Want the best software engineers? Stop looking at Stanford and Berkeley. – Protocol

Swarthmore and UVA grads are among those scoring higher than students from elite institutions on the widely used SAT-style test for software engineers.
CodeSignal’s new report draws on just one data point: how people perform on its standardized assessment of the General Coding Framework.
It should feel safe to assume that the average computer science graduate from Stanford University would ace a coding proficiency test like the one given to entry-level software engineers at companies like Square. Most of them do. But on average, they are not the best of the best.
Stanford CS grads don’t even make the top 10 list for high scorers on the General Coding Assessment, the coding proficiency test designed by CodeSignal and given to software applicants at most major tech companies. Neither do those from the University of California, Berkeley, which is tied with Stanford for the second-best engineering school in the U.S. News and World Report college rankings, behind MIT.
Ranked ahead of Stanford (at slot 13 on this year’s CodeSignal list) and Berkeley (17) are schools like the University of Virginia, Charlottesville (1) and Swarthmore College (10), neither of which are famous for their CS degree programs. Twelve schools on CodeSignal’s list don’t appear anywhere on the U.S. News and World Report’s list of top 30 computer science schools, including Ivy League institutions like Yale (3) and state schools like the University of Colorado at Boulder (11), the State University of New York at Stony Brook (22) and Arizona State University (29).

Meta, Robinhood, Square, Uber, Instacart, Zoom and Asana are among the companies that have used or currently use CodeSignal’s assessments in hiring. CodeSignal creates these ranking reports each year as part of an effort to convince these companies and the rest of the industry that recruiting primarily from universities with prestigious reputations in software engineering is an inefficient use of resources. Elite universities like Stanford produce graduates with generally high scores, but the report aims to show that plenty of other schools train students who are just as competitive, if not more so, according to CodeSignal CEO and co-founder Tigran Sloyan.
“You could find a whole bunch of amazing software engineers at the University of Central Missouri, which graduates more CS grads than Stanford and Harvard combined. Companies spend millions and millions of dollars chasing grads from the Ivy Leagues, and they don’t even recruit sometimes from the other schools,” Sloyan said. “In this incredibly competitive market, it’s crazy.”
The tech industry’s racial, ethnic and socioeconomic makeup has remained relatively stagnant over the last several years. For tech companies that profess a desire to change that, recruiting from schools beyond the stereotypically elite institutions might be one of the most straightforward ways to go about it. “Talent is everywhere; you’ve just got to be able to look for it directly by measuring skill set versus by relying on, ‘Oh, we hear people from this university are good,’” Sloyan said.
Unlike traditional college rankings, which calculate degree program success based on attributes such as graduation rates, job placement rates, reputation among peers and funding, the CodeSignal report draws on just one data point: how people perform on the company’s standardized assessment of the General Coding Framework.
Sloyan argues that the industry’s widespread adoption of CodeSignal’s assessment has created a statistically significant data set that companies and job applicants should trust. Students and entry-level engineers everywhere grind in preparation for this test, and all types of tech companies use it to screen their applicants. More than 160,000 engineers have taken CodeSignal’s assessment, and the company estimates that more than 50% of graduating CS students take the test. Most college computer science programs teach algorithmic problem-solving skills, and the test is designed to assess those skills rather than knowledge of a specific language like Java or Python.

Students applying for competitive tech jobs train themselves on practice problems and tests that emulate the assessments these companies use, trying to estimate what score they might be able to get. Subreddits like r/csMajors are loaded with questions like “How high of a codesignal general score should I aim for to get an interview at Square?” and “How hard is the Facebook codesignal assessment for University grad role?”
CodeSignal scores range from 600-849, and the company says that scores above 800 indicate excellent problem-solving skills equivalent to the 84th percentile. The university ranking list is based on how many test-takers from each school score above 800 out of the total pool of people from that school. An impressive 43% of test-takers from UVA Charlottesville scored above 800 in 2022, while Swarthmore’s 22% sits just above Stanford and at about the same level as the California Institute of Technology.
At Swarthmore, a tiny liberal arts college, the computer science program will graduate just over 50 students this year and managed to best not only Stanford and Berkeley, but the Georgia Institute of Technology and other massive engineering institutions. Swarthmore CS graduates are excelling in more than just the CodeSignal test; at the North American championship for the International Collegiate Programming Competition last year, a Swarthmore team placed fourth, becoming the only liberal arts college in the United States to qualify for the world championship.
Andrew Danner, the college’s computer science department chair, speculated that the school’s focus on algorithmic problem-solving over teaching specific languages might explain its success.
“Our intro course, it’s taught in Python, but the goal here is not to teach you Python, it’s to teach you enough Python so that you can solve some computational problems with it. We do that again in our intermediate courses too where we switch the language and teach them C and C++ so that they see a variety of different languages throughout their career,” Danner said. “There are also a lot of schools, you come in and you start learning Java, you do Java your entire time, you know that language extremely well and maybe do not know how to adapt to other languages.”

