Recent Lessons Learned The Hard Way

There’s no such thing as stasis. Only resistance to change.

If the marathon is long enough, you’ll eventually shit yourself.

Until you’re dead, you can survive anything.

At most, a person can only ever mean what they say in that very moment.

You can always hope, but expectations are nothing but dangerous.

There are three parts to you: The ship, the passenger, and the captain. The captain must always mind both its ship and its passenger in order to survive a sometimes brutal, one-way journey.

You can neither save nor be saved be someone else. Be your own fucking hero.

Love isn’t real until it’s freely expressed. And it isn’t true until you can let it go.

You can’t be honest with others until you can first be honest with yourself. And if it’s not hard somehow, then you’re not really being honest.

Just because you’re open, doesn’t mean that you’re not allowed to close a door. And just because a door is closed now, doesn’t mean it has to remain closed forever.

You can never really know anything. Most of what we perceive is filler. What we do perceive is filtered. And what we actually understand is only a fragment.

Nothing means anything, except for what it means to you.

You can never control how you feel, only how you respond to that feeling.

Everyone is broken somehow. You just never know to what degree.

Don’t get over it, ignore it, forget it, or regret it. Just deal with it.

Think of life as an epic experiment that can go terribly wrong or surprisingly well, sometimes both, and occasionally at all once.

Instead of anticipating every outcome, be open and see what happens. It will be way more interesting, and far more fulfilling.

Unplanned, happy surprises are the best experiences one can have in this life. Be that unplanned, happy surprise in someone else’s life as much as you can.

It’s better to not want anything too much.

A willing leader is an unworthy one.

If you can’t be vulnerable, then you’ll always be a coward.

If you’re perspective hasn’t changed somehow recently, then you’re not trying hard enough to understand.

At some point words will fail each other. At other points, words will be all that you have to save one another.

Three-Legged Leadership

There are countless approaches to leadership. This one is mine.

I never wanted to be a “Textbook Leader” or a “Paint-by-Numbers Manager”. My goal has always been to be authentic, unique, and teachable. Also, I have a terrible memory and find complex leadership methodologies unhelpful. So, I’ve recently been attempting to distill all the knowledge and experience I’ve gained so far into a simple framework that can be applied repeatedly. It’s already helped me navigate a variety of real-world issues.

Maybe you’ll find it helpful too.



An inexperienced leader is like a three-legged dog: Although incomplete and often awkward, it can still run.

If you’ve ever seen a three-legged dog run, you’ll notice a specific pattern: It places one paw after another in rapid succession, but always in the same order. The two hind legs propel it forward, while the front leg provides direction and braking power.

Likewise, a leader really only needs to take three steps to progress over any terrain:

  1. Be strategic
  2. Get input
  3. Be decisive

Now let’s look at each step in detail.

STEP 1: Be strategic

Leaders are confronted with complex problems every day. It’s how they deal with those problems that makes the difference between a good leader and a bad one. The most common mistake I make, for example, is reacting to these problems. Whenever I learn that something is broken or dysfunctional, my first instinct is to fix it. Now. And yet every time I try to fix-it-now, I usually just end up making things worse.

Why is reacting to a problem problematic? There are at least three reasons. First, when you’re hearing about an issue for the first time from another person’s perspective, you definitely don’t have the full story. By reacting, you’re in fact only responding to incomplete and/or inaccurate information. Second, when you immediately propose a specific solution, you aren’t considering other possibilities. Finally, by responding with a solution of your own, you aren’t empowering the person who’s raising the issue to take ownership of it. As a result, your “solution” likely won’t solve the problem, and the other person will only learn that they can run to you for help whenever things get difficult. This leads to poor results and a low performing team.

A good leader, however, takes a step back and thinks about the situation critically before actually doing anything. In essence, being “strategic” simply means breaking something down and then figuring out possible ways to build something better than before (not just “fixing” something prone to breaking).

For example, when something isn’t working, I force myself to ask some critical questions, like:

  • Who are the stakeholders and/or team members involved, and how are they being impacted?
  • What is the impact on the business or its goals?
  • What are the risks if the issue isn’t resolved?
  • What are all the potential solutions?
  • What are the short term and long-term benefits of those solutions?
  • Based on the above, which potential solution should you explore first? Which one last?

…and so forth. By doing so, you can uncover the actual problem while revealing more opportunities to make a bigger, better impact.

It sounds simple. Yet in practice it often feels unnatural to spend time analyzing a problem before attempting to address it — especially if that problem is urgent and/or acute.


STEP 2: Get input.

To be clear, being strategic is not the same thing as having a strategy. The former is a process for critical analysis. The latter is a concrete plan of action based on facts you’ve gathered during that analysis. In other words, being strategic allows you to get the right inputs necessary to define a strategy. One leg follows the other.

