Welcoming our First Dedicated Select/Spring Fund Partner Sri Pangulur

Sri Pangulur Announcement Image

I’m excited to welcome Sri Pangulur, a proven enterprise infrastructure, developer tools,  and SaaS investor and operating leader, to the team as our newest and eighth partner. Sri will be our first dedicated partner for Select/Spring Funds. He will be partnering with entrepreneurs focusing on enterprise infrastructure, AI, developer tools, and SaaS. These companies will be primarily at the Series B stage and we will invest in them out of our Select/Spring funds, which represent approximately $800 million of capital. To date, we have invested in 23 companies from our Select Funds across all layers of the technology stack, and announced our new $375M Select III/Spring Fund in May of this year.

120 IPOs, 550 Investments, 225 M+As, 20 U.S. Funds, $3B Under Management, Founded 1969

Prior to Mayfield, Sri led the enterprise software investing practice at Tribe Capital and was an active angel investor before that. Some entrepreneurs he has partnered with include the teams from Apollo.io, LinearB, Docker, JupiterOne, Orum, Instabase, MindsDB, Abnormal Security, Hasura, HYCU, Nylas, Airbyte, Hightouch, and Oort.

During his operating career, Sri held sales and business development leadership roles across multiple enterprise infrastructure and SaaS companies. Prior to his operating tenure, Sri was a member of the investment banking division of Barclays Capital.

The team at Mayfield is collaborative and focused, where every new member makes a significant impact toward our firm’s success. Sri embodies the Mayfield Way, a set of of operating principles that guide our firm, and is a perfect addition to our team for the following reasons:

  • The founders he has worked with highlight his empathy for their journey, which is a key pillar of our People-First philosophy;
  • His unique combination of recent operating and investing experience enables him to bring a both-sides-of-the-table mindset when guiding entrepreneurs;
  • He complements our inception stage focus with expertise for companies a little further along. Key areas he has contributed to include rounding out executive teams for the next stage of growth, upleveling founder narratives for successful future financings, and leveraging his recent operating experience to build scalable go-to-market strategies, high-performance organization structures and business models;
  • He is not a fan of the recent *steroid era of investing* and brings a craftsperson approach which is a signature of our firm.

Sri outlines some reasons for his excitement in joining our team including:

  • Having known us personally and by reputation for a long time as a focused and high-performing team with a track record of success;
  • Our People-First culture and willingness to follow our own North Star;
  • The greenfield opportunity to further build our Select/Spring investment practice.

Sri joins us during a momentous year at Mayfield, one during which we raised $955 million in May across our oversubscribed Mayfield XVII and Mayfield Select III/Spring Funds in record time, and also announced our $250 million AI Start Seed Fund in July. 

We look forward to partnering with bold entrepreneurs on their inception to iconic journeys.

A People-First View of the AI Economy | TechCrunch

Founding Voices: The Right Dose of Reality

The right dose of reality

The tech industry is fast, competitive and noisy. As such, founders need to exude confidence and self belief if they want to attract interest, investment and build businesses that go toe-to-toe with industry giants.

Critically however, you can’t afford to buy into your own hype. Falling into hyperbole often means overreaching, which can kick off a cycle of negative flywheels for you and your organization.

“To be a successful entrepreneur, you have to be ambitious and optimistic. You have to believe you can topple VMware, or Amazon. But many companies get carried away and don’t back it up with a dose of reality.”


Co-founder & Former CEO, Rancher; Co-founder & CEO, Acorn

It’s important to have a bold vision for your company, but you need to prioritize pragmatism when translating that vision into goals and business expectations. That means setting attainable targets across your organization.

While temperate goals are less flashy, they indicate a disciplined and realistic approach to doing business. Eye-watering reach objectives are exciting, but they’re also meaningless if you can’t deliver. If anything, they open the door to a dangerous cycle of over-promising and under-delivering, which can hurt stakeholder confidence, and wear your team thin.

“Don’t confuse realism for a lack of ambition,” says Ursheet Parikh, who led Mayfield’s inception investment in Rancher and served on the board until their acquisition by SUSE in 2020. “Being realistic creates opportunities for your organization to win. You’re more likely to achieve practical goals, and the act of achievement is a morale builder; small victories add up, and they help your team develop the confidence needed to tackle more aspirational objectives.”

Ursheet Parikh


Human & Planetary Health, Enterprise

Founding Voices: Dream Boldly, and Move with Purpose

Dream boldly, and move with purpose

Founders can sometimes feel pressure to “underreach” with their ideas, sacrificing ambition for accessibility and immediate term business viability. While it’s a good instinct to show your product is feasible, you shouldn’t hamstring a grand idea to fit it into the limitations of today’s means and technology.


“We want to produce cultured meat at a price point that competes with factory farming, and that requires creating a fundamentally new approach. If we can do that, then a lot of things that are currently impossible become possible.”

Co-founder & CEO, Prolific Machines

Ambition is valuable, but how do you differentiate your idea as a serious contender to fundamentally change your industry, or indeed the world?

Beyond telling a stellar product story, you must showcase your sweat equity. If your idea is a breakthrough away from feasibility, then know the failure modes in your sleep. Talk to leaders in the field and hire them. Demonstrate mastery over your technical challenge, build the right product and get customers involved at the very beginning. Then you’re ready to disrupt industries.

“I want people to come to me with unique insights into keystone problems that can change the world, if solved,” says Arvind Gupta, who led Mayfield’s inception stage investment in Prolific Machines. “For me, backing something truly game-changing is an opportunity to contribute long-term to humanity. As a founder, be prepared for a long, unpredictable road. When things look great, stuff will go wrong. Likewise, as hope may be dwindling, perseverance creates opportunity. Excellence in every dimension is what it takes to change history. Only when people see that will they start to believe.”


Human & Planetary Health

Founding Voices: The Road is Longer Than You Think

The road is longer than you think

In startup culture there’s plenty of talk about grit and the ability to put your nose to the grindstone. While it’s impossible to overstate the value of work ethic, a piece of the conversation that’s often overlooked is the necessity of patience.

The best founders have a long-term perspective on success. They know there will be mistakes and setbacks on their journey, but also that not every opportunity is a good fit for them. What allows them to endure, and capitalize when the time is right, is a spirit of calm persistence.

“The problem most entrepreneurs have is that they give up too easily. As an entrepreneur you have to be very patient.”


Co-founder & CEO, DevRev

An important part of patience is pacing yourself. There will be periods where you need to step on the gas, toil around the clock and chase down every lead, but this can’t be all the time. A breakneck pace is naturally unsustainable, and maintaining one for too long leads to burnout and bad judgment.

“A big part of growth is learning how to pick your battles,” says Navin Chaddha, who led Mayfield’s inception-stage investment in DevRev. “I’ve been a founder, and I understand the urge to pull all the levers and attack every single problem. But as an investor, I’ve seen companies take 10, sometimes even 20 years to exit. That’s why I keep saying founders need to treat company building like a marathon, not a sprint; you absolutely need to pace yourself if you want to make it to the finish line.”

Managing Partner

AI, Enterprise, Semiconductors

Founding Voices: Embracing Serendipity

You don’t need to overthink it

The entrepreneurial journey is intimidating, and for good reason. You’ll work brutally hard, do things you’ve never done before, and encounter all manner of new obstacles. But while it’s important to respect the challenge of company building, you can’t afford to overthink the process.

“Becoming a founder or joining an early-stage startup does not require a well-defined plan. Build expertise in a few areas, keep learning & growing, develop positive relationships, and pay attention to market transitions. After that – embrace serendipity; sometimes the right opportunity or idea simply shows up.”


Co-founder & CEO, Auradine

Having a clear direction and vision for where you want your company to go is essential. But markets, technology, or even your own interests are always liable to change. That’s why a hyper-detailed plan can often make it easier to derail.

Build a foundation of skills that will aid you on your journey. After that, focus on being open-minded and perceptive. Good opportunities often emerge suddenly, and from unlikely or unfamiliar places. If you’re too focused on following a rigid plan, you’ll likely miss them.

“Not all plans need to be precise and far-reaching,” says Navin Chaddha, who led Auradine’s initial funding round, and sits on the company’s board. “Rajiv has done the company building dance many times, and he knows the value of being patient, being mindful, and letting opportunities present themselves. There’s a time and place to be really detailed and long-term with your thinking. But early on, it’s important to be flexible and receptive, rather than try to force a specific path.”

Managing Partner

AI, Enterprise, Semiconductors

CRISPR+: The Next Generation CRISPR Systems and Applications | SynBioBeta 2023

Ursheet Parikh:

Good to see all of you. I’m Ursheet Parikh. I’m a partner at Mayfield where I lead investments in human and planetary health. Mayfield is one of the founding venture capital firms in the Valley. It’s been around since 1969. We partner with entrepreneurs like Lucas very early, tend to be seed or Series A, sometimes Series B. But it’s a joy and pleasure for me to have Lucas in conversation today. Lucas is one of the founders of Mammoth Biosciences. It’s been a delight to see them just hit it out of the park and the velocity of how they have developed more and more things like unique CRISPR systems and how they’re enabling that ecosystem. With that, let me start out with something. Lucas has a nickname, and it’s the CRISPR Whisperer. And Lucas, how did that come to be?