Computer science is the most rapidly expanding degree program for undergraduates at almost every school that offers it. At Swarthmore, it’s now one of the top three degree programs despite the fact the school doesn’t actively recruit students focused on CS. Because of the school’s small size, students have certain advantages compared to those at larger schools with famous degree programs. While a student at an elite research university might take a 300-person CS class with teaching assistants, the largest class at Swarthmore is around 60 students, and everyone will learn from the professor.
“I think debunking that myth that the best people only go to the top schools is such an important message for everyone: for companies, for parents, for students,” Sloyan said. “Students get it into their head, too. When you get it into your head, ‘There’s no way I can be great,’ that becomes a self-fulfilling prophecy. It’s practice, dedication that gets you to that skill level.”
Anna Kramer is a reporter at Protocol (Twitter: @ anna_c_kramer, email: akramer@protocol.com), where she writes about labor and workplace issues. Prior to joining the team, she covered tech and small business for the San Francisco Chronicle and privacy for Bloomberg Law. She is a recent graduate of Brown University, where she studied International Relations and Arabic and wrote her senior thesis about surveillance tools and technological development in the Middle East.
The AI revolution has already started, and business, academia and government need to act together now to prevent harm.
Devising a globally accepted set of AI principles and convincing institutions to adopt it will be a heavy lift.
Bishop Garrison is vice president of government affairs and public policy at Paravision.
It is an iron law of progress that any innovation that benefits society also has the potential for harm. We saw it with the train and the automobile. We can already see it with genetic engineering. And now we are seeing it with artificial intelligence.
Every day brings a new report of how artificial intelligence is opening up new opportunities to detect disease and eliminate hunger, to understand the nature of the universe or to combat climate change. Yet darker uses are also emerging, including deepfakes, disinformation and autonomous weapons systems capable of using lethal force without human intervention.
We find ourselves on the doorstep of the next great societal challenge: harnessing the benefits of artificial intelligence while also ensuring it is used ethically and responsibly. It is our responsibility to establish processes and policies now to determine whether AI will be helpful or harmful in the future, and how we will protect against illicit or dangerous use. The problem is manifold: How do we ensure the private sector develops this technology ethically? What do AI ethics even entail? How do we keep social biases from being embedded in and amplified by AI?

These are not rhetorical questions. They represent issues of generational concern that require both great debate and an enormous amount of collaboration between the public and private sectors. Business leaders, academics and public servants must trust one another to smartly and thoughtfully devise these solutions together. No one group will have the answer, and no singular entity will know what is in the best interest of society regarding a technology with potential that rivals — and perhaps exceeds — any yet developed in human history. We must establish these tools of trust.

The stakes posed by this dilemma — our need to get this right — make it a formidable but not impossible task. During my time in government, I participated in initiatives that navigated a host of intricately detailed, politically charged and complex problems. We rethought the future of passenger screening at the Department of Homeland Security. We supported efforts to combat sexual assault and sexual harrassment within the ranks at the Department of Defense. And I led a group of dedicated career civil employees and uniformed service members to devise recommendations on countering extremist activity within the U.S. military. I learned that tackling these problems takes an investment in people and as well relationships built on trust.
These were all difficult tasks, on a professional and personal level. They were politically sensitive, divisive and required a whole-of-community approach to develop solutions that addressed the root causes of each problem. These issues are no less complicated, but also no less urgent. Given the projected long-term capabilities of AI, ensuring its ethical use is paramount to the safety and security of the global community.
If we do not come together now to address these challenges, the consequences will be devastating for our nation and societies worldwide. This will take governments at all levels working hand-in-hand with industry, academic, community and policy leaders in a lasting public-private partnership. Determining the proper oversight, regulatory framework and resourcing will be critical to create standards that result in the least harm and the most good while simultaneously ensuring that innovation and creativity in this arena do not become stifled or suffer a chilling effect.

Critics may object to the entire project on the grounds that ethical standards can only make U.S. AI companies less competitive. They may agree with former Google CEO Eric Schmidt, who once argued of face recognition, “there is no U.S.-China contest; the United States has essentially conceded the race because of concerns over the average individual’s privacy, and deep reservations about how this technology could be deployed.”
While I greatly respect his experience and acumen, I disagree. The performance of U.S. face recognition companies in recent government benchmarks suggests that principled development is no obstacle to world-class AI performance. Perhaps more to the point, we have never been a country to run from the difficulties associated with solving hard problems or making generational breakthroughs. This is a time of challenge, a time of controversy, and it is our time to be measured.
Make no mistake: Devising a globally accepted set of AI principles and convincing private and public institutions to adopt it will be a heavy lift. But ignoring the challenge is not an option. If we want a future consonant with our values, we need to address this problem now, together, with every asset at our disposal.

