Category Archives: Insights

Running Through Walls: NFL to VC

Ryan Nece is a former NFL player, Super Bowl winner, and now a venture capitalist at Next Play Capital. He joins Venrock partner Brian Ascher to chat about the transition from the field to the boardroom, including why so many professional athletes take an interest in venture capital and what elite athletes and successful entrepreneurs have in common. Nece shares the highs and lows of having a famous parent, football Hall of Famer Ronnie Lott, and his gratitude for the opportunities made possible by his upbringing. No stranger to adversity, he also discusses a challenging time battling injuries that almost ruined his career before it started. 

Venrock Running Through Walls · NFL to VC
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Building Commercial Open Source Software: Part 3 — Distribution & GTM

Building a Commercial Open Source Company

In our time investing and supporting open-source companies, we’ve learned several lessons about project & community growth, balancing roadmap and priorities, go-to-market strategy, considering various deployment models, and more.

In the spirit of open source, we wanted to share these learnings, organized into a series of posts that we’ll be publishing every week — enjoy!

PART 3: Sequence your distribution & GTM strategy in layers

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1. Vibrant communities make for the best lead generation:
The open-source popularity of a project can become a significant factor in driving far more efficiency and virality in your go-to-market motion. The user is already a “customer” before they even pay for it. As the initial adoption of the project comes from developers organically downloading and using the software, you can often bypass both the marketing pitch and the proof-of-concept stage of the sales cycle.

2. Start bottoms up, developers first: Focus on product-led growth by building love and conviction at the individual developer level. Make it easy to sign up, deploy, and show value. Leverage developer referrals, community engagement, content marketing, and build the product-led growth mentality into each function of your company. Nailing the developer experience can lead to growth curves that look much more like consumer businesses than enterprise, and lead to much larger deals later on.

3. Nail bottoms up before enterprise selling: You can focus on product-led growth (bottoms up) or account-based marketing (top-down), but not both at the same time. Start with product-led growth to build an experience that developers love. Once you’ve reached some critical mass with a flywheel of developer acquisition, begin to introduce account-based marketing, starting with the expansion of existing customers to learn the enterprise sales motion before going after new accounts.

4. Developer first doesn’t mean developer-only: While nailing the developer-first experience is key to driving strong customer growth, it’s often not sufficient when trying to scale the project into larger-scale deployments. Transforming from a proof of concept to multiple large scale deployments across the customer’s organization requires a different set of decision-makers and requirements (i.e. security, policies, control, SLAs). Be sure to understand how the needs of the organization may differ from the needs of the developer when planning how to expand deal sizes and go after larger customers.

5. Build your sales funnel based on project commitment: Customers will come in three coarse flavors: (1) already deployed OSS project internally (2) starting to deploy OSS project internally, (3) decided to adopt OSS project. Design the sales motion tailored to the customer journey in order to focus on solving the right problems and challenges.

6. Target the ‘right’ developer: It’s critical to know who you are solving for and what you are solving for them. Going after the wrong developer persona can make a critical difference in whether the developer community understands and embraces your solutions, or not. Is this a solution for DevOps or data engineering? Technical business users or Data Scientists? An example data infrastructure project could be seen as (a) making it easier for DevOps to manage, (b) shifting the power from DevOps to engineering, c) helping data engineering leverage better code patterns, and (d) making it more secure for SecOps to manage data access. Obviously, all (4) have very different problems, with different values associated to them, but are all value props of the same solution. Focusing on the right persona, with the most painful problem, where you can continually layer value over time, is critical to building wider community love and commercial adoption.

7. Sell impact, not solutions: Help understand the total cost of ownership (TCO) of your solution vs an existing, closed, or in-house system — this matters and is rarely done well by the customer when making buy/build decisions. Understanding the value and ROI your service delivers, both hard and soft, allows you to sell on impact to the business, and not on a technical solution. Are you saving developer headcount? Increasing developer productivity? Reducing infrastructure costs? Cost-take out of a more expensive or legacy system? Being clear on the cost savings and velocity benefits of your solution drives up customer contract values.


Building Commercial Open Source Software: Part 3 — Distribution & GTM was originally published on Medium.

Source: https://ethanjb.medium.com/

Running Through Walls: When Demand Spikes

Venrock partner Bob Kocher speaks with Hill Ferguson, CEO of Doctor On Demand, about how the company managed a huge spike in demand for virtual care as COVID-19 spread throughout the country beginning in March 2020. He shares how Doctor On Demand implemented a real-time assessment for higher-risk patients to handle growing wait times, and how they partnered with Medicare to cover virtual care visits for seniors for the first time. Kocher and Ferguson discuss how social injustice, economic hardship, and losing loved ones to COVID-19 are contributing to the increased demand in behavioral health services offered by Doctor on Demand. Ferguson also highlights the importance of balance and self-care, shares his expectations for flu season, and unpacks Doctor On Demand’s plan to make primary care more accessible through virtual visits. 

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Running Through Walls: Risky Business

Jennifer Bisceglie, CEO and founder of Interos, joins Venrock partner Nick Beim to discuss how Interos mitigates the challenges of third party risk management, particularly during the pandemic, by providing customers full visibility of their extended supply chain. Bisceglie describes how Interos continuously builds “family trees” of companies and scans for risk factors so customers can gain visibility into their supply chains and understand the vulnerabilities that can interrupt operations. She shares her proudest moments at Interos so far, the biggest challenge that female entrepreneurs face, and provides advice to women who are looking to start a business.

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Op-Ed: The COVID-19 vaccines are coming. Here’s how they should be rolled out

This article first appeared on latimes.com. It is co-authored with Dana Goldman.

Sometime in the next few months we are likely to enter the era of COVID-19 vaccines. With billions of dollars poured into the multiagency federal effort Operation Warp Speed and positive signs coming from clinical trials, the odds seem high that one or more safe and relatively effective vaccines will be ready soon.

