battery, along with pricing experts from Simon-Kucher, for this closed-door workshop.
We'll spend the session working through the toughest monetization scenarios folks in the room are actually navigating and building practical models live.
It's invite-only.
Shoot me a DM or apply in the comments if you think you should be there.
Max Altschuler retweeted
energy is local. stopping datacenter builds, as NY just did (rather than designing win-win requirements and incentives for local communities and builders) is going to lead to some geos having decrepit infrastructure, and some geos benefiting from grid upgrade, investment and economic revitalization.
the state needs to “plan” faster. the last time the bureaucracy said they’d study energy it led to a 30-year abject failure to build any (clean) nuclear capacity. a standard nuclear EIS takes 4 years to even get a decision
Max Altschuler retweeted
a lot of valley companies inherited Google's approach to performance: don't make cuts, pay everyone generously, call it culture.
tolerating B and C work isn't kindness to your A players. it's how you lose them, and how the whole company falls short of what it could be.
Ramp Cofounder @eglyman says paying high performers the same is one of the fastest ways to destroy a culture of excellence:
“One of the most damaging things you can do to an organization is if there are folks who are getting paid similarly, and have similar ownership, and are just not pulling their weight.”
“That leads to this very tough but fair question from folks of—I'm busting my ass, working super hard, and giving up on things, and there's all these folks free riding and you're not enforcing high standards, why should we obsess so much over reaching a higher potential?”
Max Altschuler retweeted
"we could have executed more big bets if we had had a single person owning & iterating on them. Former successful founder profile with drive and speed"
+1
seems obvious but hiring former founders for early sales/GTM is very underrated
not only because of the speed (which is needed in an earlier stage, just taking more calls & closing deals faster)
but also because they are incredible at making bets and iterating very quickly
we had our first $1M month because of a bet started by an ex-YC founder turned AE (using the @crustdata MCP to power internal recruiting use cases)
he recorded personalized looms for hundreds of our customers, explained the use case and managed to expand accounts
also hired someone to build out the Claude skills for us and (with the help of our growth team) got us enough traction to justify us spending more time and resources on this new ICP
you need to hire quicker but also look out especially for entrepreneurial/ex-founder talent, they can change the trajectory of your company
If I had to restart @ElevenLabs GTM from scratch, these are the things that I would change 🖊️
- Hire quicker. I was alone selling for the first 9 months because I believed we didn't have PMF. Main reasons: the AI tourist external mantra of 2023, and the uphill battle convincing everyone to hire more GTM (Sales development, Sales, Customer Success) because we were still mostly PLG / self-service. The hiring constraint lasted until earlier this year when we boosted our team to meet demand.
- Build an enablement team earlier. Sales enablement has such an important role in an org, and we mostly think about it when we hire a lot of people. The reality is that we need Enablement earlier due to the speed of product iteration.
- Open more markets. The results from Uber v Lyft operating models played a key role in deciding to open markets early, but I would triple down on it if we were to start over.
- Have more big bets. Similar to VCs, you only need 1 big bet to work in order to generate Alpha. We could have executed more big bets if we had had a single person owning & iterating on them. Former successful founder profile with drive and speed.
- Be more vocal about product ROI & our success. People buy from people, and companies buy based on success & ROI. In AI, we've all been slow showing ROI. This should be the key number when you start a conversation.
- Hire senior sellers. In startups, we've been told that culture is everything and someone with +25y experience may struggle to fit in. This is bullshit. The experience, connections and drive +25y sellers bring is crazy. We have a bunch today, but I would hire many more earlier.
- Reduce cash commissions and replace them with more equity. Cash is king, but Equity is queen. Queens also rule countries, so why not make Equity the dominant one in GTM?
- Open more offices. We are a remote-first company, but our customers are everywhere, and employees want to meet each other. I would open more offices to be embedded in markets quicker.
- Fun brand. Brand perception is 33% of the work. Building a fun brand adds quickly.
- Outbounds outbounds outbounds. We waited too long to migrate to an Outbound organisation. I would do it from day 1 now.
- Pipeline construction with more whales. The ideal pipeline needs to have a combo of segments to reduce risk, improve results and provide liquidity. We waited too long to pitch & bring whales.
- Not all deals are good deals. We, sellers, want to close a lot of ARR, but it is important to split early on between good vs bad deals.
Thank you to Tomasz Gmur for asking how I would do GTM again!
Hedge funds are trying and failing to hire prediction market sharps.
"We are just getting crushed by these sharps," said Susquehanna's Jeff Yass.
@iscoe tells the story of a guy who's made 7 figures trading Rotten Tomatoes betting markets, and rejected an offer from SIG:
"He said, 'Not only am I just making a killing, but I can do things that a big institutional fund can't do.'"
"He's a Rotten Tomatoes trader. He trades how a film's going to do on Rotten Tomatoes. He's made 7 figures, easily. He's building models, scraping websites, and he's doing things that SIG, through their corporate policies, maybe wouldn't allow."
"And he asked in the interview, 'Could I do this technique?' And they said, 'Yeah, probably not.'"
"And this guy, he self-describes as a 'dips**t from the Midwest.' He's like, 'I didn't go to an Ivy League school, and I'm able to outcompete Wall Street with a $600 Lenovo laptop.'"
From his appearance on the show last month.
Max Altschuler retweeted
Benchmark’s @peterfenton says 90%+ of tokens could come from open weight models in the next 18-24 months, pressuring frontier model margins.
Full convo at 12p PT/3p ET on the livestream, plus @AravSrinivas on Perplexity’s new orchestrator model and @jmorgan on why enterprises are moving toward AI models they can download and control





