Lucas Harrington:

Definitely it’s been a very rapid trajectory that we’ve taken since starting in Jennifer’s lab. But it really started maybe back with this concept actually that I think we encountered way back in middle school, which is something you might be familiar with, Pasteur’s quadrant, which is basically this idea of applied basic research. And once I started at Berkeley in Jennifer’s lab, that really was the perfect distillation of this concept, where if you’re doing very basic research trying to understand how CRISPR systems work – in this case protect bacteria – applications just flow naturally. And it’s a really unique section of biology where you can do that basic research and have a lead application. It snowballed as we started to understand this natural diversity. We’re also collaborating with Jill Banfield’s lab, which is metro focused on metagenomics and really just mining diversity naturally.

And then from there we were able to find some really cool new CRISPR systems that unlocked this whole new section of using CRISPR, specifically being able to use them beyond the liver and beyond XPR applications. And that was really one of the foundations of Mammoth, and from there it’s just been basically taking the things that we were doing in Jennifer’s lab, which were very hands on, and figuring out how do we actually build automation to do that on a scale that’s three or four orders of magnitude beyond what we could do as graduate students in the lab. And here we are today, now thinking about how we actually apply those for patients.

Ursheet Parikh:

I think Lucas is being very modest because I think Lucas and his team at Mammoth have probably been one of the most prolific survey discoverers and developers of new CRISPR systems. I’d love, Lucas, for you to walk us through just that history – where were things in 2014 when the first set of CRISPR companies were formed? And how has the field developed, and what have been some of the cool new systems that you and your team have developed?

Lucas Harrington:

I’ll preface this by saying from my perspective it’s still very early days for gene editing and for CRISPR. We’re just scratching the surface of what the promise is. But if we rewind the clock back to 2012, or maybe even before, CRISPR specifically was this scientific backwater that no one in the mainstream media was that interested in. And Jennifer definitely was very focused on RNA biology and how this worked from a basic science perspective. And it really was just happenstance that these tools they were working with were very applicable towards genome editing and that they worked in mammalian cells.

As with a lot of times in science, the first thing that got discovered just got wind behind it and that started to move forward, and that’s really the premise of a lot of these first generation CRISPR companies that are based on Cas9. But that said, with the haste to get those things advancing into the clinic, there was definitely a missing piece of what else was out there for gene editing. And there’s actually hundreds of thousands of different CRISPR systems that just exist in nature. Probably just in the bacteria in this room, there’s probably thousands of CRISPR systems.

What we really decided to focus on was looking at that diversity and saying, all right, statistically the chance that we pick the first system and it’s the best system seems very improbable so let’s actually understand that diversity, see if we can overcome some of those limitations of the legacy system Cas9. We originally focused on ultra-compact CRISPR systems. We’ll probably talk about it today, but the biggest challenge with gene editing is how do you actually get it into the right tissues. And these ultra-compact systems are much easier to get into the target tissues using delivery like LMTs or AVs.

And yeah, from there we started to build on top of that, what we call CRISPR+, actually being able to not just use CRISPR as a pair of scissors, but to think about them as more precision tools that you can use to do epigenetic regulation, application or more precise gene correction. And now we’re really looking towards how we put all these pieces together in terms of delivery technology, in terms of the gene editing systems, to move beyond just editing liver, which is really where when you see all the progress in the news for gene editing. I would think of it more as a good demonstration of the utility of CRISPR, but falls short of curing most genetic diseases, which is ultimately the promise.

That’s really the timeline for the company and for the field overall. And going forward, yeah, it’s about progressively being able to treat more and more diseases that are moving away from rare genetic disease and actually thinking about more common and prevalent diseases that have huge unmet needs for patients.

Ursheet Parikh:

Let’s take the ultra-compact systems. What is Cas9 size and what would be maybe top two or three examples from Mammoth of the ultra-compact systems? And what would become the applications that unlock these new systems?

Lucas Harrington:

The first Cas9 systems, to put some numbers on it, was about 1,300 to 1,400 amino acids, in terms of bacterial proteins, a very large bacterial protein, not compatible with most of the viral delivery methods that we use. The newer systems that we use, a few of them would be CasPhi, which was for us, it’s one of our larger systems, but even that, it’s about half the size of those normal Cas9 systems, so that’s about 700 amino acids. And then our most compact systems go down to about 400 amino acids. You’re talking about something that’s about a third or less of the size of the original CRISPR systems.

What that enables, again, going back to the key challenge of how do we actually deliver on this promise for gene editing, is it allows you to use delivery vectors that we have, namely things like AAV, which have a very, very constrained packaging limit. And it allows you to not just fit the CRISPR system, but fit all the other things that are needed for creating the bespoke therapy for a particular target.

One thing to think about and to keep in mind with CRISPR is that CRISPR is the heart of the therapy, but there’s really a whole ecosystem of other things around that that’s required to get this to patients, from the genetic understanding to the regulatory elements, and then of course the delivery vector. When we think about enabling CRISPR, for us it’s thinking about how do we actually innovate on that core component, the CRISPR system, so that we can better use all these other components that are required to push therapies forward.

Ursheet Parikh:

Pre Mammoth, most of the CRISPR companies went with Cas9, and they decided to just build the application out of that. But there was also the tendency to want to keep it just to themselves and do it all their own. And one of the core founding premises of Mammoth was that this is going to be a platform that enables an ecosystem like Microsoft for PCs, or Apple with mobile phones. There’s a core set of things you do well, there’s a subset of applications you develop, but you really focus on the few things you do well and then partner with everybody else along the way out on that.

And you developed a wide range of applications. As you were doing the ultra-compact system on edit, what else did you end up finding, like diagnostics, as potentially interesting applications of CRISPR and how they go beyond healthcare? And I’d love to come back to the epigenetic and the CRISPR+ stuff, but while ultra-compact systems are happening, you were essentially developing CRISPR for beyond therapeutics.

Lucas Harrington:

At its core, CRISPR is a way to program a protein to a sequence of interest. And that can be in the context of a genome, it can be in the context of in vitro diagnostics. This also goes back to our work at Berkeley and Jennifer’s lab – one of our co-founders, Janice, was very interested, again, in the basic science of how a CRISPR system cuts its DNA target. And in doing that, and running radio-labeled gels and very old school biochemistry techniques, we were able to start to see that some CRISPR systems have this feature where they don’t just cut the target that you program them to, but they turn on this collateral activity that allows you to detect a signal. That led immediately to development of CRISPR for diagnostics, which was a field that really hadn’t been contemplated before. 

But beyond that, when you think about it in the genomic context, we’re largely focused on human health internally. To Ursheet’s point, the applications of CRISPR go well beyond that. Of course many of the companies that you might hear about are using CRISPR for one application or another. Strain engineering is definitely a key area, especially when you’re talking about more exotic organisms that don’t have the robust molecular biology tools that we have for things like OI and as well as agriculture. I think agriculture is actually where we’re going to see probably some of the biggest and most immediate impacts for gene editing.

And yeah, it is important for us as a company to enable other groups to do this and really build a system of applications beyond what we can do internally. Because even with our rapid growth, there’s only so much we can do, even within genetic disease there’s only so much we can do, and so making sure that the tools that we develop get disseminated more broadly is definitely a key thesis for us as a company.

Ursheet Parikh:

One of the things that in the early days of Mammoth was to align on the values and the mission, and the idea being that if the world had X number of products without Mammoth, with Mammoth it should be 10x or more. And that could only happen if we have an ecosystem and platform kind of mindset, which was actually pretty different from what most people were thinking about at that time. Going back to building and developing new CRISPR systems, you spoke about size. What are some of the other attributes that have made these CRISPR systems better?

Lucas Harrington:

As we think about CRISPR, the 1.0 technologies were just making a cut in the genome. In order to be able to do other types of edits, you really need a repertoire of different systems. Size is one of the foundational things that a lot of things are built upon, but specificity, especially as you move to some of these other applications, is also a very, very important one. When we talk about treating diseases that have some kind of standard of care already, those safety burdens become higher and higher, where there’s really no tolerance for any off-target cutting that might happen. Mining through the natural diversity, we’re able to find systems that are much more accurate. 

And yeah, another key thing that we think about is this portfolio approach. When you think about Cas9, there’s a lot of applications that have been built on that, but there’s a lot of applications that you can’t do with that system. Generally we don’t want every company to have one little area that they can work on, but for us, we actually have the breadth of tools to be able to widely use these systems, whether it is for epigenetic editing or for editing plants or for diagnostics. But you have all of those systems under one roof and you can actually choose the best system for the job as opposed to just being stuck with whatever you started with.

Ursheet Parikh:

I think that is a very interesting and important attribute. Because I think that fundamentally works with the platform model. If you are developing an application, in this case an application to get you a diagnostic or therapeutic, you want to be able to use the best tools available to you to solve the problem, rather than only the tool that you had licensed out. And structurally that is why partners find Mammoth to be a really good partner, because they know that the innovation engine at Mammoth will keep on finding more tools. And if they’re trying to solve the problem for a specific disease, they will be getting the best tools.