But getting ready and getting people immunized are two different things. Well before Operation Warp Speed delivers products en masse, we need to be prepared to distribute them effectively. Initially, we will have to prioritize some highest risk Americans over others, and — perhaps most challenging — we will have to persuade millions of reluctant or complacent Americans to get their shots.

To crush the virus, we need a moonshot-like goal: 150 million Americans vaccinated by Sept. 1, before next year’s school year and flu season. Only by achieving this level of immunization can we confidently achieve a sense of normalcy again.

How do we achieve that goal?

First, make any FDA-authorized vaccine completely free of charge. Our research shows cost will be a barrier for many Americans. Not only should the vaccines themselves be covered, so should the administration fees for pharmacies and distributors. The payment system must be simple so that red tape doesn’t delay delivery. The government is already buying doses through Operation Warp Speed, but it should formalize that process to guarantee all inoculations are free regardless of location or insurance.

Then set priorities for early distribution and get the initial target groups ready to line up for shots. When the vaccines are first approved, many more people will want them than can be accommodated. Healthcare workers will probably be the first priority. Next will be people at higher risk of serious illness or death, including the elderly, those living in nursing homes and jails, and those with suppressed immune systems. This is also the time to create a national registry that keeps track of who has been vaccinated, enabling long-term monitoring of the vaccine’s safety and efficacy.

Lay the pavement for rapid deployment of vaccines to the rest of us. Retail pharmacies and local healthcare providers will need help preparing to take on the massive task ahead, and they should not be alone on the front lines. Employers should incentivize their workers to get their shots at workplaces. Vaccinations should be required for all school employees and university students to address super spreading. Moreover, as soon as the first vaccine approaches availability, Operation Warp Speed should fund research on its safety and effectiveness in children. It is hard to imagine interventions like physical distancing and masks alone preventing all future superspreading events at schools.

Lastly, think big. Plan for a level of throughput that has never been achieved by our health system, which is usually characterized by fixed capacity, long waiting times and bricks-and-mortar facilities.

Public health agencies must be proactive and get creative. Vaccinators should show up wherever a crowd gathers, such as bars, nightclubs, parks and even the South Lawn of the White House. (At bars, instead of one shot, how about two?) Create a mobile registration system that eliminates the need for clipboards and insurance cards. This may be the way that the Apple and Google COVID-19 partnership achieves its potential. Launch free training programs to create new workers capable of administering vaccinations and pay them per vaccine delivered. Create a network of thousands of local distribution centers for vaccinators to pick up doses. This could be a great use of the 31,322 post offices in the U.S. simply by adding refrigerators and an inventory control system to track vaccine doses.

Finally, governments at all levels should coordinate with pharmaceutical companies, doctors and hospitals on a vaccination awareness campaign of a scale not seen since the advent of polio immunization. Unlike that tranquil time when trust in government and the medical establishment was high, the public today is rife with suspicion. For many millions, the delivery of vaccines in record time is a sign that something must be wrong or dubious.

The name Operation Warp Speed should be retired as soon as vaccines are approved and something more encouraging put in its place.

Behaviorists tell us that negative motivations don’t work as well as positive ones. “Get a shot, it’s your responsibility” has less appeal than “Everybody is getting immunized, and you should too.” When coupled with rewards for participation — maybe entry into a lottery after being added to the vaccine registry — the trend line toward herd immunity should move rapidly in the right direction.

The oncoming vaccines give us a chance to return to normalcy. The scientists did their job; now it is time for the rest of us to finish it.

Source: http://bobkocher.org

Venrock Expands Healthcare Team with Industry Experts

All aspects of company building are hard: not just the standard tasks like product development, but also the non-consensus thinking and the constant adjustments required to build truly disruptive, substantial, and sustainable businesses. Great entrepreneurs are learning machines – constantly seeking out wisdom and experienced counsel to help them navigate the knife’s edge journey they have undertaken. For over 50 years, Venrock has been fortunate to partner with amazing founders and CEOs, both to build their businesses as well as eventually connect them with the next generation of visionaries. 

From this broad pool of entrepreneurs and industry experts, a handful have been of such extraordinary help and become such close colleagues that we decided to formalize exclusive advisory relationships with them. Additions to this group include:

  • Mathai Mammen, global head of research and development at Janssen Pharmaceutical Companies at Johnson & Johnson. Previously, Mathai was an SVP at Merck and co-founder and SVP of research and development at Theravance;
  • Todd Park, co-founder and executive chairman of Devoted Health.  Previously, Todd was CTO of the United States (2012 – 2014); co-founder of Castlight Health; and co-founder and former president of Athenahealth;
  • Kole Roybal, assistant professor of microbiology and immunology at UCSF. He was a founding scientist at Cell Design Labs (acquired by Gilead in 2017) and is now co-founder of Arsenal Biosciences.
  • John Stuelpnagel, chairman of the board of directors of 10X Genomics, Inscripta and Element Biosciences. Previously, John was chairman of the board of Ariosa Diagnostics (2014 acquisition by Roche) and co-founder and initial CEO of Illumina.

We look forward to working in partnership with these esteemed advisors to build enduring companies in healthcare. 

Building Commercial Open Source Software: Part 2— Roadmap & Developer Adoption

Building a Commercial Open Source Company

In our time investing and supporting open source companies, we’ve learned several lessons about project & community growth, balancing roadmap and priorities, go-to-market strategy, considering various deployment models, and more.

In the spirit of open source, we wanted to share these learnings, organized into a series of posts that we’ll be publishing every week — enjoy!

1. Solve for the homegrown gap

When developers struggle with deploying an open-source project into their complex internal environments or infrastructures, they build homegrown solutions instead. Solving for key areas turns developer engagement into commercial customers. This means it needs to be as easy and seamless as possible to set up and deploy in order to start demonstrating value. Whether it’s providing Kubernetes operators, specific integrations, CLIs, or UIs, make it dead easy to deploy.

