Greylock Partners retweeted
That was fun! Here’s some of my favorite things we announced today at @Wealthsimple Presents.
1. Penny is your new private banker. It can send transfers, pay bills, flag duplicate charges, and buy & sell stocks — only after you approve every move. Use it in app or via email or text.
2. Virtual cards. Great for merchants you don't fully trust or subscriptions that might be tough to cancel.
3. Wealthsimple Pay: send up to $100,000 instantly and safely. That’s ~33x what most big banks allow on e-Transfer.
4. Business credit card. No FX fees, 1% cash back, and extra cards for your team.
5. Portfolio line of credit. Borrow at some of the lowest rates in Canada at the push of a button.
6. Perpetual futures and commission-free Canadian options. First in Canada.
7. Wealthsimple Pro: our most sophisticated trading interface. Free Level 2 data, live options chains, bracket orders from the main screen, and a fully customizable layout.
8. $CADD, a Canadian-dollar stablecoin with 3.25% APY rewards.
And I can't wait to ship our beautiful+fast new mobile apps.
Oh yeah, and we gave one lucky client a million dollars!
Check out the full livestream here: youtube.com/live/MReTQMhB-FA…
Greylock Partners retweeted
Big news: We've entered into a definitive agreement to be acquired by @Salesforce!
We built Cresta to make great customer experiences an unlimited resource through a single AI operating system for customer experience. Today marks a major step forward in that journey.
Together, we see an opportunity to realize that vision at scale with Cresta complementing Salesforce’s first-class customer service platform.
More: salesforce.com/news/stories/…
Greylock Partners retweeted
One of the biggest bets startup employees make is on the founder. That trust may not be tested until years later, when the company exits.
A startup can sell for billions, and the people who helped build it can walk away with vastly different outcomes.
During M&A negotiations, investors bought in at different prices and have different return expectations.
The buyer has its own priorities. Employees don’t have a seat at the negotiating table, even when the deal could be a life-changing event for them. So much can come down to whether the founder has their back when they're not in the room.
In the latest Greylock Originals, @chronosphereio co-founder Martin Mao (@martin_c_mao )and Greylock Partner @jerrychen share what happened behind the scenes of Palo Alto Networks' $3.35B acquisition of the company.
00:00 The decision behind the headline
01:01 Why sell a fast growing company?
02:15 What makes an offer worth accepting?
03:36 "You only get one chance to sell"
05:18 A first-time founder vs. a Fortune 500 CEO
07:11 Who speaks for the employees?
Greylock Partners retweeted
SuperMe announced its Series A today, led by our good friend @kirstenagreen at @ForerunnerVC, and we're excited to keep backing the team.
@onecaseman & @ludo_antonov are two of the absolute best operators in the world when it comes to consumer networks, and they've taught a whole generation of builders how growth works. So it's fitting that their current ambition is to build the AI-native expertise network.
We led the initial investment back when @SuperMeAI was simply an exploration of "why aren't any AI products being built network-first?" The more we dug in, the clearer it became that existing networks and LLMs both fall short for operators who need help from someone who's done it before. Your network only reaches so far, and the best earned insights from great operators rarely get written down, so the LLMs never see them either.
The launch of Group Chats has been the most exciting in SuperMe's history. I can now pull a group of growth marketers into the Claude thread where I'm already working on my own marketing data and have them debate incrementality testing vs. media mix modeling. Each of them shows up as an AI profile built from what they've chosen to share, so I learn from people who've actually run these tests.
Excited to see the growth OGs jump into growth mode 🔥
Greylock Partners retweeted
You shouldn't need the best network to get the best insights.
SuperMe turns operators' work into profiles that work through your problem. Now in group chats, Claude and ChatGPT.
@ludo_antonov and I raised a $20M Series A led by @kirstenagreen from @ForerunnerVC with participation from @GreylockVC.
Read more about the changes here: superme.ai/blog/series-a
Greylock Partners retweeted
Upwind Security
Today, @AmiramShachar and Upwind Security announce an important milestone with their $400M Series C at a $3.8B valuation, and we at @GreylockVC are proud to quadruple down.
Over the last few months, there's been growing discussion around how AI will reshape cybersecurity and where new companies can win. Upwind is the answer: revenue has quadrupled in 2026, and hundreds of organizations now rely on its platform to secure their cloud and AI environments. We at Greylock co-led Upwind's seed at inception in 2022 and its Series A, and it's been a privilege to partner from the beginning.
Amiram and the team started with a prescient thesis: security must be built around runtime, grounded in how applications and systems actually behave. As AI transforms software, scans and static snapshots are no longer enough. Detecting and preventing attacks at the speed of AI requires runtime context and real-time action. Upwind has built for this from day one, and the company's significant acceleration reflects the urgency of the need for runtime security in the AI era.
Upwind is just getting started.