In contrast what has happened is that there have been companies that have taken each version of the incremental development in CRISPR and have become dedicated to it. And from an application developer or a therapeutic company perspective, that becomes a big challenge, in that they may start working with a partner only to find that the version of the tool they need is actually sitting with somebody else.

And then I think from an investor perspective, either private investors or public investors, you end up having to worry about whether you are picking the right tool, or the values of the people who created it. Are they in on this company, or are they onto that next version or the next shiny object? And this is fundamentally this thing about building things to last for the long haul. So now, Lucas, introduce CRISPR+. Where do you draw the line from all of that and how that is working to where the future is headed?

Lucas Harrington:

CRISPR+ is a term we came up with a few years ago to really capture this evolution of CRISPR beyond making double stranded cuts as a genome editing tool, recognizing that most diseases cannot be cured by just making a break in a genome. A lot of this is thinking about CRISPR as this method to search out a sequence, really this honing system, and to fuse on different modules that are going to change the effect that you’re getting. This can be things like epigenetic editing, where you’re actually permanently changing the methylation of the genome, which can silence genes, or turning them on. It’s also more precise methods to not just correct things that you can knock out, but actually write in sequences that you want. This is really one of the key pieces of how we develop this to more broadly address genetic disease.

One of the dirty secrets of the CRISPR+ field though is that for a lot of these companies, you’re taking a large system, a Cas9 system, and you’re now fusing on even more machinery, even more baggage onto those systems. You end up with these systems that are so enormous that they really have pretty limited applicability except in the ex vivo applications.

It’s really been a natural transition for us as a company where we’ve got these very, very small CRISPR systems which leave open all this payload in traditional delivery vehicles where we can now fit that machinery in and efficiently deliver it to tissues in vivo. And it wasn’t the original or only reason that we developed those small systems, but being on the forefront of that, it’s really positioned us to be able to push those forward into the clinic.

Ursheet Parikh:

As you look at the crystal ball going forward, what are some of the diseases that you think you will have therapies in the clinic in the next three to five years?

Lucas Harrington:

Of course in the field overall, most are closely watching and anticipating that we’ll have the first commercial sickle cell programs, again, a very exciting milestone for the field, but still in an ex vivo application. We’re seeing a lot of activity around rare genetic diseases in the liver. But really where we as a field want to be moving is towards these much more prevalent, serious unaddressed diseases, especially as we think about degenerative diseases in the brain, from the CNS or skeletal muscle or the heart.

Eventually as we get these proof points, especially with rare disease, it’s about moving more towards preventative medicine, things that maybe aren’t as acute but that we know 10 years down the line or 20 years down the line, you’re going to have some kind of adverse health consequence. Necessarily we need to build up the safety profiles of the systems before moving into those, but that’s really what gets me excited. And for me a lot of the initial programs for both Mammoth and otherwise are really to try and develop the systems so you can go and go after things like curing Alzheimer’s or Parkinson’s, things that many people have had personal experiences with.

Ursheet Parikh:

It is definitely very, very fabulous. Lucas, what’s the secret? How is it that Mammoth’s able to do these things so much better? And clearly the conversation that everyone’s talking about is generative AI, a lot of large language models and how AI is going to try to change everything. And I’d love to hear a little bit about what enables your success in this research and research product area. And how much of it is technology, how much of it is culture? And what kind of technology?

Lucas Harrington:

A big part of it is the team that we’ve been able to assemble, as well as the commitment to innovation. Going back to the early commentary, there is a tendency for some companies to take something that’s working and just harvest it, just think about how to monetize it. We definitely take a longer term perspective, and this isn’t just the internal management team. But it does require a cohort of investors that are supportive of that and that are thinking on long time scales of how we make an impact on the species. That’s the foundation.

And then to think about it more technically, a lot of it’s just the science that goes on internally. Going back to how we were doing this even in an academic setting, a lot of it is very, very creative approaches to finding the systems, the models that you’re using. There’s of course a lot of excitement around AI recently, but most of us know in biology that these genomic data sets are really built for machine learning and it’s just something that just happens naturally, that we use these tools and develop these tools. That’s been a key part of it.

As with any AI or ML approach, it’s about having very clean, good data sets to start with. And that really was the foundation, is this metagenomic engine that started this, and now it’s much more around protein engineering and continuing to evolve and adapt systems. But no, technical things aside, a lot of it is the culture of the company of really what we set out to do and keeping that vision in mind as we continue to grow and not letting our success distract from the long term vision.

Ursheet Parikh:

I think you’ve brought up the culture and the long term mindset we’ve made. Changing gears, what has been your growth journey as from scientist to entrepreneur, manager and leader? I’d love to get some look back on your journey and both what are your learnings and what is your advice for anyone that’s really take the benchtop science and translate that into real products?

Lucas Harrington:

It’s definitely been an interesting and awesome opportunity to be able to do this. Most of the time that people spend in graduate school doesn’t prepare them to actually manage and interact with people. You learn the science, you’re a technical expert, but a lot of it is progressively, and by no means are me or any the founders perfect at this, but progressively getting better and better at orchestrating the team and taking that scientific knowledge, using that to actually motivate and build credibility with the group.

It is a challenge, and not all PhDs make it through that hurdle. And one of the big areas that probably we should adapt is the education system. The graduate education system is a much bigger focus on just communication generally. It’s important for entrepreneurship and of course leading teams and building teams, but it’s really important for of course anything we do pretty much, and just also educating the broader public about what the opportunity is of the tools that we’re building or the broader synbio community. For us it’s just been also of course working with mentors and having coaching, being open to feedback and really taking that feedback to heart.

Ursheet Parikh:

What is your process when you are trying to recruit or bring in someone? And how do you start with a benchmark of excellence for the role? Because there’s so much that you don’t know. In our opinion, a company’s fundamentally limited by the learning ability of the founders. Independent of the role they take in the company, their influence is really broad, and it does require that they really develop a broad aperture and effectively bring their own infrastructure for learning very quickly. I’d love to hear what your personal process is, and then what you look for.

Lucas Harrington:

Early on in the company when I didn’t have much experience in hiring, my initial instinct was to just hire the people that seem the smartest, just the technical experts. But if you just push a bunch of technical experts together without actually curating that group, it very quickly crumbles and falls apart. A lot of it is hiring, maybe indexing less now on that and indexing more on is the person actually passionate about the company? Are they going to be committed? Are they agile and able to learn quickly? Because most of the stuff we’re doing, you’re not going to find someone off the shelf who’s done it before. And then of course are they going to work well within a group and actually be able to build something bigger than themself as an individual.

Often in interviews, I’ll ask someone to teach me about something that I have a good sense of. And how they respond to that and how eager they are to really dig into what they know is a good signal for how well they’re going to be able to adapt to a startup like Mammoth.

Ursheet Parikh:

We have about 10 minutes left. I can continue asking lots of questions, but if any of you guys have questions, raise your hands.


Thank you very much, Lucas. Now I’m quoting Jennifer. She said that a cure is not a cure if people that need it cannot afford it. Which are the bottlenecks next to get the point that everyone can afford CRISPR therapies?

Lucas Harrington:

Definitely it’s not an easily solvable challenge for sure. It is important to have that perspective over the lifetime of the technology as well. Build the roads to your first model and then try and build more afterwards is definitely something that I think resonates here. But it’s not just a question about the intervention. A lot of this is that the healthcare system is built to have this chronic care model where you’re giving someone a pill every morning or giving them an injection every month. And CRISPR does have the potential in terms of the curative things to actually condense that treatment cycle into one treatment. The biggest cost factor is going to be also about the regulatory strategy of how do you get multiple successive things into the clinic without having to reinvent the wheel.

Because we’re building this as a platform, the roads to the first program, again, will be expensive, but the successive ones should be able to stand on that. The FDA, they’re very smart people and they’re trying to figure this out and grapple with it. But there needs to be some kind of platform approval process that also allows you to move into rare and rare genetic diseases. No silver bullet, but of course, as everyone knows in healthcare, the cost is usually not the cost of the therapy, but it’s actually all the investment that goes in the front. And a lot of that is driven by what’s required by the regulatory process approved that it’s safe. I’d say thinking more creatively about that, especially after we have these initial successes, is going to be important to drive the cost down of these therapies.


Can you expand on that at all on the regulatory side? Is the FDA engaging? 

Lucas Harrington:

They’re willing to talk about it now. It’s still too early in the technology life cycle for them to be thinking about that because it’s still this one-off thing. But even if you look at one genetic disease, you often have mutations scattered across the disease target. It’s really rare that you have just one perfect mutation. And that’s of course what most of the programs are focused on. What you want is a way to get a broader approval for the platform, and then with CRISPR being a platform, you can just change out the guide. And having some kind of minimal safety requirement of actually understanding that that guide is actually the same as in terms of safety from the perspective about targets and things as the other guide, and then being able to get a leg up on the program and actually more broadly address the patient population.