2. Offer an enterprise-ready package

Open source is designed for the community, by the community, and by definition wasn’t designed to work out of the box in the enterprise. Comprehensive testing, a certification program, performance guarantees, consistency & reliability, cloud-native, and key integrations are all substantial value propositions on top of an open core.

3. Layer value on top of the open core

Focus on ways to magnify the value of the open core within the customer’s organization; make it easier to deploy, operate, manage, and scale. Adding capabilities such as rich UIs, analytics, security & policies, management planes, logging/observability, integrations, and more make it easier to work within increasingly complex customer environments. For example, Elastic built a number of products on top of their core that made it easier to deploy and manage such as Shield (security), Marvel (monitoring), Watcher (alerting), native graph, and ML packages.

4. Narrow focus until you become ‘the’ company:

Focus narrowly on making it easy and obvious for every company in the world to be on your open core, and use it to grow both the community and customer love to become the [open source project] company. Avoid splitting focus until you’ve generated enough market adoption (i.e. $25M in ARR) to declare yourself the winner. Databricks is the Spark company, Astronomer is the Airflow company, Confluent is the Kafka company, by focusing on developing, growing, and scaling the open core.

5. Go horizontal over vertical

Focus on modular, horizontal capabilities that apply to all engineering organizations, of all sizes, that make the open core and enterprise solution more robust, manageable, performant, and scalable. Horizontal would include such capabilities mentioned earlier such as analytics, logging/observability, management tools, and automation, but also enabling new capabilities that amplify the value of the core. This might include improved capabilities for data ingress/egress, replacing existing infrastructure components for tighter integration, or moving up/down the stack. Vertical capabilities are focused on specific customer segments or markets, such as offering a ‘financial services package’ or specific offerings designed for large enterprises. The illustration of this has been most recently evident in diverging strategies of Puppet vs Chef and led to Chef’s low revenue multiple acquisition.

6. Optimize for developer usage over revenue

In the early commercial days, usage counts more than revenue. You are looking at downloads, stars/fork ratio, contributor velocity on the open source project, and beginning to see reference customers adopting your project on the commercial side. Developer engagement is key to building customer love, deep adoption, and lock-in. These lead to eventual expansions, referrals, customer champions, and all the goodness.

7. Without telemetry, you’re flying blind

Without understanding how the project is being used, the number of deployments/developers/organizations, service utilization, and adoption curves, it’s difficult to prioritize fixes or features. To better observe, manage, and debug before they become major issues, implementing lightweight telemetry can offer continuous, unfiltered insight into the developer’s experience. Two key projects, OpenCensus and OpenTracing have merged to form OpenTelemetry, enabling metrics, and distributed traces that can easily be integrated into your project.


Building Commercial Open Source Software: Part 2— Roadmap & Developer Adoption was originally published on Medium

Source: https://ethanjb.medium.com/

Running Through Walls: M&A from the Heart

Venrock partner Camille Samuels speaks with Corvidia co-founders Ram Aiyar and Michael Davidson about Corvidia’s recent acquisition by Novo Nordisk, just four years after its founding. They discuss how inflammation contributes to cardiovascular disease – the number one killer in the United States – and how their drug Ziltivekimab “Zilti” is proving to be a successful therapy. Aiyar and Davidson share their experiences and advice for other companies exploring a sale, including always being ready for Plan B (or C), maintaining positive relationships, and not rushing any deals. They also discuss why the cardiovascular space is becoming increasingly appealing to entrepreneurs and investors when it was previously avoided. 

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State of COVID-19 in America

The following is a transcript of the “State of COVID-19 in America” session held during a Venrock virtual conference featuring Amy Abernethy, Principal Deputy Commissioner of Food and Drugs at the U.S. FDA and Andy Slavitt, former Acting Administrator of the Centers for Medicare and Medicaid Services, moderated by Bob Kocher, Partner at Venrock.

Bob Kocher: [00:10] I’m so excited to have two people who are really at the heart of our responses in America to COVID-19 to get a up to the minute view of what’s going on and how we’re thinking of responding. We have Andy Slavitt and Amy Abernathy. Amy at the FDA and Andy everywhere else. I want to ask both of you, I guess, to kick off from where you sit. Where are we now in this pandemic? What’s the current state, as you look at America? Andy, I’ll start with you.

Andy Slavitt: [01:02] Hi everybody. Thanks for having me. I think part of our current state of affairs is we, in the U.S., have led a relatively privileged existence in that we have not had large scale pandemics coming to our shores like this, and we’ve, I think we normally expect that based on our wealth, our statuses and how the nation, our innovation, our technology, these things don’t happen to us. And the reality is that they do, and sometimes our technological prowess and our wealth and all of that can’t keep it from happening, what happens in the rest of the world. But I think in a greater context, if we stepped up a little bit higher, we would see, this is a virus that is, while I think very upsetting and confusing to all of us, in a scheme of viruses, this is manageable. Not easy, but manageable.

Andy Slavitt: [02:06] The continent of Africa has 1.3 billion people and about 35,000 deaths. It’s actually not even a particularly high-tech answer that we need to manage it. It’s actually some of the softer stuff that we all took in school and to get A’s in so we can, we can study for our harder classes, sociology and psychology. It’s a little bit of a governance, it’s a little bit of collaboration. Hong Kong shares a border with China, as we all know, and has the most travel with China and with Wuhan and people put on masks quite early and they minimized the death toll. Now I’m not saying it’s all just about masks, but my point is that when left to our own devices we’ve been at a bit of a loss.

Andy Slavitt: [03:00] And whether that’s been in part government and leadership, whether that’s been in part how we conduct our own debate around the importance of our personal individual freedoms versus our collective responsibility, those things are within our grasp until such time as Amy and team decide that hard science that’s going to replace the soft science, but we need to be able to count on the soft science, or we’re going to continue to suffer disproportionally as we’ve been suffering. And that’s hard, it takes leadership, it takes self-examination, and it takes a certain amount of empathy and compassion that we have not really been able to show. Frequently people will say to me, something to the effect of, ‘Hey, I don’t know anybody who’s died from COVID-19’. And, my response is usually something to the effect of that’s because we no longer know the people who grow our food.