If you thought the rise of remote work, independent contractors and contingent workers rose sharply during the pandemic, just wait until the next few months when you see a higher uptick in the on-demand talent economy.
Rising workload and pace, the stress of commuting and a taste of the flexible work-from-anywhere lifestyle have all contributed to what many are calling the Great Resignation, which is only just the beginning of the headwinds organizations are facing, says Tim Sanders, vice president of client strategy at Upwork, a marketplace that connects businesses with independent professionals and agencies around the globe.
“It began with front-line workers, but it’s not going to end there,” Sanders notes, “Recent data suggests that the biggest industries for quits are now software and professional services and on top of that, I predict that we’ll see more leaders and managers continuing to quit their jobs.”
As the economy leans toward a recession, and layoffs across dozens of tech firms make headlines, Sanders predicts companies will increasingly turn to on-demand talent. “These highly skilled independent contractors and professionals offer the speed, flexibility and agility companies are seeking right now. Leaders are becoming more empowered to fully embrace a hybrid workforce and shift away from rigid models.”

Leaning into headwinds: Driving growth amid uncertainty
A recent report from Upwork, The Adaptive Enterprise, underscores the importance of flexible on-demand talent during uncertain times. Sanders notes: “A growing number of organizations, including Upwork and customers like Microsoft, Airbnb and Nasdaq understand that on-demand talent enables companies to reduce risk, drive cost savings, and at the same time, protect their people from burnout. Flexible workforce models also allow businesses to respond to and recover faster from crises than more traditional models.”
Some crises come in the form of economic slowdowns, while others can take the shape of geopolitical conflicts that disrupt life and work as we know it. Mitigating risk — such as a pandemic wave striking a certain region housing the majority of a company’s staff — is one reason businesses turn to on-demand talent, but it’s certainly not the only one.
CEOs surveyed by Deloitte in 2022 see talent shortages as the biggest threat to their growth plans. The survey goes on to report that CEOs believe that talent is the top disruptor to their supply chain and there is more to be gained within their workforce by providing greater flexibility (83% in agreement) as opposed to merely offering more financial-related incentives. What is top of mind for many business leaders is needing to fill talent and skills gaps, so they can deliver new products and enhanced services. In other words, companies are struggling to find the specific skill sets needed to advance their business objectives and innovation agendas.
The biggest benefit of leveraging on-demand talent is often tapping into the talent and skills that businesses can’t find elsewhere. Upwork’s recent report highlights that 53% of on-demand talent provide skills that are in short supply for many companies, including IT, marketing, computer programming and business consulting.

By harnessing a global talent pool from digital marketplaces like Upwork, businesses have wider access to skilled talent who can accelerate what those companies offer to customers at a fraction of the cost. “Skillsourcing” on-demand talent helps companies maintain a more compact population of full-time employees to concentrate on work that only they can do as well as maximize their strengths while bringing in independent professionals to handle the rest.
Behind the growth: Speed, flexibility and agility
Speed, flexibility and agility are three critical benefits offered by on-demand talent to businesses seeking competitive advantages in their sector. While on-demand talent solutions give companies speed-to-market advantages, Sanders sees that they also give organizations a strategic form of flexibility.
“An agile organization is able to make bold and quick moves without breaking everything,” Sanders says, “and look at a number of our Fortune 100 customers that have a workforce made up of almost half on-demand talent, and how they can pivot on a dime. It’s a case of structure enabling strategy.”
As for speed and efficiency doing the actual work, Sanders says clients report that when hiring managers have been given access to on-demand talent, they engage the needed talent within days instead of months, and when they bring them onto projects, the work is completed up to 50% faster than through traditional avenues.
Sanders says, “Businesses have realized that remote work experiences are best led and judged by outcomes, not just time in the office, and more leaders are comfortable and confident opting for a hybrid workforce that can deliver based on those outcomes.”
Upwork’s Labor Market Trends and Insights page shows that organizations are indeed ramping up their hybrid workforces: 60% of businesses surveyed said they plan to use more on-demand talent in the next two years.
“The old way of acquiring talent isn’t efficient,” Sanders says. “Staffing firms aren’t the silver-bullet solution they once were, and more businesses need to rethink and redesign their workforce with on-demand talent as the economy and work rapidly evolve. The conversation is no longer about the future of work, but the future of winning.”