It’s still too early, and whether it’s the FDA or MedSafe or EMA that drives this, it’s going to play out of course as most regulatory policies do over the course of years and years. But yeah, all of that said, the access issue is definitely important, but there’s also treatments that need to be delivered immediately, and that’s the first step that needs to be taken even to broaden that access subsequently.

Ursheet Parikh:

When I’m looking at regulators, this is what I advise everyone to think about. Recognize that they have a hard job. They don’t get to market fast. They do end up having to take a lot of the pain for anything that’s done prematurely. Having said that, they went through this not because they want to stop you. Essentially most of regulators, they’re scientists, they’re engineers. They care. They want things to get to people. That’s why they entered that field.

We do make a common mistake that a lot of people do, is not talk to regulators early enough. And because if you really think about it, one of the best things you can do is develop relationships. If there is negative news, you might as well get it. You want to go ahead and engage in that kind of conversation. And over time you do see a good change in mindset emerging. And often what happens is I think emerging companies actually make that as a bigger mistake than some of the larger companies. Because the larger companies will often have a lot of dedicated people for talking to regulators so they get to input things.

The advantage you have as an emerging company is that your senior leadership and your best scientists can actually engage in the conversation. The regulators actually like talking to you because they are not talking to layers and layers of corporate BS. They are actually talking to people who will acknowledge, help them understand by breaking the core issues down around that. 


Yeah. Lucas talked about how AAV imposes delivery constraints on how big the Cas9 can deliver. Could you alleviate that by using mRNA? mRNA and LNP, now they’re talking about delivering self replicating DNA.

Lucas Harrington:

It’s a great technology. The challenge there, especially when we’re talking about programs in the clinic, is it’s really constrained to the liver. And it’s a pretty small subset of diseases. The liver is a great place to target. It’s this production place for a lot of things. But that said, it’s still pretty constrained, and viral delivery, specifically AAVs, are still really the gold standard for everything ex peripatetic.

If I’m completely honest, delivery from the technical hurdles is more challenging than gene editing. We build something that goes and cuts a sequence in the genome, and that’s great for us that we’ve got the easy task. But delivery is really hard to get systems that work effectively and safely across different models as well. Our perspective has been, we’ll be agnostic in terms of the delivery technology. And as, LNPs mature and hopefully you can move ex peripatetically, we’re ready to use those. But what we have today is that our delivery vectors, in terms of the treatments that we want to push forward, let’s take what we’ve got, versus compounding risk with a bunch of new elements that are going to be more risky altogether.

Ursheet Parikh:

Well we have time for one last question.


If you could spawn one CRISPR system that trumps the current limitations of the other ones, which would it be and why?

Lucas Harrington:

Well I’m biased, but I would say it’s our nanocas system, and largely just because pretty much everything we test about it addresses a lot of concern. Off-targets, the safety of the system, we’re talking about regulatory, is definitely one of the things that gets brushed under the rug, and especially in ex vivo applications. And Cas9 is definitely pretty sloppy in terms of where it cuts in the genome. That’s what scares us about CRISPR, is that you’re making any unintended consequences. The nanocas system, not only is it a third of the size, but also has the specificity advantage, it has the ability to work in all these CRISPR+ applications. But that said, I still think that repertoire approach is pretty critical towards addressing the diversity of genetic diseases out there.

Ursheet Parikh:

Well, thank you all, guys. This was great. Thank you, Lucas.

Built to Last – Where Will the Next Big Companies Be Created? | SynBioBeta 2023


Raj Judge:

Well, hello, everyone. Great to be here. Looks like it’s a great turnout this year, and we’re excited this morning to talk a little bit about built to last companies, and where the next big companies will be created in synthetic bio. And of course with me is Ursheet Parikh, partner at Mayfield, and we’re going to jump right in. 

Ursheet, let’s talk first about the current environment. We’ve got valuations that have plummeted. We’ve got capital access problems. The IPO market is shut down. A lot of negativity, a lot of doom and gloom, if you will, in the synthetic bio market, as well as in the technology market as a whole, and we’re not sure where the economy is going. So I wanted to get your thoughts just generally on what you think about the market and where things are going to head over the next couple of years. Are we going to be in a doldrum for the next five years, or are we going to be coming out of this in another six months, or are we going to be stagnating? What’s going to happen?

Ursheet Parikh:

So first, good morning, everyone. I’m really excited to be here, and I’ve never been more excited about our space. I know, with all the various things that Raj alluded to, it can feel challenging, but I think we are set up for the absolute Cambrian explosion of innovation that is coming from startups. The one thing I would say is that we are set for synthetic biology to fundamentally go mainstream and transform all of our lives in the next five, seven years.

What are the things about the current environment that make me feel so excited? So if you remember the first SynBioBeta ’09, it’s right in the depths of what felt like a tough environment, and so it’s probably easier to draw similarities to that. But what has changed are the fundamental demand drivers for our industry. They are coming because consumers want better products, and making them with the old Industrial Revolution technologies isn’t sustainable – and it also doesn’t necessarily create the best products either. And so, you have consumers who want amazing products, and biology as a technology has emerged as the core platform that can drive that. So all the advances we have in digitizing biology, engineering biology are where the cost drivers are going.

The second thing that has happened is, to see an industry like this emerge into the mainstream, you need policies. And I think, in the last several years, we’ve seen an amazing alignment of policies. Some of it got driven by the need to bring back the supply chain. Some of it got driven by things like the Inflation Reduction Act that even brought the biggest greenhouse gas emitters in the oil and gas companies to start wanting to do things with synthetic biology.

But then there’s also the big trends that have emerged like AI. And what AI is doing is, if we were to go back and sort of manufacture with biology here in the US, it was not going to be the way bioreactors were done 10, 15, 20 years ago. It’s going to be done much more with an AI-powered system at every step of the workflow. This could be in high-throughput screening to find new strains. This could be in automation. This could be in generating new products.

So I’m just so excited about this domain. And to get over to the other side, I think all of you in the room will clearly be innovating, but you’ll also have to be very methodical, very thoughtful about how you really make every dollar count because of where the interest rates are. The cost to rebuild the world with biology has gone up dramatically, and capital is going to be scarce. And so, we have to just be able to demonstrate that we can provide returns that are going to beat pretty much any other asset class.

Raj Judge:

So I love the optimism, definitely contrarian to the current mood in the economy, so that’s wonderful to hear. But we’re in a tumultuous time. We’ve got China relations. We’ve got the Russian War that we’re dealing with. We’ve got all sorts of different issues. We’ve got India growing as another potential location and market. So lots of different contractions and expansions occurring, and I know that spells opportunity for some, and it spells challenges for others. But the whole geopolitical climate and the whole geopolitical situation globally provides us with a lot of different complexities that we’ve never really had to face before. Tell me what you think about that a little bit, Ursheet. I’d love to hear.

Ursheet Parikh:

Yeah, so I think, to me, I’m looking at everything that is happening at the geopolitical level, and it’s fundamentally creating new demand drivers for things to happen in the US. I touched upon briefly on how you want to be able to go ahead and manufacture close to home. This SynBioBeta is also feeling and sounding different because we have a lot more conversation about healthcare and applications of synthetic biology in healthcare.

But the top trend that I’m seeing right now when I’m talking to a lot of people in big pharma is, how can we leverage the Inflation Reduction Act to actually start manufacturing antibodies and other biologics in the US? And if somebody’s going to go ahead and do that, they’re not just going to go and do it with the older technologies. People want to see, how do I use a different manufacturing stack? How do I use different workflows? How do I set it up to be targeted or customized better on that end?

We have been involved in a company that’s actually converting methane into fertilizer on the spot at farms, and it’s the kind of company that is clearly seeing great demand from anyone that is doing organic farming because organic fertilizers are expensive. This is using methanotrophs, but this is also seeing just a huge level of demand from the major oil and gas companies. And then, you end up having the elevation of synthetic biology as a core biosecurity initiative. And if you look and talk to our classified agencies, or you look at the government strategy, AI, quantum computing and synthetic biology are seen as these strategic technologies and platforms for the future.

So by all of these issues, the energy independence and the worries that came because of the Ukraine thing, this has fundamentally created demand for self-sufficiency and a green economy. And who else is going to make it? It’s all of you guys in this room. It’s the synthetic biology ecosystem that’s going to go ahead and make it. So I’m excited for it.

Raj Judge:

That’s interesting. Very, very helpful insights. But let me take a little more controversial probe into that question that we’re talking about on geopolitical situations and the Inflation Reduction Act that you talked about. Some say that the biggest benefactors of the Inflation Reduction Act are the largest greenhouse gas emitters as well, and they’re getting the benefit of the green dollars. So how does one look at that from an emerging company standpoint or a new company standpoint? How do you take advantage of that? Because it seems like the big guys are really getting a lot of that advantage, and politically we want to obviously support the larger companies as well on the global stage, but we also need to make sure that innovation is still occurring and younger companies are allowed to grow with those dollars.