Andy Slavitt: [04:01] We don’t know the people that drive it to the distribution center. We may know them on a first name basis, but we don’t really know the people who work in our grocery stores and their families. We certainly very likely don’t know the people in our jail and in homeless encampments and so forth. And so the sociological effects are even more complex because many, many Americans are feeling safer and more anxious to get back to life. Understandably. And others are still suffering in great number. So, we can talk in more detail, but where we sit in my mind is that a place where we have the opportunity to do a much, much better job to reduce outbreaks. We know that the things to do at this point, we understand that bars are not good things. We understand dormitories are probably not good.

Andy Slavitt: [04:50] We understand that community spread happens. And even goes into, it’s hard to protect older folks when there’s a lot of community spread. So we’ve got to do what we can to keep it down while we have the next year’s outlook, which I think Amy will probably talk about. Which is science will continue to get there for us, but, we continually, magically think that it went to the East it’s not going to come to the South, and it went to the South and it’s not going to come to the North. Well, that’s not how the virus behaves. And I think we all know that. We just have to cognitively react in a way in which protects one another, and it’s not clear yet, that we’ve got the wherewithal to do that.

Bob Kocher: [05:38] Amy, I’d love for you to riff on that and maybe help us know if the soft sciences are going to save us or what’s coming on the hard science side too.

Amy Abernethy: [05:50] Well, it’s interesting. I was going to start with the soft sciences. So I like Andy, see, this softer side has to be really important here. We’re still in the middle of a multi-pronged emergency and we call it a public health emergency, but it’s an emergency that is addressing every part of our lives, including health. And it’s going to continue to be complex. It’s going to continue to be uncertain. It’s going to continue to feel a bit like chaos. And we have a sort of series ongoing activities that contribute to that. But, there’s another part of the soft science I just want to hit on. And that’s that there are things that the soft sciences can teach us, right?

Amy Abernethy: [06:30] There’s the things we can learn from sociology about how we deal with this. And I think that we’re going to start to do more, to build that into our capability set for COVID-19. So, thinking about agility and resilience and how that’s going to help us as we continue to navigate, we have to really start considering COVID-19 a marathon, not a sprint. This is a different muscle group in order to manage this, right? We need to go back to core principles. One of the things that’s in our core principles set is a focus on science and data and make sure that we’ve got the information right. And another is learning from what’s happening and being willing to update what we think we know in order to make the next move, in order to how to manage the virus. And another is consistency and communication and leadership is very important, and all of that.

Amy Abernethy: [07:20] The other thing that I would say is that we need to codify what has worked and then be really clear what hasn’t worked and what needs to be updated. And sometimes things that we’ve codified as working themselves are going to need to be updated. And, ultimately right now, as we think of the criticality of public health measures, they’re going to need to stay in place. We’re going to need to continue the criticality of the mask and social distancing and public health measures like hand washing. And there’s going to be other things that we’re going to need to think about how do we update such as how we evaluate contact tracing and super spreader events. And what do we learn about how this virus is essentially being disseminated across our community.

Amy Abernethy: [08:10] So I think these things are going be changing. Finally, I would say, go back to the data and the science, what do we add into our therapeutic regimens? We’ve learned across time that we often need cocktails to manage disease, and we may end up in the same place in COVID, but, in the beginning we need to study individual therapies and understand how they perform. We understand the role of vaccines; we’ve got to get this right. We need to continue to improve on our understanding of the role and how we’re going to use diagnostics.

Bob Kocher: [08:39] So what you said makes total sense. I’m curious, how do you manage that with the expectations of political people who badly want sort of answers sooner or guidance as to reflect their interests, as opposed to the best science?

Amy Abernethy: [09:03] Yeah. I’ll start. And Andy, I’d love for you to follow up here. Ultimately, it is important again, to go back to first principles, to acknowledge that we have had long-standing processes in place that we know how to follow. We’re practiced at, for example, reviewing applications and understanding the weight of the evidence, both risk and benefit. And we can’t lose that practice. We need to make sure that we keep our eyes on carrying out that task, even when there’s a lot of noise around us. Part of those first principles is that of leadership, and leadership at the agency, the leadership that is around us, making sure we create the space for that work to get done in a thoughtful and disciplined manner. And so I think that becomes really important. And the last thing in there is that we acknowledge that it’s hard, including for the people who are trying to carry this out so that there is a sense of the safety of the environment to get the hard work done.

Bob Kocher: [10:12] Andy, what would you say? You’ve been around policymaking and politics and trying to create space to have the right things happen. What are your thoughts for how we can do better?

Andy Slavitt: [10:27] The first principle here, I think, is for everyone to keep in mind that the science is good, that vaccines are good things. And that we can’t contribute to vaccine hesitancy by worrying about the politics of the moment. We should all have the attitude that as soon as Amy and the other 17,000 brilliant men and women at the FDA tell us a vaccine is ready and show us the data, that that’s great news and it’s happening in record time. And no matter your bill political belief, it’s easy to get knee jerk about this, or cause people to be concerned and so forth.

Andy Slavitt: [11:13] And the truth is that we all want a working vaccine that is a part of our arsenal as soon as possible. And both sides need to keep in mind that if they’re concerned about the politics they don’t let that spill over to making Americans hear messages that make them worried about vaccines in general, we don’t want to go back there. Second thing is there are no better people in the world than the people at the FDA to guide us through this. And so we have to help the public understand the difference between the FDA and the politics of Washington and the politics of the moment, that we have an institution. And if we didn’t have that institution, I imagine what we would have imagine how we would figure out what medicines were safe, what medicines were effective, what food was safe, what food was effective.