John Stark, founding chief of the SEC’s Office of Internet Enforcement, is joining other experts in a major gathering of crypto skeptics.
“[I]t’s not the early days. It shouldn’t be hard for anyone to explain to me the benefits,” says John Stark, leading crypto critic.
Benjamin Pimentel ( @benpimentel) covers crypto and fintech from San Francisco. He has reported on many of the biggest tech stories over the past 20 years for the San Francisco Chronicle, Dow Jones MarketWatch and Business Insider, from the dot-com crash, the rise of cloud computing, social networking and AI to the impact of the Great Recession and the COVID crisis on Silicon Valley and beyond. He can be reached at bpimentel@protocol.com or via Google Voice at (925) 307-9342.
John Reed Stark helped launch the SEC’s Office of Internet Enforcement in 1998, at the height of the dot-com boom.
Under Stark, the office’s founding chief, the team had the task of clamping down on securities fraud committed through the nascent but rapidly expanding web. The job was to go after the bad guys with the same technology they were using — technology that Stark found fascinating.
“I was an internet evangelist,” he told Protocol. “I was out there talking about how incredible the internet was and how infinite the possibilities were.”
More than 20 years later, Stark is speaking out against what he considers a new wave of fraud. But this time he’s also taking aim at the technology that he says the scammers are using: cryptocurrencies and blockchain.
“There’s so many reasons to be skeptical of cryptocurrency,” Stark said. “I just feel like it’s really shameless.”
Stark has emerged as one of the most outspoken critics of crypto and is a leading figure in the movement pushing for a more critical view of the industry and the trend.

This loose network includes leading technologists, academics, journalists and activists. One of them is the prominent software engineer Stephen Diehl, who was among the technology experts who in June sent a letter to U.S. congressional leaders urging them to resist the crypto hype.
On Monday, Stark will join the first major conference of this network of crypto critics, including Rep. Brad Sherman, chair of the House Financial Services Subcommittee on Investor Protection, and Alex Sobel, a member of the British Parliament.
In an interview with Protocol, Stark discussed what the network of crypto detractors hope to accomplish and why he decided to battle the blockchain.
This interview has been edited for clarity and brevity.
How did the idea for this conference of crypto critics come up?
Stephen [Diehl] started working on that letter with a group of other extraordinary technologists. Once the letter came out, there was such momentum because the skepticism surrounding cryptocurrency, DeFi, NFTs and all that other Web3 nonsense is extraordinarily multifaceted.
There are so many aspects to it, whether you’re talking about bitcoin and the greater fool theory, or the externalities of ransomware and drug dealing and human sex trafficking, or the financial systemic risk created by cryptocurrency or the real bluster, hype and nonsensical belief in blockchain. There’s so many reasons to be skeptical of cryptocurrency.
There are critics who worry about the way the crypto industry is evolving, but they don’t totally reject blockchain technology. I get a sense that this movement totally rejects these technologies.
Yes, yes, yes. It’s a broad way of putting it. That’s fine by me because blockchain is the fundamental aspect of all this. And as the technologists explained in the letter, this is not the solution. [Blockchain technology] generally makes things worse. It doesn’t scale. It has all sorts of problems associated with it.
There was a Wendy’s commercial when I was growing up [which asked], “Where’s the beef?” I was chief of the Office of Internet Enforcement for 11 years. Almost my entire tenure at the SEC, which was almost 20 years, was spent in the juxtaposition of law, business and technology.

I was an internet evangelist. I was out there talking about how incredible the internet was and how infinite the possibilities were. I actually helped install the very first internet terminal at the SEC headquarters. It was this incredible technology.
“The crypto crime wave is taking the world by storm.”
Fast-forward to today. [I asked] one of these crypto enthusiasts, “OK, tell me what, what are the benefits here?” It’s just so incredibly aspirational, or it’s just a marketing ploy so that an IT person can get a little more funding. It’s not this panacea that people make it out to be.
On top of that, the ramifications of blockchain technology being used in cryptocurrencies, in NFTs, for decentralized finance — all of these things have wreaked havoc, not just in terms of ransomware, human sex trafficking, drug dealing. The crypto crime wave is taking the world by storm. Then there are the environmental issues associated with cryptocurrency mining.
What do you say to those who argue that crypto is similar to the web, which also encountered a lot of skepticism but eventually evolved and thrived?
The first thing I always say is, “Tell me a use that isn’t just broad-brush aspirational blather [like], ‘Hey, this is gonna make it so that when you buy your house, it’s instantaneous. This is going to make it so that when you make a credit card transaction, it’ll be safer than ever before.’”
They just throw out anything. They say it’s about financial inclusion, which is the worst of all — that it’s going to solve the problem of the unbanked. That’s how they loop people in. So what I say to them is, “Tell me a use.” Don’t tell me this is here to stay, just because a lot of criminals have begun using it and a lot of venture capitalists have gotten rich investing in it. Tell me why it’s worth it.