Ursheet Parikh:

This is a very real problem. And so, if I can give an example to illustrate the point that Raj is asking us about is, if you look at the Inflation Reduction Act, the top recipients actually so far of the funding from the government have actually been in Texas and Georgia. And a disproportionately high number of them are actually the major oil and gas because in the Inflation Reduction Act, there is a huge incentive to move to a hydrogen-based economy.

A lot of what we do in synthetic biology with the green stuff really marries well with the decarbonization that’s enabled by electrification, and so there’s companies here which are working on doing things with hydrogen, using microorganisms that can go out and work things with them like the example that I just gave. But at the same time, what you now have is the large oil and gas companies being able to claim that they are able to go ahead and make hydrogen out of natural gas, and the resulting CO2, they’re just going to go pump into the ground, and hopefully it’ll stay away, and oh, by the way, they know how to pump CO2 into the ground because they’ve been doing that with fracking.

So you can see how some of these best intentions can suddenly make the fossil fuel-based economy even harder to beat. And when you are working with the government as a larger company, you just have more resources, all right? You have people who can do government affairs, you can talk about working through policy, things like that. This is where I’ll give a call-out to John. I think John Cumbers, who’s been the convener here, has done quite well in educating and bringing a lot of our community together in having these conversations. But I also do think that, as a community, we also need to get more politically active. We need to engage in conversations with policymakers, lawmakers, and then take and share the best practices that we have so that we don’t find that it’s the old economy companies that in effect end up leveraging and benefiting from all these demand dollars, but with greenwashing.

So this is a problem, and I don’t think we have a magic formula for it other than, all of us have to get engaged, involved, and work through it with each of our local jurisdictions, politicians, and senators, while sharing best practices on how, when we do the projects. If you’re doing a new bio-manufacturing thing, how do you go ahead and leverage the best of these incentives?

Raj Judge:

Yep. That’s definitely the case, and I think that we’ll have to spend a lot more time on this trying to understand where the complexities can be taken advantage of, if you will, for emerging companies and new technologies. Because we don’t want this to turn into part two of the solar energy movement 10 years ago, where there were a lot of government dollars, but ultimately they didn’t really benefit the innovation cycle that people wanted it to benefit. So more to be seen on that.

The other thing that comes out of the geopolitical state that we’re in is that, over the past 20 years, we’ve really enjoyed a free economy where R&D could get done, particularly for companies that are innovating in different geographies, whether it was teams in China working with teams in the US, or teams in Europe working with teams in the US, or for that matter in Russia and India and all of that. And now, what we’re seeing is this very nationalistic approach, even by the US, which is something that we haven’t seen before, at least in the last 20 years in technology.

And so, we’re having problems with companies developing AI-based synthetic bio or AI-based technologies and exporting that between borders. So we’ve got a company, for example, that wants to set up an R&D team in China as well as in California, and they’re having problems doing that because of the government restrictions around the export of AI algorithms and the like. So what do you see that, and how do you see that impacting the way companies are going to grow and how they’re going to continue to take advantage of talent that’s global?

Ursheet Parikh:

Yeah, I think for large companies, be it large conglomerates, large pharma companies, large companies in the industrial space, I think they have the infrastructure and the ability to actually do development in multiple geographies. I think for emerging companies, it’s going to become increasingly harder and more expensive, if you are operating at the intersection of synthetic biology and machine learning or AI, to be in multiple countries or multiple continents without running afoul of many of these rules.

So the thing that I’m most excited about and what helps drive the synthetic biology economy down the cost curve to be at par with the broader mainstream legacy technology is the ability to have AI in all of its various forms. From the old form of reinforcement learning to the newer forms of generative models, it is basically going to help us really run a lot of experiments in parallel, look at the data, synthesize, optimize. It takes what we do in innovation with biology from the old school world of biotech, which was often set upon accidents or divine inspiration, to an engineering optimization-based model.

But as I said, this is happening. If you talk about the national priority technologies, like quantum computing and synthetic biology, they are far from being real. And I think those cross-border considerations will become factors. And by the way, we’ve been involved in companies that have actually been transformed and have been made possible because of AI. One of the companies that we engaged in early on was Mammoth Biosciences, and they have become one of the most prolific innovators in the CRISPR system space. And there’s actually a session from one of their founders later this afternoon that I’ll be moderating. What fundamentally made it possible was their ability to really master high-throughput screening with a high level of automation and then using machine learning to be able to go ahead and identify candidates, and then marry that with the web biology to go do that.

Now, that world of AI was much more about, how do I use AI to screen, look for stuff, but somebody still had to then figure out, what is going to be my next set of things? What do we do, right? Now, you take that with generative AI and large language models, and you can start even taking the other side of the equation and amplifying the speed on that, and that whole loop then becomes very significantly exhilarating.

So one of my favorite books is from the nineties, from the founder of Intel, Andy Grove, and it was called Only the Paranoid Survive. And the essence of what he says is that, every decade or every five, seven years, something happens which is such a 10x force that shapes the world. And you may think it’s not relevant to you, but it comes very quickly, and it will touch every job, every business, every industry. And I would say that, for our industry and just generally for the economy, I think generative AI is actually going to be one of those forces.

It doesn’t matter what your business is, whether you have nothing to do with AI, whether you’re just doing manufacturing of reagents or whether you’re providing services. I would definitely encourage taking a step back and tuning in to see what is happening in that world and then dreaming on how it could potentially impact your business because 12, 24 months from now, I personally would be shocked if your jobs have not been touched in some way, shape, or form. And I actually think they will have been touched for the better because inherently it’s the kind of technology which is really far from replacing people, but it is actually going to be great for augmenting people to do their jobs better.

So if there was one takeaway to take from this session, it’s probably that, as alien as it has felt and far away and esoteric and behind the scenes, there is a high probability that it can actually be used to transform and accelerate your business and make it much more capital efficient. 

Raj Judge:

So there you go. Paranoid survival is what I picked up off of that. I think Winston Churchill even talked about that at one point. Let’s talk a little bit about the dovetail between how digitization software and AI are impacting synthetic bio and funding because we haven’t talked about funding, and funding is a difficult environment. It’s a difficult thing to do, and traditionally software companies get to revenue faster. They have less capital intensity. But at the same time, software is starting to get a little bit more commoditized. The barriers to entry have gone down, and now we’re seeing this opportunity with AI, particularly in synthetic bio to create something more driven by software, but at the same time with lots of barriers to entry. So let’s talk a little bit about the funding environment there. What can companies do, particularly synthetic bio companies, to become more attractive, to become mainstream, if you will, for venture funding?

Ursheet Parikh:

So if you look at the Cleantech 1.0 era which Raj alluded to, and the big returns over there accumulated in the public markets to investors. This included companies like Tesla and Phase, and overall, the private investors did not necessarily end up doing as well. Now, a lot of the public investors who got so excited about those gains have been burned really badly in the SPAC boom, where you had a lot of companies, whether they were cleantech or built by bio, go public but then underperform on stock returns. So coming out of this, what investors want to fund is companies that they can evaluate and measure and operate and measure their operations on. And this often for public companies starts with when you are in revenues and when you start showing operating leverage and earnings profits and things like that.

So this is where I would definitely encourage any private company today to fundamentally think about how they’re spending their dollars, and how they execute to demonstrate their differentiation to get better pricing. If you build amazing products that truly meet customers’ needs, you will get better pricing. You will have better margins that can then help you leap ahead.

And this is a shout-out to my colleague, Arvind Gupta, who normally is on stage with me but had a conflict today – he talks about how essentially, when you’re building a synthetic biology company, you really think down of how you’re going down the cost curve. And in the earlier years, where you are pretty high up on the cost curve, you have to find niche markets and applications where you are going to get paid a premium. And people can remember Tesla today as this mainstream company that’s selling a car which is at a lower price than the average American car. Average American cars sell at like $42,000. Tesla has a $40,000 car, but it IPOed on the Roadster. It was able to go at the first billion, and it was a premium product. It was a niche product.

So I would say thinking about amazing products, thinking about the unit economics of the products, getting to revenue quickly, and giving investors very tangible operating metrics by which they can measure the progress of your business. And this applies at seed, A, B, C, D, IPO, and even for public companies. Otherwise, it becomes just easier for investors to stick with the big large companies in an era where it feels a little dangerous to be investing.

Raj Judge:

So we’re out of time. I’m going to give you one last question. I want a quick, rapid-fire answer from it just because I think a lot of us want to hear. What areas do you see in synthetic bio as the prime areas to be looking at in terms of potential growth and investment and the like? And so, I’d love to hear what you think. Is it food? Is it materials, hydrogen, carbon sequestration, CRISPR, we’ve talked about that engineered bio? 

Ursheet Parikh:

All of those and hydrogen, but most specifically, I will highlight things which are set up to be capital-efficient biomanufacturing. And I think fundamentally AI-powered everything in synthetic biology, it will absolutely transform how everything happens. A person can run experiments or can marshal AI to do a thousand things for them simultaneously, right? I think that’s what every scientist and every engineer, every manager needs to think about.

Raj Judge:

Wow. Fantastic. Well, thank you, everyone. Thank you, Ursheet. And I hope you folks had a great time today and learned a little bit of what Ursheet thinks about the market. It’s definitely contrarian to what I saw and what I thought, and only the paranoid will survive. So thank you very much.