Andy Slavitt: [12:03] So we also can’t undermine the effectiveness and people’s belief in the FDA and the CDC. It doesn’t mean that they’re perfect, doesn’t mean they don’t get it wrong. It means that they looked at the data, they make their best decision and they adjust. The third thing is, anybody thinks that there’s politics not involved in every thing at this stage, moments like this, no matter who’s president, there’s always some element of politics. So it’s not like there’s a pure distinction. Now, historically your job running an agency – I think Rob Califf says this as well – is to protect the people of the agency to do their best work from the politics, keep the politics out or filter in the politics as a check on reality, right? Because you don’t want people in a room saying “I’m going to do this in 20 years without any consequence.”

Andy Slavitt: [12:57] So look, I think we’re going to get through the next month. Things will hopefully tone down some short time after that. And then I think it’ll become easier. In the meantime, I really respect the fact that Amy and her colleagues, as well as former FDA commissioners have been vocal and have been part of the dialogue and have been part of the debate. Because the last thing we want is a confused public, a confused public will really hurt us. So the fact that we have the folks speaking out, it’s not as good as being able to speak with one voice, that’s what we want. But in the meantime, I think we do have some breaks in the system.

Bob Kocher: [13:41] So one thing that I’m wondering about is we’ve been in this plateau of sort of ~40,000 cases a day for quite some time. And, we’re making some progress in some places and we’re seeing regression in other parts of the country. Is it possible to sort of break the back of transmission like maybe Asia has, and would it be prudent to potentially take more aggressive actions in more systematic national way as opposed to letting each State and each County decide how to manage this? Would that make a difference?

Amy Abernethy: [14:20] So, ultimately this kind of core question of can we learn from other countries, can we learn from specific measures in Asia and in Europe, in Africa? And, ultimately as I think through this, there are a series of isolated events we can learn from all across the world. The challenge being that ultimately the cultures are different. The populations are different. The ability to systematically get everybody in line following the same set of rules looks different in United States than other places in the world. I think that’s fascinating that we don’t necessarily have to go that far. We have a series of systematic events happening within the United States that we can learn from. And, the first thing that I reflect on is just a few weeks ago I was in Orlando and this is the town that I grew up in.

Amy Abernethy: [15:19] And I am there at the same time as the NBA bubble. So on one side of Orlando, we’ve got the NBA bubble, we have $150 million plus investment in trying to make sure that the players are kept safe and that COVID is kept out. And this included, for example, innovation and diagnostic testing that went on within the bubble, it included the expectation that everybody performed in a similar manner. It also included the very distinct messaging to people who did not follow the rules of the bubble. And I believe there was over a hundred page bubble rule book. And then, just down the street in Orlando, we had a series of events with no masking, many people together, and no consistent messaging as to how to participate within the community.

Amy Abernethy: [16:14] And you see persistent community spread on one side of town and really no spread of COVID on the other side of town. So we have individual activities to look and see, what does it take for this to be performed within our own country? And so that’s the first thing I would say. The second thing I would say is that these micro experiments are happening all across our country, whether it’s state by state or county by county. We’re getting better at being able to understand what happens across individual counties and states. But in fact, we still don’t really have the data to learn from those events and understand the features that are allowing, for example, COVID spread to persist in some areas, go up or go down depending on specific areas. And so the second thing I’d say is we need to learn from those individual elements.

Amy Abernethy: [17:02] And then the last thing I would say is we need to learn about what’s happened across time. March is very different than September. What have we learned? And what have we forgotten since March, the importance of how do we ultimately within our country figure out how to collaborate and communicate? How do we ultimately understand what made a difference in my own life three months ago, and what have I sort of forgotten because it’s just too hard to persist, and what I need to go back and learn. So I think there’s a lot of this activity we actually need to bring back to our own life here in the United States.

Bob Kocher: [17:33] As a person that worked in the California response, one of the big challenges we had is that we had counties adopt public health policies. And so we would have a lot of receding, we would see that when we sequenced the virus and, coming back communities and sort of reinfecting people and even we had different public health orders, even though we had sort of a statewide one, it was adopted differently. And obviously that’s just in California, let alone the rest of the country. Do you think that the local control of public health is I mean, you mentioned that the learning opportunity, do you think it’s a barrier to our effective response as a country right now for a pandemic? Because these were laws designed for more local outbreaks.

Andy Slavitt: [18:20] Yeah. I mean, look, let’s stipulate a couple of things here. First of all, we think we know cause and effect of what is allowed in certain places to handle this better than others. I would posit that we don’t. There’s so much randomness that goes on that we could say, well, Arizona open this and the other state didn’t and therefore that state did better, and therefore Arizona was wrong. I had the most fascinating conversation with Ed Young and he basically said a big epidemic is a weird epidemic, basically, meaning you’re going to see every edge case, and we’re watching it from like four feet away, our eyes are peeled. So and then, everybody on Twitter can see two data points and draw a correlation and believe that because they know data science, they know epidemiology.

Andy Slavitt: [19:04] And so you have a lot of theories out there, but we have gaps in our knowledge. And I suspect a year from now, there’ll be things that explain why some of the curves in certain states and certain localities are doing what they’re doing that we don’t know yet. It could be just transmission spots. It could be immunity levels. It could be susceptibility levels. It could be any of these things. I hesitate when people are positive that they know the answer because they’ve observed, kind of a community. So we have to have a lot more humility on all sides in this because we really don’t know what’s going on. And we really don’t know what’s going to happen in the fall.

Andy Slavitt: [19:52] No one has been able to predict these things so far, because there is a lot of randomness. Now wrong person gets off in the wrong airport in the wrong city and maybe our outbreak wasn’t in New York, maybe it would have been in Chicago, who knows. So in the meantime, that means that nobody likes the fact that you have to kind of operate a little bit more by the precautionary principle, while you don’t know. And that means more people having to pay the price in parts of the country where they’re relatively safer because we just don’t know. And until our knowledge advances, we don’t know what we can do. So the quicker we learn things like, Hey, you can go outside and Hey, you can open packages. I was at someone’s house last night.