Up and Up!
Greylock Partners retweeted
We’re honored to be named to the @techcrunch #Disruptors60 Class of 2026!
From 17x faster root cause identification at MSCI to 87% less time to root cause at DoorDash, our team is building something that’s delivering real results.
Thank you to our team, customers, and partners!
Cybersecurity has always been asymmetric: attackers only need to find one opening, while defenders have to protect everything that matters. Now, AI is changing the scale and speed of that equation.
@chandna, Partner at @GreylockVC and Cylake board member, believes we're entering an era of machines fighting machines, where increasingly sophisticated attacks powered by “bad AI” will require equally capable “good AI” on defense.
In Episode 6 of Inside Cybersecurity, Asheem joins @renebonvanie to discuss what AI means for the cybersecurity stack, why truly AI-native architectures need to be built differently, and what three decades in cybersecurity have taught him about the people and companies that successfully navigate major technology shifts.
🎧 Watch Episode 6 of Inside Cybersecurity: cylake.substack.com/p/good-a…
Greylock Partners retweeted
Sweet! Honored to be named to the #Disruptors60 Class of 2026 curated by @GreenfieldVC at @TechCrunch Disrupt.
Building the most powerful AI hacker in the world is a mission we're proud of.
Thank you to our team, and to the customers and partners who helped us get here.
See the full class: disruptors60.ai/?utm_source=…
Greylock Partners retweeted
“The answer to a scientific breakthrough is rarely found in one place. One of the biggest bottlenecks is the fragmentation of data and context across experiments, simulations, images, and production systems.”
- @catherinehyeo, co-founder of @altaratech
Watch the talks from last month's AI for Science Symposium on @GreylockVC's youtube channel, linked in the comments!
Greylock Partners retweeted
Most of AI Twitter read the OpenAI breach of Hugging Face as an alignment story. It was also a preview of what every hacker will be able to do in a few months.
In July, a swarm of 700 AI agents broke into Hugging Face and fired off more than 17,000 actions, gaining admin control of multiple internal clusters.
Swarms like this will shred cyber defenses built for human attackers at every company, hospital, government, and power plant.
Today we're launching the defensive counterpart. Cogent Attack Path Analysis finds the routes an agent swarm would take into your company, so you can close them first.
Greylock Partners retweeted
Everyone is racing to build personal AIs that can shop for us.
But agents can only buy what they can see.
Greylock Partners retweeted
"Will AI cause Armageddon?" is the wrong question.
The discussion about the threats that AI might pose has taken on an apocalyptic tone: will it extinguish life on Earth? Will it destroy humanity? It won’t, but it poses some far more real dangers to us all—right now, not in some imagined future. In the next couple of years, we are likely to face a new wave of rampant, pervasive cyberattacks and cybercrime.
As the recent series of attacks by AI agents show, we no longer need to speculate about whether AI can conduct cyberattacks. It can. The important question now is what happens when attacks that once required skilled human beings can be conducted by machines, at machine speed and machine scale.
For most of cybersecurity’s history, we have built defenses around an unstated assumption: the attacker is human. A person—or a team—has to inspect a system, find a weakness, exploit it, see what happens and decide what to do next. That takes time. Detection therefore buys time. Defenders spot an intrusion and respond before the attacker gets much further.
Frontier AI attacks that assumption.
An agent does not need to sleep. It can inspect code, probe a network, hit a barrier, devise another approach and try again. Make a thousand copies and they can work against a thousand targets at once. Allow agents to share what they learn and hacking begins to change from a human-scale activity into a machine-scale one.
At Rubrik, we are seeing part of this transformation firsthand. Through our participation in Anthropic’s Project Glasswing, one lesson became clear. AI is not necessarily creating new vulnerabilities. It is collapsing the cost and time required to discover them.
That changes the economics of cybersecurity.
Modern software may contain thousands of small imperfections. Most lead nowhere. A few, combined in the right sequence, open a path through a supposedly secure system. Historically, finding those chains required talented people, lots of time and some luck. Frontier models can increasingly do the searching themselves, discovering paths through complex systems that humans might never find.
This is what makes complacency about the new threat so dangerous.
In 1998 a group of hackers appeared before Congress and warned that the rapidly expanding internet contained vulnerabilities capable of producing enormous disruption. There was no single cyber Armageddon. Instead North Korea crippled Sony Pictures. WannaCry raced through more than 200,000 computers in roughly 150 countries, disrupting hospitals and factories. NotPetya began as a Russian attack on Ukraine and caused about $10 billion in damage worldwide. Ransomware shut down Colonial Pipeline and disrupted fuel supplies across the American east coast.
It would be strange to look at that history and conclude that the warnings were overblown. The catastrophe did not arrive as one spectacular event. Cyber insecurity became a permanent condition.
Now imagine that condition at machine speed.