Ursheet Parikh:

Thanks, Raj.

Silicon Catalyst – Fireside Chat with Navin Chaddha

Silicon Catalyst recently hosted their spring 2023 Portfolio Company Update, where Mayfield Managing Partner Navin Chaddha shared his insights on the semiconductor industry, company building, generative AI and more in conversation with Dave French. Key takeaways include:

  • In order to win, startups need to first get mind share with their potential customers, then they need to get market share, which will lead to revenue;
  • As venture capitalists, we aim to partner with great people because ideas and markets will come and go, and great people will pivot to find the right opportunity;
  • The plateauing of Moore’s law has led to the need for application-specific architectures and the renaissance of silicon;
  • Silicon is not the only deeptech opportunity – entrepreneurs should also look at innovation in physics, chemistry, biology and other sciences;
  • AI is a real trend but it won’t happen overnight, so founders and investors should be patient.

The full transcript is available below – we’re proud to be partnered with the Silicon Catalyst team to help nurture the semiconductor entrepreneurial ecosystem.


It’s an honor to be at a major Silicon Catalyst event, probably the biggest event of all time for this group, and it’s also an honor to be able to speak with Navin, who’s a legend in our industry, and in other industries as one of the best investors in early stage activity throughout many segments, and so, I’m pleased to be here.

My goal here is to allow Navin to impart the maximum amount of wisdom to this group of highly intelligent people in 31 minutes.


I think it’s going to be the other way. There’s so much wisdom in the room, right? At the end, crowds win, not individuals. Really looking forward to it, and thank you for your kind words.


So we’re going to use a question and answer format. We actually worked a little bit on formulating a few questions that might bring out the most interesting information for the group here. I talked with a bunch of the people here, I consulted with chatGPT, I talked to my wife, my kids, but we came up with about a dozen different questions. I’m going to shorten the list, and then, hopefully, open it up to live questions from the group, if possible.


That would be awesome.


First, if I might ask here, can you recount one of your experiences in the entrepreneurial world that it was most educational, most valuable, or most interesting? Then can you share some of what you learned, and how you got some out of that, and how you’ve brought that to Mayfield to allow Mayfield to make better investment decisions?


Great, great. So for those of you who don’t know me, I have been doing venture capital for 20 years, but before I did that, I was on the bright side of the business called entrepreneurship. So I started my first company in ‘96, right out of grad school at Stanford, and my company was one of the first ones doing video streaming over the internet in software. And it grew like crazy in 18 months.

And the highlight of the journey was Microsoft – it essentially started as a partnership, and one thing led to another, and they said, “Hey, this is a core technology you need to come pitch.” I said, “Okay, but to who?” They said, “To Bill Gates.” I was like, wow.

You always hear about 10X Entrepreneurs. But when I went to this meeting with Bill Gates, I met a 100X entrepreneur. This was in ‘97, and the questions he asked were just amazing, and I keep those things to myself, and try to bring them into our startups.

One thing he asked me was, “What do you think is going to be your market share if we partner with you?” My answer was, “We should be in every Windows powered computer and every Windows server.”

Then he asked me the law of physics, which I failed, and then he asked, “What do you think is the amount of profits a number two player makes in an industry?” I said, “Maybe 30% of the profits.”

He says, “Nope, you’re wrong. The number one player in any industry makes money, number two breaks even, and there’s no number three.”

Then I go to Microsoft, and they’re in the war with Netscape. Fast forward, number one player makes money, there’s no number two, and then when Google Chrome comes, there’s only two players. You go back to Windows, there was Solaris, 100s of forms of Linux, down to two. One is freeware, the other makes money. You go to the mobile ecosystem, Apple makes the profits, Android is number two, there’s nothing else.

I learned the hard way that in order to win, startups need to first get mind share with their potential customers, then they need to get market share, and that will lead to revenue.

So if you have a land grab opportunity, don’t just think about short term revenues. Think about community, think about winning the mind share, and the hearts of your customers.

So I think those were some of the key lessons, but just meeting an 100X entrepreneur, or maybe 1000X, still gives me chills. I never had to pitch to Steve Jobs. I’m pretty sure he used to be like that too.


A remarkable story. It’s something for all of us to learn from. Another question, if we might draw from your vast experience, can you just give us a brief history of Mayfield, and how you’ve progressed through the years, and some of the more exciting times in the firm?


Yeah, absolutely. So this is the third generation of leadership at Mayfield. The firm started in 1969 by a gentleman named Tommy Davis. He actually started at another firm in 1961, Rock Davis, along with Mr. Arthur Rock who funded Intel, but then they split, and Mayfield got formed in 1969. Tommy Davis decided they were going to build a people first firm.

So what exactly does that mean? He wrote a book on how people make products, products don’t make people. He called it a one-man war, that hey, he didn’t come from the technology industry. He came from a legal background, fought in the Vietnam War, and he didn’t know anything about technology, he wanted to learn about technology, so he hung around with the smartest people at Stanford and named the firm Mayfield. Any guesses what Mayfield represents?

Any guesses? Maybe you? Some people think it’s the dairy company. There’s a company, Mayfield, then they thought it’s the Mayfield Bakery. No, it’s not. It’s basically the town of Stanford, before it was called Stanford, was called Mayfield. And then, it transformed, 100 years back or so.

So Tommy Davis essentially learned the business by just driving Dean Terman around. So he used to consult, and just understand what’s happening, and from that day, to today, with a 50 plus year history, the firm believes you need to be in partnership with great people, because ideas, markets will come and go. Look at NVIDIA, one of the most valuable companies in the world, fourth, or fifth-largest market cap. Started as a small company, was a fledgling for years in this ecosystem. Today it has a trillion-dollar market cap because it kept reinventing, kept pivoting.

So if you back great people, their initial idea or market isn’t going to matter, because they’ll pivot to find the right market opportunity. So as long as you’re patient, just partner with great people, who have a sixth sense, and have the tenacity to go through any wall to just make it happen.

So that’s what became the culture, and the ethos of the firm. Don’t get enamored by the tech and the market, because it’s all about execution. Genius is only 1% inspiration, so bet on people who are going to go through any wall – but ethically.

So I think that was the background, and the firm has been through its own ups and downs, and you learn from the mistakes. Learn from the mistakes, but do a lot of right, and if you keep partnering with great people, just good things happen.


Remember that. So here’s Mayfield, been around for 50 years. We’re at Silicon Catalyst event here, so we’re all focused on semiconductors largely.

And I’ve been in the industry, well, for a lot of years, and I remember when venture capitalists in the Bay Area, and everywhere, were highly enthusiastic with almost no exception about investing in semiconductors. That’s not always been true for the past 20 years in particular. I’m really enthusiastic that Mayfield made a commitment to get more focused on semis, with its relationship with Silicon Catalyst.

And one of the questions that has come to mind, and came up in Silicon Catalyst discussions, is what goals do you have in the relationship, the partnership that you’ve announced with Silicon Catalyst, and what do you hope as a firm to achieve?


Yeah, so Mayfield, I think, from the 1970s until around 2005, was one of the most active investors in the semis space. And then, VCs just bailed out, because it was really hard to build semis companies with the dominance of the X86 architecture, and it was just very hard for companies to raise money, get design wins, it just took forever.

And so with the VC fund life of 10 to 12 years, semiconductors became like biotech, and at the same time there was money being made in games, in social, so people ran for the hills. So some of us started re-looking at this area in 2014, 15, and started realizing, and people in the room know this better, that there’s going to be a plateauing of Moore’s law, unless there is some innovation in physics, or quantum physics, because at the end, you’re fighting physics. You can only pack so many transistors.

So we said, “Okay, if that’s the case, what kind of companies can get created? Yes, they’ll be capital intensive, but if the prize is massive, you should be funding them.”

So we coined, this term, the renaissance of silicon and we predicted that with the plateauing of Moore’s law, there’ll be a need for application-specific architectures. There’ll be a need for low power devices. With the prevalence of 5G, there’ll be new silicon coming out. Power and cooling will become a huge issue. All these trends were just emerging, and we realized if the Moore’s law is plateauing, you can only do so much in software.

Then we met with Pete and Tarun, and we agreed that aim number one is grow the semis entrepreneurial ecosystem. How do you foster more entrepreneurs to work on bringing silicon back to Silicon Valley? Right?

Number two, if Mayfield can help advise Silicon Catalyst companies, help them during the selection process, and of course in the right ones where it matches our thesis, fund them, then you’re helping Silicon Catalyst, and the broader ecosystem.

And then, being part of this rich community, hopefully, we won’t make the mistakes they’ve already seen. So we’ll make new mistakes, and at the end, in venture capital, it’s all about making that 100X, 1000X return, but you don’t need to reinvent the wheel, and make the same mistake.

So that’s what Mayfield gets in return. We bring a lot, but in return, our hope is Silicon Catalyst will not only advise our companies, but also keep Mayfield out of trouble of backing our own things, right? Because even though we think we have a thesis, that means nothing compared to industry experience. It’s just amazing to be part of this collective.