John Stark pointing to an office sign that reads "Division of Enforcement: Office of Internet Enforcement, John Stark, Chief" John Stark helped launch the SEC’s Office of Internet Enforcement in 1998.Photo courtesy John Stark
It doesn’t work as a currency. Is there anybody who uses it? Of course not. It’s way too volatile. What retailer would want to take it one day, and the next day have it be worth a third of what it was worth? It makes no sense.
And the idea that it’s decentralized is a complete fraud. There’s miners. There’s digital wallets. There’s the platforms, the exchanges. There’s so many intermediaries. There’s just more and more every time you read about it.
Seven or eight years ago, I was willing to entertain the thought that this might be something someday. But I’m just done with that. Because there came a point in my research, my writing and my experience, where I just felt like it’s really shameless.
Gary Gensler is considered a leading critic of crypto. But I’ve never heard him denounce blockchain as a scam. In fact, in his 2018 MIT lectures, he comes across as being open to the potential innovation from crypto and blockchain technology.
I completely appreciate Chair Gensler’s position. If you go back to my original writings in 2017, 2018 and even 2020, I would usually end by saying blockchain might have the most incredible potential.
I’m not a technologist, although I’ve been around technology my entire life. I’m not an engineer. So I was very careful.
“It doesn’t work as a currency. Is there anybody who uses it? Of course not. It’s way too volatile.”
Then I started to read more and more technologists and talked to more and more of them. I started gathering data, gathering information sources, watching lectures, reading everything I could on it. I came out one day a couple years ago and said, “You know what, blockchain is bunk.”
I stand behind that, not as someone who makes that conclusion somewhat reflexively or without a lot of study. Gensler was exactly where I was, at the same time that he was teaching. I think I would have said the same thing.

But you know, it’s not the early days. It shouldn’t be hard for anyone to explain to me the benefits.
There are crypto industry leaders who acknowledge the need for regulation and who are even taking steps to set up structures and systems for compliance requirements like KYC. What do you think of these moves?
I think, first of all, the industry is crumbling. You can view it with optimism because all of these venture capitalists are pouring money into it. It’s a magical money machine. Slap the label Web3 on anything and what do you get? An exponential enterprise valuation.
Look at the NFT market. Initially, I was kind of like, “You want to buy some silly-looking electronic cartoon with a link to a JPEG file and you want to pay a lot of money for it and help somebody else reap more money? Go ahead.”
People want to be ridiculous with their money, let them do it. But as you look into it, it became such an incredible industry, filled with so much fraud and chicanery. None of it made any sense to me. It looked like a big money-laundering machine.
Suddenly, to me, there was a lot of harm in this stuff, and the celebrities touting it, to me, seem so incredibly appalling, so shameless, that you would exploit your own fans so that you can pocket a few extra million. The conflicts of interests were so incredible.
People talk about, “We need a new regulatory framework.” I don’t see it. I see the existing regulatory framework. They keep saying how wonderful everything is going [but] we need regulatory clarity. We just want to do this right. There’s no transparency, at all, into any of these entities. And you cannot have a financial system without that kind of transparency. It’s just not safe.
I’m not a big regulations guy. But when it comes to finance, it’s just not an area where you can let people run free.
You argue that the industry is crumbling. But it’s hard to imagine crypto and blockchain disappearing.

You know, that’s a very good point. Like, what are we gonna do with this industry? It’s here to stay. All I can tell you is how bad it is.

What do you hope to accomplish with the conference?
The idea is to bring some sunlight into all of these many misrepresentations and fallacies of Web3, crypto, bitcoin, DeFi, NFTs — all of it. And to focus on all of the issues as to why these products are not a good thing.
We’re all just a hodgepodge of experts with different areas who will come together to talk about, through their lens, why they believe what they believe.
None of us are going to make any money by what we say in this conference. Maybe somebody is making money somehow, I don’t know. But I know that waking up in the morning to a bunch of Twitter hate and vitriol is not necessarily the right path toward business development and profit. There isn’t any anti-crypto factory you can go work in.
From my perspective, I think the magnificence of this conference is that it’s the first in history to really present these experts who are going to come together for the first time in a way that presents every angle. Because it’s a multifaceted situation. There are hundreds of cryptocurrency conferences, and they are all these lovefests where everyone just sits around and talks about how great it is, because they’re all getting rich from it.
I don’t mean to sound cynical, but that’s the truth. That’s the reality. So it’s a bit of an antidote for that illness, which plagues the space right now.
Can you talk about your role in creating the Office of Internet Enforcement?
That was a long time ago. I was always very interested in technology. I started doing a lot of just technology-only cases and developed a name for myself in the Division of Enforcement as someone you could go to if you had any sort of technology-related issues. I wrote the first set of guidelines for electronic investigations.
It started exploding. More and more cases touched the internet. There were so many investigative issues, so many prosecutorial issues. I wrote a white paper that we should create an office just dedicated to online [issues] that would help with surveillance, education, liaison and prosecution. We set up the first online enforcement complaint center. We set up an email box called enforcement@sec.gov. And I opened that email box every morning and read every single one and figured out what to do with each one.