Andy Slavitt: [20:40] And we were having this conversation about they weren’t sure whether or not you could still open packages or not. So this point about being so close to the science resetting all the time, getting a set of general rules and then the rest of it, Bob, I mean, I almost think it’s like are laws well-suited? I mean, I went through that with some of these lawyers, maybe, maybe not, but almost the bigger question is even if you could mandate things on a national level, are they more effective if have Ron DeSantis saying ‘uh no, I’m not doing it,’ right? And so at some level you can’t get around the problem we came to our problem with talking to each other and building consensus, explaining why, and giving people a light at the end of the tunnel. Governor Andy Beshear said to me, it’s a lot easier to ask people to do something than to do nothing.

Andy Slavitt: [21:35] So if I tell people, sit home wear a mask, that’s very hard. If I can tell people like go sew a thousand masks, everyone’s on board, right? So it’s like, we’ve got this weird thing where we’re not, I almost feel like there’s a formula here, because right before we have a vaccine or really good therapeutics, our best drugs are communication. It’s telling people, helping people explain why they don’t need to breathe near one another all the time in large spaces. And we’re still figuring that out. I think there are laws and structures that could help us, but I don’t think that’s going to stop the death threats for local public health officials by itself. I don’t think a mandate solves all the problems. I think someone who can and people who can sell the country on a path is going to be important. And I don’t know that that’s so easy.

Amy Abernethy: [22:34] So I agree with Andy and my answer to your question was that we don’t know the answer, whether or not we should be doing this in the microcosms of individual communities at the state level, at the national level. But, I’ve had this idea for a while now that we need to accelerate our understanding to try and define the understanding to these kinds of questions. At FDA we advanced a concept called the evidence accelerator to learn how to use all the different data sources available in service of COVID-19. And in order to do that, to basically get data holders, government, academics, industry, and everybody together in public-private partnership mechanisms around the same table, teaching each other what’s being learned in rapid scale and basically being very transparent and also making advancements through data and information and teaching each other. And so my thought here is that we need some kind of concerted, collaborative, transparent model for essentially the evidence accelerator of public health to try and figure out what do we do within the context of our communities.

Bob Kocher: [23:56] One of the things that will make many PhDs after this is the learning from all of these natural experiments that are happening, and I’m sure the FDA will be on the leading edge of also learning from that. If you both look ahead maybe 18 months into the future what are the changes that you most anticipate in how we’re living with COVID? Will there be testing we take before we do everything, will we all be wearing masks, will there be effective, early, applications of treatments. How do you see the world in 18 months?

Amy Abernethy: [24:35] So as you were starting to ask this question, I was sort of thinking about a little bit of a different question. So I’ll answer what I was hearing first and then shift. A lot of people ask me, there’s been a lot of changes that happen with COVID from the standpoint of FDA, and which of these changes are going to persist because we’ve learned now that this is a better way of doing things so to speak and it falling into a couple of different categories. So essentially, shifts in clinical trials, such as use of decentralized trial mechanisms, telemonitoring use of real world data fill in clinical trial datasets. There’s been shifts in how we think about the role of real world data and how we think about real-world data writ large, to answer questions of an evolving living, history of a pandemic.

Amy Abernethy: [25:29] And there’s also, I think, going to be shifts in how we think about lining up, for example, data sets and other activities, in service of those payer needs as well as FDA needs at the same time. So we can parallelize those kinds of processes. And so I expect that many of these lessons learned will come from having stepped back and saying, wait a second, by putting in these differences in the way that we get things done right now, were we able to maintain safety, continue with data quality and be able to get the data sets that we need in order to answer questions related to therapeutic effectiveness and safety vaccine effectiveness and state safety, et cetera. And also be able to do the work more efficiently or in a more patient-centric way. And I think we’re going to see ourselves really answer those questions in a very deliberate way.

Amy Abernethy: [26:24] And hopefully what we’re going to see is persistence of many of those activities. As it relates to what’s going to happen for ourselves as COVID-19 potential concerned citizens? And while, 18 months from now, we would love to be COVID-19 kind of in the rear view mirror, we may or may not be, but at that point we will be much more fluid in appropriate diagnostic testing strategies and I think we’ll be able to think about what’s the strategy for the population for me personally, for my school, et cetera. I think we’ll be much more fluent in both preventative measures from a therapeutic perspective, as well as therapeutic measures from a drug and therapeutic perspective. And then hopefully for the vaccine side.

Bob Kocher: [27:12] Andy, what do you think world looks like in a bubble or out of the bubble in 18 months?

Andy Slavitt: [27:21] So look, I think that probably everybody on this call, I’m looking at the roster, can imagine the science will help us a great deal and give us many, many more tools and that that will have a big impact. We’ll be able to self-test, we’ll be able to know when there’s peak seasons and people may be at higher risk. We’ll be able to continue to use the NPIs. We’ll have therapeutics, which will hopefully make this even less lethal than it is now. It’s far less lethal than it was six months ago. And I think that will continue and will solve some of these mysteries hopefully of what’s going on and how it’s spreading. I think the the last mystery to be solved on the science side is what the hell is it doing in the human body?

Andy Slavitt: [28:14] And why is it reacting so differently in so many people? And I think that will continue to be scary. I don’t think people will want to get this virus. I don’t think it will be like the flu, even if we start to approach, as we hopefully might, lower fatality rates. I think from a policy and healthcare system reaction standpoint, my answer is it depends. And won’t surprise you that I’ll say this, but I think it depends on if we see this in the rear view mirror, or as we get past that as like the crack epidemic of the nineties or the opioid epidemic of the most recent present and current present. And what do I mean by that? I mean that the crack epidemic was something that happened to other people.