Wow. I, for one, am glad that you’ve joined the Silicon Catalyst community. One of the questions that many people have posed to me, and requested that I posed to you, is that you recently raised a new fund. Congratulations, again, another billion dollars, or whatever it was. One of the-


A little bit less. Somebody said, “You don’t want to be a unicorn VC, that’s why you did it.” I said, “No.” They said, “Great marketing.” No, we don’t need it. We could even raise two, three billion if we had wanted to. Companies should be unicorns, and often times even they shouldn’t. They’re imaginary figures, they’re not real. You need to build real companies.


There you go. Real companies are where the difference is made. And the question that comes up is, out of that billion dollars, do you anticipate, or have discussions with the LPs that you brought into that fund, focused at all on semiconductors? Is there a positive attitude? Is there the governmental emphasis? I hear politicians can even say semiconductors, and silicone, and all these kinds of things, and do you think that semiconductors are going to be a focus for the new fund?


Yeah, I think it’s a big focus for us. And here’s the thing. Having been in the business for so long, both as Mayfield, and me, there’s a lot of trust that we know how to spot great entrepreneurs chasing new markets or existing markets, and we have the capability to turn small boxes of money into bigger boxes of money.

Now, the thing is, the boxes itself at input have gotten bigger, but when you see multiple huge companies in the space like NVIDIA and AMD, you can dream that there can be five or 10 billion dollar companies that VCs can back in this ecosystem.

So Mayfield’s aim is we want to be one of the biggest VCs, who focuses on inception stage, and has the most dollars to work in deep tech. So both inception, and deep tech is like 50% of our focus, and deep tech doesn’t just need to be silicon. It could be systems, which are based on silicon. It could be MEMS based technologies. Why stop there?

Biology, synthetic biology is also deep tech. So what physics does, you can do it in chemistry for batteries. It’s a big unsolved problem for EVs, right? Look at the cost. Why won’t you want your car to run for 1000 miles? Why wouldn’t you want your phone to not overheat? So to me, I would push the people in the audience to think beyond just silicon, and say, can we go back to our roots, and look at innovation in sciences, look at innovation in physics, chemistry, biology, and bring the knowledge you guys have done in the silicon industry, and do it elsewhere.

And I think silicon, and silicon based systems, I think, will be 20 to 25% of our focus, especially with trends like IoT, AI, networking connectivity, and optical switching. It’s not in the data centers. You can’t do these things on X86. You guys know it better.

And so, I think there’s a lot of innovation to do, but having been in the business for so long, the key issue still is, who’s the buyer of the technology, and what do you do with the capital intensity of these companies?

So you need a follow on ecosystem, and you need people in the room who are at corporates to say, “Hey, let’s foster innovation so all of us win.” And TSMC is a good example. They are helping companies of all sizes. Clearly, they have to give preference to the trillion-dollar companies, but our companies hopefully can be one 10th of them. That’s 10 billion.


But you heard them talk, they still love startups at TSMC, which is great to hear.


Yeah, we love them. They’re great.


Yeah. So I have to bring this up, generative AI?


Biggest topic.


Everybody’s talking about this topic. I’ve heard your thoughts about some of the specific investments in that area. Do you think that startups in semiconductors, or around semiconductors, have a chance of making a great return in that general domain, even in the face of the hyperscale companies doing what they’re doing, and the kind of money that they’re spending?


So I think, first of all I would say, not just generative AI, but AI is a real trend. Basically, we lived through the client server era, then the PC desktop era came, then came the web era with browsers, then came the mobile era, and the cloud era, so I think AI is a real thing. And either we are going to fight it, or we going to use it, and say at the end it’s a tool, it’s a technology, so humans should control it.

So there’s going to be a lot of innovation, and there’s going to be a lot of opportunities. Now, whether there are opportunities in silicon, whether there are opportunities in middleware, whether there are opportunities in systems, whether there are opportunities in applications etc is all still to be played out. I think applications are a white space. So could you have applications which don’t displace humans, but augment them.

Let’s look at security, let’s look at coding, let’s look at testing. There’s a shortage of talent in DevOps, in SecOps, so if you have 10 racks, maybe five you can fill, but five can be AI as your teammates. Now, you may not need five, maybe just equal into two. So at the apps layer we see clear, clear opportunity. Similarly, we see opportunity in middleware and tools to enable the mass market outside of cloud providers. Now, comes the hard part, which is like, what do you do at the silicon layer, right? Because half the buying probably is going to happen by three, four companies, the hyperscalers – and can they really depend upon startups, or will they go just work with AMD and NVIDIA?

So I think edge-based AI, where markets are fragmented, where Xilinx, and other people used to play, could be an interesting market. I think inference is still unsolved, but the big players are there. The question I’m trying to figure out is what is the end market? Because if you have concentrated buyers, like the cloud providers, they have too much power. They have proprietary software. If they port it into a startup, first it takes 18, 24 months, and then, the startup gets acquired by a competitor. You wasted all the time. They learn.

So you have to go find fragmented markets where just, because four people in the world can do it, can rest of the world do it? And I don’t think if AI is going to be like CPUs, that’s where the market is betting with NVIDIA. If it’s going to be everywhere, startups, and entrepreneurs have to go find markets where it’s not just four, or five concentrated buyers, and come up with a solution which optimizes your design, optimizes your solution to that need, and build channels which somebody may not be interested in doing.

So you can’t just say you’re going to go sell to Google Cloud, or Azure Cloud. They may not want to work with you. They’re happy with NVIDIA, maybe with the AMD, or they’re already building their stuff. And I think in AI, one of the areas is this connectivity between all these AI servers, which these people don’t do is an area. Edge is another area on the silicon side, I would say, so let’s keep an open mind, but I think going, and fighting, and saying, “I’ll take down somebody who already has 95% market share,” is like a fool’s errand. So go find new markets, new wedges, and remember you only need 1% of the market. Don’t go play in somebody else’s territory. Startups don’t do that.


Keep that in mind, otherwise you’re on a suicide mission.

Shifting gears a little bit, before I try to open it up to some live questions here. A question that I’ve always asked people in the professional money management space, as much as anything else is. We’ve got a pragmatic situation. We’ve got, I don’t know, 30, 40 entrepreneurs here that will make 300, 400, 500 presentations to venture capitalists over the course of the next six to 12 months, probably.

Are there any particular words of wisdom you could impart to this community about what they ought to do, or ought not to do, in order to, number one, make sure they don’t turn off potential investors in their company, or more, to bring them in, to lure them in to their story.


So I think every VC firm is different, and it’s hard to say what other people look at, but I can say some of the things Mayfield looks at, but some things I’m pretty sure every VC will look at.

So let’s go through what the industry will look at. The first thing everybody’s going to look at is, what market are you going after, and how big is it, right? It’s just a common thing people will ask. Second is people are trying to figure out, it’s not about the technology, and most of the people just get lost in that area, is to figure out, is your product really a painkiller, or is it a vitamin? Because people don’t have time, they’re going through a down economy, CapEx budgets are being slashed, IT budgets are being slashed, and you are number five in the priority. They don’t even show up.

You better be number one. Somebody has a headache, don’t tell them, right? “Hey, take vitamin C.” They’re interested in Advil, so sell something which is an Advil to them – figure out the need of the customer. As far as Mayfield is concerned, we look at those things, but I think the most important thing is be authentic, be yourself. VCs. You’re pitching to 35, 40 VCs. I see 2000, 3000 pitches a year.

So 3000 pitches a year, and you are looking for that as a firm. That’s what we do is, you have to keep looking, looking, looking, whether it’s Zoom, whether it’s PPTs, and other things, but you look for authentic entrepreneurs.

And don’t be coin-operated in the meetings. Try to be patient. Try to understand what this VC is really getting at. Don’t interrupt them, because answer the question they’re trying to ask. Don’t answer stuff that is not even important.

So I think those are some of the things I would say, yes, have your notes on market. And most VCs, do not build chips, we are not from this industry. We don’t know how to write this stuff, so don’t spend time there. Get them on the same page.

And the most important advice, I kept it to the end, is, guys, since we see so many pitches, you better get your message across in 30 seconds. So I always tell entrepreneurs, when you open the slide, be very clear. Why do you have the right to exist?

And then, after that, it’s your elevator pitch when you are on TV, right? It’s just the headline stuff – “I’m going to be X of Y.” Right? Because nobody has time to sit through 30 minutes. That’s why VCs will take out their phones, they’ll start taking notes, but it’s better to just get to the punchline.


Thank you very much for that, and I thank you on behalf of the people here.

We have a little bit of time left so I’d like to open it up to live questions in the room.


There’s one there.

Audience member:

Yeah. So you focused on Mayfield, focusing on humans, so what is the criteria you use to figure out if the founder is good or not?


Yeah, I think that’s a secret, right? If I say that, then people will fool us, right? Okay, man, that’s the joke, so it’s very simple, right?

We are looking for authentic entrepreneurs, and we are going to spend enough time, not one hour meeting if you’re interested, 10 hours, 20 hours, till the entrepreneur gets tired, and we are really going to get to the bottom of, are these people thinking about themself, or the company? Entrepreneurs who use I, versus we, is a signal, and I hope you understand what I’m saying, right? So they’re company builders. They’re not like individual builders.