That is why “Will AI cause Armageddon?” is the wrong question. A hospital whose systems are encrypted, a bank that loses control of its identities, or a company that cannot recover its data doesn’t care much whether civilization remains intact. The question is whether AI can make attacks faster, cheaper, more sophisticated and vastly easier to replicate.
We are beginning to get the answer.
Cyber-defense therefore has to change as well. For years the industry has concentrated on prevention and detection: keep the attacker out and, failing that, spot him quickly. Both remain essential. But when attacks operate at machine speed, detection may no longer buy enough time. Intrusion, exploitation and damage can begin to collapse toward the same instant.
Companies must assume that some attacks will succeed. They need to be able to recover just as fast.
The answer is not less AI. It is more AI on the defensive side: continuously hunting vulnerabilities, watching identities and data, detecting abnormal behavior, patching weaknesses and helping restore compromised systems. Machine-speed attacks require machine-speed defense.
There has always been an asymmetry in cybersecurity. An attacker has to be right once. A defender has to be right every time. AI makes that imbalance more dangerous because attackers do not need permission, compliance reviews or perfect systems. They need only find one opening—and now they can search for it continuously, cheaply and at an enormous scale.
Criminal groups and hostile governments will use this technology. They would be foolish not to.
The first generation of cybersecurity was built to stop human beings sitting at keyboards. That world has ended. The next attack may be launched by thousands of agents, moving at a speed no human team can match.
If the hackers are becoming machines, our defenses must become machines too.
Greylock Partners retweeted
Feels like every week in robotics there’s a new ‘this is the GPT-3 moment for robotics 🤖’ announcement.
We brought on @GeneralistAI CEO & Co-Founder @peteflorence on @GreylockVC Change Agents to dig into what’s going on at the frontier of robotics models.
We covered the company’s latest Gen 1.5 model, few-shot learning, training robots on different embodiments, and the milestones towards a more generalized physical model.
Timestamps:
00:51 The inception of Generalist
04:13 Long-term goal of the company
05:47 Parallels and differences between robotics and language models
12:05 Key differentiation in 1.5 Gen model
12:48 Robot vs banana
14:49 Emergent capabilities not explicitly trained for
17:13 Cross-embodiment and the importance of hands
22:26 Research vs working with customers
24:58 Beyond VLA vs world model
28:50 Future-looking milestones
Some of the top takeaways:
- One-shot and few-shot learning emerged without being trained for. Gen 1.5 can learn a new task from a single demonstration, and Pete compares it to the GPT-3 moment in language. In one example, a robot taught to sweep a cube into a bowl with a brush used a banana instead. Given a dustpan, it held the pan with one hand, swept with the other, then tipped the cube into the bowl. Neither behavior was explicitly trained, and Pete sees this as a signal of where the model's generalization is headed.
-Generalizing to new hands remains a challenging problem for cross-embodiment. Physical hardware doesn’t stay static, and so cross-embodiment - the ability of a physical AI model to adapt to different hardware systems - is vital for success.
-Customer deployments are a valuable source of research inputs. Generalist actively partners with their customers for feedback, which they use to inform their research and make real-world evaluations.
-Generalist doesn't think in terms of "VLA vs. world model." Pete helped create early VLAs and has worked on world models, but he argues the goals matter more than the label, and the team is trained to think in a first-principled way when considering new research directions.
Watch the full episode at the link in the comments. Thank you to @peteflorence for joining us!
Greylock Partners retweeted
Sharing our thesis for co-leading the Series A in Parallax, the AI energy company
greylock.com/blog/introducin…
Greylock Partners retweeted
So Tenzai is #1 on @Hacker0x01's business VDP leaderboard - for the second quarter in a row.
Here's the news: this time we did it using an open-weight model anyone can download. Same result as the frontier model, ~30% cheaper per report, and only 3.5% false positives.
And here's the real news: These models are highly capable to power offensive AI operations at scale. Attackers can and will build malicious agents with these models.
The write-up: tenzai.com/blog/an-open-weig…
Greylock Partners retweeted
the most interesting thing happening in AI x code today?
speaking with @spirosx about production engineering, AI SREs, and how @resolveai has been out-executing the labs in the SDLC
thanks @baseten for hosting
luma.com/baseten-8li0
Greylock Partners retweeted
Baseten is now available as one of the first open-model inference providers in the @OpenAI B2B Marketplace.
Enterprise customers can use existing OpenAI commitments for open models served by Baseten (Codex or the Responses API). Run what makes sense for your enterprise—open, closed, or both.
Greylock Partners retweeted
Excited for @GreylockVC to partner with @CarlSchoeller and the @parallax team to build the leading AI energy company
@CarlSchoeller is on a relentless mission to build purpose built turbines that will power the next wave of intelligence



