Andy Slavitt: [29:05] We criminalized it. We talked about it as something that was far from us. We wanted to keep it far from us and we wanted to move on and keep our society separate. And as a result, our policy response was not very good, not very human. Not very understanding. The opioid epidemic has happened to us. It feels like it’s happened to us. I don’t think we’ve responded particularly well from a policy standpoint either, but we responded more humanely and we don’t see it as a criminal activity. We see it as something that we should try to understand and solve and move forward together. If we come out of this from a public health standpoint, you can imagine a world where there’s a set of people that are like, so glad that’s over, I need to get back to the life that I’ve got.

Andy Slavitt: [29:49] I had COVID fatigue a year ago, I sure as hell have it now. And by the way, I’m not giving any more money to CDC because they screwed up and I’m not giving any more money to the FDA, because I don’t trust them either. And I’m even less of a believer in science because this wouldn’t have even happened. And by the way, I don’t know anybody that it happened to, but I know five small businesses are closed. That’s one response. And the truth is we’ll have some of that no matter what. And then the other response is, oh my god this is happening to all of us. There’s a learning moment. There’s a teachable moment. Our healthcare system didn’t work right. We can fix certain things there. And we won’t have that nirvana moment because we’ve never quite do. And we have a split country. So some people will be in each camp. And, I hope that we’re able to come to some consensus and learn some lessons and progress, but it’s entirely possible that we learn no lessons from this or very few that we apply.

Bob Kocher: [30:48] This is from Kathleen Sebelius, who knows a lot about communication, and she’s asking the question: who should be the communicator for America on the message – what’s important to the public and also how to update the facts without undermining either confidence or the message, how should we do that?

Andy Slavitt: [31:13] I would love our CDC to do that. I would love our CDC to have it’s, separate from the white house, from Atlanta, it’s weekly call, it’s sit down chats with America, which says, “Hey, two weeks ago, we told you this, now we’ve learned the following thing. And here’s why, and here’s how and here’s the explanation.” And to be able to do that and communicate in a way where the public feels like it’s got one voice. CDC also then communicates to the local public health officials so that people are on the same page and have the same information. I mean, this isn’t particularly hard to do. You have to do it consistently and have have to have a place like that where people feel like they can trust that the CDC can do that. We can get back to that. The current CDC is not doing that, but there are so many people within the CDC that are trying to do that, that I know it’s possible. I don’t know what Kathleen thinks, but I suspect she has a lot of that same confidence in the CDC to be able to do that if they’re allowed.

Amy Abernethy: [32:21] I agree. CDC, it really has both the responsibility as well as this is their knowledge base and their mission. Ultimately I see FDA providing a really important resource to CDC in this, and being able to help maintain the standard of what good looks like with respect to appropriate authorization and review, so that we get the products available that are needed. And then CDC helping to understand from a public health perspective, how does our population manage itself? How do we manage ourselves? And then also make sure that those products are in our portfolio in a way that, that we know what to do.

Bob Kocher: [33:09] Amy, this is for you, this is from DJ Patil. One of the really wonderful aspects of COVID-19, back to Governer Beshear’s “let’s all make masks,” one thing that data scientists and tech people have done is many have come forward to support public health modeling and epidemiological modeling. How do we continue to engage that population, that’s jumped into public health and data science, to continue the mission of the FDA and public health in America?

Amy Abernethy: [33:43] I think this is an example of where we’ve seen incredible engagement, as well as sort of a sense of we’re all in this together, both from the standpoint of organizations who have data ready to figure out how to contribute to the cause, as well as scientists and software developers and others ready to figure out how to make sense of the data. But there’s a couple of things that I would say here. So the first is making it easy to participate. One of the things that we’ve done as FDA is prioritized the questions that we have. That way, if you do want to participate, you can have a list of topics and issues to go after and know that they will meaningfully contribute to the story. And I think we should be able to do that across all of public health.

Amy Abernethy: [34:34] The second is make it so that there’s visibility of participation and that’s important for two reasons. Number one is to provide credit. And then the other is to ensure transparency, because one of the challenges is that we need to make sure that the answers that are received are actually the right kinds of information that contribute reliable and credible information. And then the third thing here is to think about what have we learned from COVID-19, that’s going to be durable around this sort of large participation for the future. And a lot of this issue of durability has got to do with the building of new partnerships, the realization that innovation is needed in certain areas, and that innovation can now happen. And I sort of am struck by the fact that practically speaking within the context of the models we’ve developed at FDA, what we’ve figured out is the durability actually comes by showcasing what is possible, whether that’s through the data visualization of the week, or helping FDA realize what these different companies have to add that FDA now has in our day to day thinking, or ultimately showcasing the idea that a new innovation to solve this problem and privacy will be important for the future. Those are the kinds of things are going to create durability of this space.

Bob Kocher: [35:55] I’m going to make that the last comment and end on the following. We are all in this together, and we’re all better off for the work that both of you have done to help save many, many lives and to help us learn more quickly, both the hard science and the soft science, which we need if we’re going to deal with this well and together, and also for future pandemics. And hopefully the work that we’re doing today will help us be better prepared and better funded and better communicating and faster learning so that we can do better in the future. And we’re thankful for this conversation this morning, and the work you’re doing.

Building Commercial Open Source Software: Part 1 — Community & Market Fit

Since the early 90s, with the emergence of the MIT free software movement and popularity of Linux, there has been an accelerating shift away from proprietary, closed software to open source.

Today the open source ecosystem has over 40M registered users, 2.9M organizations, and 44M projects on Github alone. Just in 2019, 10M new developers joined the GitHub community, contributing to 44M+ repos across the world.

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Open source continues to be the heartbeat of the software community and one of the largest and growing segments of the market by IPO, M&A, and market cap; with new projects emerging well beyond low-level systems to machine learning, data infrastructure, messaging, orchestration, and more.

Companies such as Hashicorp, Astronomer*, Puppet, Confluent, and Databricks are a new approach to commercial open source, with a focus on deploying their open cores to the broad developer community and the largest companies in the world with enterprise-ready needs attached to them. All while actively contributing to the community and gradually opening up more of the closed platform to the community — and building big, meaningful businesses along the way.