I had this terrific director, Dick Walker, who was very tech-savvy in his own right, and he said, “Let’s create an office.”
They created the Office of Internet Enforcement, and that ended up just growing. We kept doing more and more. We had different experts — broker-dealer registration experts, tax experts. We had technology people. We also had seasoned enforcement people.
I have a picture of myself pointing to the placard outside my office, which said, “John Reed Stark, Chief of the Office of Internet Enforcement.” You can see I’m so excited, like a little kid.
Benjamin Pimentel ( @benpimentel) covers crypto and fintech from San Francisco. He has reported on many of the biggest tech stories over the past 20 years for the San Francisco Chronicle, Dow Jones MarketWatch and Business Insider, from the dot-com crash, the rise of cloud computing, social networking and AI to the impact of the Great Recession and the COVID crisis on Silicon Valley and beyond. He can be reached at bpimentel@protocol.com or via Google Voice at (925) 307-9342.
ARPA-E is quietly backing some of America’s riskiest — and most promising — climate-saving tech.
The wonkily named Advanced Research Projects Agency–Energy has built a reputation among founders for game-changing funding that’s helped startups through their earliest stages.
Michelle Ma (@himichellema) is a reporter at Protocol covering climate. Previously, she was a news editor of live journalism and special coverage for The Wall Street Journal. Prior to that, she worked as a staff writer at Wirecutter. She can be reached at mma@protocol.com.
Inside the vast ecosystem of the Department of Energy sits an unassuming agency that’s quietly shaping the transformative technology needed to confront the climate crisis.
Relatively unknown outside of climate tech circles, the wonkily named Advanced Research Projects Agency–Energy (or ARPA-E for short) has built a reputation among founders for game-changing funding that’s helped startups through their earliest stages.
While a number of technologies to reduce carbon emissions are mature — think wind turbines, electric vehicles and the like — there are still countless innovations needed to get the world to net zero. Venture capital can play a role in helping nascent technologies such as carbon dioxide removal mature. But ARPA-E fills a unique niche for startups with promising moonshot ideas that just require a little more TLC to realize their potential.
Though the office only employs a few dozen people and its $500 million budget is barely a blip in the Department of Energy’s nearly $82 billion pot, the agency has an outsize impact on fixing our most intractable climate problems. Since its inception, ARPA-E has provided over $3 billion in funding to more than 1,300 projects. Of those projects, 190 have together received more than $10 billion in private sector follow-on funding, and 25 have even had exits totaling over $21 billion. ARPA-E projects have also generated almost 900 patents and more than 5,700 peer-reviewed journal articles, reflecting the breadth of the agency’s impact.

“Their hit rate is better than the VC community,” said Christina Lampe-Önnerud, CEO and founder of Cadenza Innovation, a startup working on a cheaper, safer lithium-ion battery. Cadenza has received both an ARPA-E award and limited private funding for its battery technology.
In Lampe-Önnerud’s view, what makes ARPA-E a success is that the private market will focus on the obstacles in the way of an idea succeeding, whereas ARPA-E will take an unlikely opportunity and ask, “Well, what if it actually works?”
Formed in 2009, the agency was modeled after the Department of Defense’s larger and more well-known DARPA (Defense Advanced Research Projects Agency). That program has helped fund projects that gave rise to the internet, GPS and drones. Like DARPA, ARPA-E is focused not on funding incremental technologies but ones it deems transformative. Where ARPA-E differs, though, is in what radical technologies it backs: The agency’s mission is to seek out ones that cut emissions, increase energy efficiency or reduce reliance on foreign fossil fuels. Those projects are also almost exclusively high risk and high reward.
That model is exactly what the U.S. innovation system was missing, according to William Bonvillian, a lecturer in MIT’s Science, Technology and Society department. He points to the “valley of death” critique referenced by Lewis Branscomb and Philip Auerswald in 2002. That valley is where some promising technologies fail to go from technical ideas to commercially successful products. Letting disruptive emissions-cutting technologies linger there poses a serious risk to the climate, given the need to get to net zero by mid-century. Yet Bonvillian said ARPA-E “steps right into that gap,” bridging that valley and helping projects move neatly from idea to prototype.