Second, they have just high EQ. Everybody has IQ. The EQ, the emotional quotient, is very, very high on people who build big companies.

Third, they’re very secure in their skin. They don’t get defensive, and they listen to the question being asked, and if they’re secure in their skin, they demonstrate vulnerability.

And then, they’re just amazing, amazing, amazing team players. Because to build a company, it’s not about your intelligence, it’s not about your individual hard work, it’s not about any of those things. It’s about leading teams, it’s about being authentic with investors, with your customers, and it’s not about you, it’s about the company. Support the company first, and believe me, it’s very hard to fool a VC who’s focused on that, right? We have psychology degrees now.

And by the way, these skillsets, people who are at GE, who are at many of the big companies here, you can’t grow in an organization then you are an IC. To become a leader of a company is the same.


That’s a great answer. We have another question over here, please.

Audience member:

I’m curious about your thoughts on the advantages of having design and manufacturing of semiconductors in close proximity, and the implications, if any, due to the fact that much manufacturing capacity in the United States has moved overseas, the ability therefore to build world-class semiconductor companies here in the US now?


Yeah, so this is more economic, so where I think the proximity to is more important, at least in my opinion, is to your customers. So the design, and the product management needs to be very close to where your customers are.

So if your customers are in APAC as an example, and you are sitting, and designing a product, not engineering design, defining the spec, what is called an MRD, or a PRD in the old days, sitting in the middle of US somewhere, be close to your customer.

So if you are close to your customer, now, comes the problem. The customer has a supply chain in country unnamed, X, and you say, “I will build in the US.” Okay? So you just build your chip in the US, but their whole supply chain is sitting in some other place in Asia Pacific, or in Europe, or something. So I think you need to be close to the customer, and the customer supply chain.

Now, because of shortsightedness in the past, cost reasons, this reason, that reason, supply chains have moved. They have become global, and it’s going to be very hard to just change it overnight. So what it’ll come down to is not startups. I think it depends upon big companies. They need to move first, right? Startups have so many risks, for them to, basically, go take that risk now, will be very hard, because they don’t even have volume.

So I think it’s dependent upon many of the companies and the partners in the room to take the leap. And by the way, they are the ones who are going to get government subsidies, not our small startups, basically, they have the volume. So they need to lead the path to bringing manufacturing, and the supply chain here.


Another question over here on the right-hand side.

Audience member:

Yes. Okay, thanks very much, great talks. My question is regarding more on the recent economic trend, and I think that, in general, VC investment are affected, or in the past few months, and I just wonder if you can comment on the probability deep tech and the semiconductor will behave differently? So I just wonder if you can comment on what you see in the past six months, and what you can expect for the next six months?


Yeah, absolutely. Right. So I think if we look at the data, the amount of funding that happened a decade back before the correction, was one 10th, there was a time in 2011, 2012, startups used to raise 40 billion. 2021, that number went to 400 billion, then 2022, it came down to 200 billion, and then, it might come down again, right?

Here is the thing. I went in and looked at the data, and this is not seen by most people, actually, the number of new companies getting funded wasn’t changing. Its existing companies were raising 10X the capital, because all the Wall Street money came to Main Street, and they don’t go fund the companies which were presenting here. They focus on mid to late stage companies, and because of the inflation, the company which used to raise 5 million at seed, or 2 million at seed, they said, “Instead of seeds, will raise mango seeds, they’re bigger.”

Then they said, “Oh, mango seeds are not big enough. Forget about seeds, we’ll raise watermelons, not watermelon seeds.” They became even bigger. And so, number of companies, new ideas was the same. They just raised more money at inception, and then, they is 10X the money.

So I think, actually, jokes apart, this is a great time to be an entrepreneur, And the main reason is big companies have to focus on their business. They can’t just go and work on science fiction projects, which will make money nine, 10 years from now. Talent is available. There’s less money by VCs into the startup ecosystem, so if you have a great idea, along with a great team, your chances of success are actually higher, and for the next three, four years, if you are in product building mode, it’s great, because big companies budgets are slashed everywhere, besides some segments which are growing, but when you come out with your product, they’ll be again buying.

So it’s a perfect time, and great companies, most of the time, are not created in bull markets. They’re created in times of economic turbulence.

So I would say, right, basically, it’s time to get your parachute together, and jump from wherever you want to, and have the right VC partner who will help you.

Audience member:

So jump without a parachute?


No, that I won’t advise that you can, I’ll get sued. That’d be bad advice.


That is a great way to conclude. There are many of us who would love to sit here, and absorb your ideas for as long as we possibly could, but I know that you have a hard stop. We really, really appreciate the time, and the wisdom that you’ve shared with us here today, and we’ll let you get off to your next assignment.


No, I think it’s a real pleasure to be here, and thank you Pete, Tarun, and thanks, Dave, for making this happen. Real pleasure. Thank you.

10 questions early-stage founders should be asking investors

When I wrote this post in August 2021, we were at the peak of exuberance in VC investing and startup valuations. I bemoaned the decline in early-stage investing and feared that innovation would suffer as a result of it.

The VC industry is turning back to its roots of investing at the early stage, although activity is still dramatically lower, with Q1 US 2023 data showing a 53% decrease in deal value and a 52% decrease in deal count at the seed stage year over year. Similarly, we’re seeing a 60% decline in deal value and a 47% decrease in deal count at the early stage of investing year over year. While I welcome this focus back to early-stage investing, I am sorry that it has come at the cost of hundreds of thousands of layoffs and continued challenges for startups.

However, I am sounding another note of caution today. As a pure inception-stage firm that has partnered with founders for more than five decades and guided over 225 companies to successful exits (including 120 IPOs and over 225 acquisitions), I know that early-stage investing is a craft that is honed over time, not a hobby or tourist destination.

Similar to a master chef or carpenter, the ability to work closely with founders at the fragile stage of company formation until they bake the perfect soufflé or build a bespoke coffee table takes time, skill and patience.

It may not be the right mode for every investor and is best pursued by those who believe that company building is a marathon, not a sprint. In an era where everyone’s dollars are green (albeit with fewer floating around today), I believe it is important to help founders with ways to evaluate investors before committing to a partnership.

Let me share some specific examples of what it means to be a “roll-up-your-sleeves” inception-stage investor:

  • A semiconductor company with a breakthrough chip for cooling devices is evaluating where to establish its first beachhead. Over a multiday whiteboard session, we work with the founders to go beyond the obvious and attractive large market of smartphones to settle on the smaller market of surface devices as their initial entry point. This is informed by our experience in working with other inception-stage chip companies, as we know how long it takes to go from design to tape-out, and then to scale production to fulfill the needs of hundreds of millions of customers.
  • A consumer fashion marketplace has ignited the love of its community of seller stylists, but its e-commerce infrastructure is breaking down. Its CEO has just raised a round of financing based on growth projections but now tells the board that they need to slow down to strengthen the platform. In a growth-at-all-costs environment, the inception-stage investor, a former three-time serial entrepreneur, knows that the journey often takes a decade or more for a successful outcome. Consequently, we are willing to support the CEO in a slower growth plan, knowing it is so that they can build a sustainable marketplace platform.
  • An enterprise software company needs to go beyond its known networks to rapidly attract top-tier entry-level talent to scale its business. We design a program for college campuses where we partner with the career centers to host many custom immersion days, thereby attracting hundreds of qualified candidates for consideration.
  • An inception-stage cloud company needs help refining its value proposition and defining its insertion point to get to product-market fit. We arrange more than 50 conversations with the precise C-level buyer persona to help with this process so that when the company debuts, it does so with early customers and a go-to-market motion that accelerates mainstream adoption.

These are just a few examples of playing strategic sounding board, patient investor and value-added partner, but there are hundreds more from our experience. So when a founder is evaluating an investor for an inception round, here are some non-obvious considerations:

  • Has the team at the VC firm ever founded a company and nurtured it to a successful exit as entrepreneurs?
  • Have they ever invested through downturns?
  • How many investments does each investor make per year? Does every company count in their model?
  • Can the firm provide you a list of inception-stage founder references?
  • Does the firm have a few breakout companies with similar characteristics at the inception stage of investment and sector to yours?
  • How do they specifically add value as board members along with their portfolio services teams in talent, marketing and business development?
  • Can their founders tell you if they work solo or as a team with everyone available to help you?
  • How do they act when things are not going well? (Talk to those founders especially.)
  • Do they take a long-term view and are they patient investors? Do they see company-building as running a marathon, not a sprint?
  • Above all, try to intuitively assess: Will they watch your back, or are they going to be evaluating you constantly?

While it might seem daunting for founders to question potential investors in today’s climate, remember that you need to build a mutual zone of trust for the long journey.

Equipped with this knowledge, founders need to also trust their instincts when picking their inception-stage investor, as chemistry plays a key role in the founder-investor partnership. With that, we invite founders to lean in so we can build a bright future together.

Originally published on TechCrunch