These new approaches are building platforms that wrap open core packages with support, enterprise-focused capabilities, and enterprise-level stability to transform a solution into a high availability, horizontally scalable, modular service that can fit into any set of cloud or infrastructure needs. Riding a tidal wave of community growth and demand as the underlying projects proliferate across developers and enterprises.

While there is no one-size-fits-all approach, each of these companies have navigated a complex maze of decisions as they built and scaled their solutions: deciding when building a commercial solution made sense, ensuring the community still stayed in primary focus, remaining open yet balancing the needs of the enterprise, deciding when to focus on bottoms-up or introduce enterprise-wide selling, and how to remain competitive against the cloud providers.

Building a Commercial Open Source Company

In our time investing and supporting open source companies, we’ve learned several lessons about project & community growth, balancing roadmap and priorities, go-to-market strategy, considering various deployment models, and more.

So in the spirit of open source, we wanted to share these learnings, organized into a series of posts that we’ll be publishing every week — enjoy!

  • Part 1: Building blocks to a commercial open source offering
  • Part 2: Focus your commercial and OSS roadmaps on developer adoption
  • Part 3: Sequence your distribution & GTM strategy in layers
  • Part 4: Your deployment model is your business model
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1. Find Community-Project Fit

Ultimately the success of a commercial open source company first relies on an active community of contributors and developers supporting the project and distributing it to more and more developers. This means building a project that the community has decided is worthy of their participation and support is the most important goal starting out. The keys to building a vibrant community around your project center around earning developer love by solving an important and widely felt problem, inspiring and supporting others to actively contribute, and giving reason for a passionate community to begin to form around it; whether it’s around integrations, an ecosystem built on top of it, or new ways to extend the project. The key questions we ask ourselves when evaluating a new project are: Is the project seeing increases in contributors, commits, pull requests, and stars? Has the community rallied beyond this project amongst the many variants or flavors attempting to solve a similar problem? Is this project introducing a compelling new approach to solving a thorny and wide- felt problem? Have the project creators put forward an assertive and opinionated view on the direction of the project? Have they also been inclusive in ensuring the community has a voice and say? How would developers feel if the project was no longer available?

2. Build Around Project-Market Fit

Next is understanding how your project is being used inside of companies: how are developers using your project? What are the killer use cases? Where are they struggling to use the project? From there, you can decide whether building an enterprise offering around the project makes sense. For instance, is it a run-time service that companies struggle to host where a managed solution would see strong adoption? Are developers building homegrown solutions to make it work or stitch it together internally? Might customers need enterprise-level security, support, or performance in order to deploy into a production environment? Could the value of an enterprise solution wrapped around the open core eventually multiply if coupled with capabilities such as logging, analytics, monitoring, high availability, horizontal scaling, connectors, security, etc. Understanding how the project is being used and where there might be value-add for enterprise customers is key before embarking on building an enterprise service.

3. Start With a Loose Open Core

The goal in going open source to enterprise is to see widespread distribution and adoption of a project by a large community of developers which can eventually turn into a healthy cocoon of demand for an enterprise offering. To do so, it’s best to avoid dogmatic decisions in the early stages of going pure open or what/how will be closed. Rather, focus on keeping a loose open core; keeping the core open for the life of the project and building an enterprise offering as source-available and closed source capabilities that magnify the value of the core when being deployed into complex environments or use cases. Over time you can decide to graduate source available and closed source capabilities into the open core — more about that in an upcoming post. Keeping a loose open core allows the flexibility to continue to build and grow the community while offering specific SaaS or deployment models that meet the needs of the commercial market, and hopefully keep both constituencies satisfied.

4. Pick the Right License

Your project license structure is key to get right from the start; a permissive software license (MIT, BSD, Apache) allows for mass adoption by unburdening users from needing to contribute back. Protective licenses (GNU GPL) force forks/derivatives to release their contributions back as open source. Then there are variants such as the LGPLAGPL, and Apache 2.0 with Commons Clause that are mostly permissive but have specific limits if you’re concerned about cloud providers or others freeloading on your project into a managed service. Thinking through the competitive risks, such as what groups forking your project might be able to do, or if the cloud providers could fork a managed service of your project, are critical to designing the right license structure. See, in example, the Redis Labs post on changing from AGPL to Apache 2.0 with Commons Clause and why.

5. Define Clear Principles for Open vs Closed

Constructing the right open core vs source available vs closed source strategy could be a company-making or killing decision. Source available and closed core need to be thought of as value-adds that wrap around open core, with many cases, in a path to eventually graduating into open core. Be explicit about the principles you use to decide what to open vs close, and how/when/if they graduate. A guiding principle for what to make part of open core vs closed might be (a) the closed enterprise/commercial edition only focuses on the needs of enterprise segment, or (b) the needs of companies that are post-revenue, or © based on use cases that exceed certain scale/performance requirements. Be explicit about it, write it down, share it with your community. The selected guiding principle then dictates when to release to the open core vs keeping closed The community often will understand that a strong commercial business is required for continued investment into the project, as long as you are explicit about the intentions and roadmap to continue supporting the community. These transparent principles will often avoid many of the conflicts between the community and commercial needs, i.e. the community pushing for a feature that competes with the enterprise offering.

6. Maintain Project Leadership

Even as the project creators, maintaining project leadership is key and is not guaranteed. This means striking the right balance between supporting and leading the community, and being explicit with the direction of the project, yet engaging deeply with the community. Taking an active role in the PMC if part of the Apache community, lead the AIPs, know the top 50 contributors intimately, and drive the direction of the project. Be responsible for the majority of the new commits and releases for the project. Ensure there is always a reason for new contributors to join and for the community to continue growing.

Next week, we’ll talk about focusing your commercial and OSS roadmaps on developer adoption.

*Venrock is an investor in Astronomer, the enterprise developers of Apache Airflow.


Building Commercial Open Source Software: Part 1 — Community & Market Fit was originally published on Medium.

Source: https://medium.com/@ethanjb