ARPA-E’s secret to success is its organizational structure, which is modeled off the DARPA playbook.
At the center of the structure are the agency’s program directors. Some hail from national labs and others have formed startups of their own, but all have R&D leadership experience and deep subject-level expertise in their area of focus. Each is “very empowered” to decide for themselves what problems are most critical to prioritize and which proposed solutions are most promising, said Jennifer Gerbi, current acting director for ARPA-E.
“We look for people who can think problem first and impact as opposed to tech first, who are visionary thought leaders but also at the same time have a deep technical knowledge of this field,” Gerbi told Protocol.
Program directors typically have a focus area and put together a portfolio of projects, with some that Bonvillian said are “crazier than others.” He also noted that directors are encouraged to assemble a collection of projects with varying levels of risk as a way of hedging bets, similar to diversifying a stock portfolio. Critically, directors are term-limited, meaning they typically only have only three to five years to make something work at ARPA-E. That incentivizes people to really make the most of their investments while they’re there and means there are always fresh minds cycling in to challenge the status quo.
ARPA-E’s approach is a big departure from the way traditional federal R&D funding is doled out. Agencies like the National Science Foundation award grants based on a strict peer-review process with experts ranking different proposals. The highest-scoring proposals take the cake, and grantees must then stick strictly to the areas of research outlined in their proposals. While that approach ensures public money is spent by the book, the box-checking method for awarding research dollars can constrain what gets funded. The approach also offers little leeway for grant winners to change gears in their approach mid-grant.
Awardees who win ARPA-E grants, in comparison, have much more flexibility to pivot and explore new research areas if they run up against a dead end or find a tantalizing new possibility. Gerbi said the rule of thirds applies to ARPA-E projects in that, typically, around a third are successful, a third are terminated and a third end up pivoting to a different technical approach that the agency approves and for which the award is renegotiated.

Josh McEnaney, CTO, president and co-founder of Nitricity, a startup working to reduce emissions tied to nitrogen fertilizer production, said ARPA-E funding hits a sweet spot for startups. Its seed funding, some of which Nitricity has received, offers “more flexibility” than federal grants. But unlike venture capital investments, it doesn’t dilute founders’ equity.
While ARPA-E funding can help a startup explore new avenues, it’s what the agency offers beyond that that can be transformational.
Program directors do more than choose a portfolio of projects. They offer other forms of support to founders from pure technical guidance on data management to drafting a pitch deck to recommending events to attend, Gerbi said.
In Nitricity’s case, the startup’s program director was “very hands-on,” McEnaney said. “They want to get deep into the technology with you, go through slides of data and help you forge your path to the next best thing for your technology.”
The agency also fosters dialogue between its grantees. Companies in the program are encouraged to speak to each other and share ideas, which Gerbi said can lead to greater group innovation.
The agency also provides support through a dedicated tech-to-market team whose sole mandate is to help projects get closer to commercialization. This team is typically made up of people who’ve had experience scaling up research and are able to help identify market opportunities and connect with potential collaborators and funders. It’s a model so successful that Bonvillian said DARPA has since copied it.
“If you are a star performer, they will actively help you,” Lampe-Önnerud said.
The reputational boost that ARPA-E provides, which Bonvillian described as a “halo effect,” is a game changer for the projects the agency funds. “If you get an award, everyone knows, ‘Wow, this one was picked up by ARPA-E,” he said.

Because the agency’s selection process is notoriously difficult, having that imprint can make it easier for projects to find private sector follow-on funding. That can be crucial for early-stage climate startups, many of which are centered on R&D-intensive hardware that’s expensive to build. That was the case for Frost Methane Labs, whose remote devices identify, monitor and destroy methane in sites like coal mines and manure ponds.
Venture capital investors are typically less willing to sponsor hardware, or if they do, “the check sizes aren’t the same,” since the amount of investment required to reach the first step of commercial success is much larger than for software companies, Frost Methane CEO and founder Olya Irzak said. Hardware also takes longer to build and prototype than, say, code, which can be quickly rewritten. That, along with the condensed timeline that VCs expect for a return on investment, isn’t always well-suited to the kinds of moonshot technologies backed by ARPA-E.
Securing ARPA-E seed funding was crucial in helping Frost Methane cover engineering costs. Just as important, Irzak said the funding has definitely made the startup more attractive to VCs.
Time will tell the true scale of the agency’s impact. ARPA-E has only existed for a little over a decade, and hard technologies within the energy sector typically take about 15 years to scale up to real implementation, Bonvillian said.
“Has it changed the world yet?” he said. “No, but it certainly made a whole series of valuable contributions that can continue to be built on.”
Michelle Ma (@himichellema) is a reporter at Protocol covering climate. Previously, she was a news editor of live journalism and special coverage for The Wall Street Journal. Prior to that, she worked as a staff writer at Wirecutter. She can be reached at mma@protocol.com.
Last month, LinkedIn launched a new feature called “Diversity Nudges” to show recruiters how to widen their search and recruit more women.
Leaders sometimes say underrepresented talent is “hard to find.” Usually, they’re just looking in the wrong places.
Lizzy Lawrence ( @LizzyLaw_) is a reporter at Protocol, covering tools and productivity in the workplace. She’s a recent graduate of the University of Michigan, where she studied sociology and international studies. She served as editor in chief of The Michigan Daily, her school’s independent newspaper. She’s based in D.C., and can be reached at llawrence@protocol.com.
Megan Morrone (@ meganmorrone) is a senior editor at Protocol Workplace. Previously, she was a senior editor at OneZero, Medium’s premier technology publication covering technology’s effects on people and the planet. Prior to that, Megan hosted and produced several popular video podcasts at This Week in Tech and was an on-air contributor for The Screen Savers, a daily live television show about computers. She is currently the mother of three teenagers and the president of her dog’s fan club.
Tech leaders have made their commitment to DEI loud and clear. Meta, Google and Apple publicly back affirmative action, cybersecurity companies are trying to close the talent gap by hiring diverse employees for entry-level positions and some of those meticulously tracking their numbers have met some of the goals they set for themselves. But tech’s progress in hiring workers of color, women and other underrepresented folks is still incremental.
One excuse leaders give is that underrepresented talent is “hard to find.” Usually, they’re just looking in the wrong places.
Last month, LinkedIn began rolling out a feature called “Diversity Nudges” for LinkedIn Recruiter, the paid plan that companies use to find and manage candidates. The new update is designed to challenge that “hard to find” myth and help hiring managers find a more diverse group of candidates. According to LinkedIn, the feature will be available everywhere in the coming weeks. Right now, the feature only works for gender diversity.

If a recruiter’s search results skew either too male or female, the nudge feature will recommend ways to broaden the pool of results. LinkedIn says that if less than 45% of the talent pool is male or female, hiring managers will see a banner in their search urging them to change the criteria. The nudges also recommend certain locations, skills and companies that will most impact the hiring search. For example, adding candidates from a particular location or with a particular skill might increase the percentage of female candidates.
“It’s not an extra step that we’re asking recruiters to take,” said Jennifer Shappley, VP of global talent acquisition at LinkedIn. “It’s built into the day-to-day activities of a recruiter.”
Diversity Nudges will direct recruiters on ways to appropriately widen their talent pool.Image: LinkedIn
The goal is to help hiring managers expand their preconceived ideas of what makes a candidate qualified. Shappley noted that women tend to emphasize soft skills and men tend to emphasize technical skills. A nudge might tell recruiters that including soft skills in their search criteria will amass more female candidates. Ideally, that knowledge will stick with them.
Mandy Price, co-founder and CEO of Kanarys, a diversity, equity and inclusion technology company, told Protocol that “while many organizations claim there’s a pipeline problem when they can’t find diverse talent, we know that’s not the case because talent resides everywhere.”
LinkedIn infers gender through the information you provide in your profile and pronouns that others use when they endorse you. According to its website, LinkedIn does not infer gender through profile photos. Some people tell LinkedIn their gender in an “anonymous manner,” Shappley said, as the information is not public-facing. LinkedIn can also infer gender via LinkedIn identity-based groups listed in profiles. Anyone using LinkedIn can read how the company uses their demographic information, update their own and remove that information later if they so choose.
Diversity Nudges are limited to gender right now, as the company doesn’t have enough data yet to identify race, age, sexuality or whether someone is nonbinary. “Once we have sufficient self-ID data to have accurate sample sizes, we’ll also be able to expand our insights to race, age and more,” a LinkedIn spokesperson told Protocol.

The idea is that Diversity Nudges would make it that much harder for leaders to lean on the “they’re hard to find” defense, and is one more way to hold companies accountable to their DEI promises. Many big tech companies invest in elaborate tech that uses machine learning to root out recruiting bias. But that doesn’t mean they shouldn’t try the simpler solutions too.
Recruiters might not be aware that their approach to the day-to-day candidate search is actively impeding their diversity goals. “It is really hard to get people out of the routine that they have become used to,” Shappley said. “Being able to connect folks to that outcome they say they want with their daily behavior is really important.”
Two recruiters who spoke to Protocol were interested in the idea of the Diversity Nudges, but pointed to another feature of LinkedIn Recruiter as potentially even more useful. Both Kindall Carlson, senior technical recruiter at DailyPay, and Dan Logan, senior director of global recruiting at Beamery, said the tool that allows recruiters to hide photos and names in their search could do even more to eliminate unconscious bias.
Price from Kanarys called the Diversity Nudge “a great first step.” But if companies really want to fix their diversity problems, they must look within. “They need to examine their entire policies, practices and procedures to eliminate bias — not just change how they search for talent on job boards and other online platforms.” Price said this includes “standardizing interview questions, creating diverse interview panels, reworking job listings to include inclusive language, shifting to skills-based hiring and more.”
Lizzy Lawrence ( @LizzyLaw_) is a reporter at Protocol, covering tools and productivity in the workplace. She’s a recent graduate of the University of Michigan, where she studied sociology and international studies. She served as editor in chief of The Michigan Daily, her school’s independent newspaper. She’s based in D.C., and can be reached at llawrence@protocol.com.
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