But getting the right inputs is also harder than it sounds. Whether you realize it or not, you already believe something about the situation, or the people involved, when analyzing a problem. If you’re not careful, you can end up reinforcing your prior (mis)beliefs instead of learning the actual truth. This is called confirmation bias. For instance, you might only ask specific people certain questions because you know that they’ll tell you what you want to hear — therefore “justifying” your beliefs and reinforcing your biases. As such, your potential solutions will only address an issue from that limited perspective. Depending on the size and severity of the problem you’re trying to solve, this can lead to disastrous results.

It takes intention and courage to get input from those who have wildly different perspectives than you. It also takes skill to ask the right questions without betraying anyone’s confidence or alienating those you’ll need support from in the future. The trick is to ask direct, open-ended questions, but without accusations or assumptions.

A few examples:

  • Instead of asking “What went wrong?”, ask “What did you observe?”
  • Instead of saying “Tell me what happened”, say “Show me what happened.”
  • Instead of the question “What should have happened”?, ask “What is the result you would hope to see going forward?”

In essence, your goal in gathering input should be to separate personal interpretations from factual information. If done correctly, you can more easily identify the root of a problem while building a coalition of support to execute a potential solution (and then pivot if one particular solution doesn’t work). If done incorrectly, those who are to “blame” for a problem will become further isolated and deprived of the opportunity to improve gracefully. Or, if nobody actually did anything wrong/incorrectly, then nobody will take responsibility for making things better.

The same applies for proposing solutions. When coming up with ideas, it’s all too easy to have a favorite. This is the most dangerous form of confirmation bias, because otherwise avoidable mistakes can quickly become major problems — perhaps worse than the original one. So, it’s always best to get input regarding any possible solutions, and to investigate opportunities with an open mind. It all depends on what questions you ask.

A few more examples:

  • Instead of asking “How can we make sure this never happens again?”, ask “How can we improve the process going forward?”
  • Instead of saying “Here are my ideas for fixing the problem”, say “These are some possible solutions.”
  • Instead of the question “Which solution is best?”, ask “How would you prioritize these possible solutions in order of greatest potential impact?

At the end of the day, you should want everyone to feel motivated and responsible for delivering better and better results over time. That isn’t possible if you don’t truly understand the issue to begin with, or seek only to implement the fastest/easiest/most convenient solution.


STEP 3: Be decisive.

So far you’ve taken a strategic approach to responding to a problem, and have gathered all the input necessary to define a plan of action. Now it’s time to decide to act.

As a leader, “acting” isn’t telling other people what to do (in the corporate world, at least). It’s about communicating — both who you communicate to, and how.

For example, maybe the problem can be solved by tweaking a process shared by a small number of stakeholders. In this case, communication across the team/department/company isn’t necessary — only the people involved need agree and commit to changing something. You just need to make sure those important conversations happen, and document the outcome.

Or maybe the problem is complex, and/or will take more time and effort to address. In such instances it may be necessary to inform a larger group what the issue is and how you intend to solve it. Then you might need to work directly with a few smaller groups to implement a solution. Once a potential solution has been implemented, it’s then always a good idea to follow up with progress reports and end results.

The point is that you must stand up as a leader and take a position, educate and/or work with others, and remain present throughout the process. It requires courage, energy, optimism, and thoughtful communication. A leader who acts is basically putting themselves on the front lines, while sharing ownership of the outcome. Otherwise, they aren’t actually being decisive — they’re just maneuvering in order to gain the most by doing the least.


The world of business is complex. There are many factors that contribute to any one problem, and there is almost always a human component. As such, there is no perfect formula for problem-solving for as long as there are imperfect people who must contribute to any solution.

You might be new to leadership. You might have some experience, but still lack certain skills/abilities. That’s okay. Like a three-legged dog, you can still run with the others. For as long as you respond to problems strategically, get the right inputs from the right people, and then demonstrate decisiveness through action, any problem is solvable.

Learning How to Lead: Part 3

Genuine leadership isn’t a formula. It’s personal.

I’ve gained a lot of experience as a leader since joining eyeo. Most of it has been tactical, like hiring, developing talent, establishing processes, and unblocking things that get in the way of progress. Some of it has been strategic, like developing a vision for the product team, driving innovation, and setting priorities. But I still have a hard time defining what kind of leader I want to be, beyond all the things that need to get done. So, I started working with a personal coach to help me develop further.

The coach sent me a list of questions before our first session, just to get a baseline. They were difficult to answer, since I couldn’t really answer any of them unequivocally. During our session, she asked me to define what a good leader looks like, or if I had any role models in mind. Apparently, I really don’t know how to define leadership beyond vague American stereotypes, and I honestly can’t think of any leaders that actually inspire me (especially present day). I admire a few traits here an there, but no one person embodies the full expression of leadership that resonates with me.

That’s when it occurred to me: To develop further, I shouldn’t be trying so hard to copy somebody else, just because I think that’s what people expect from me. Fuck listicles. Fuck how-to manuals. Fuck role models. Fuck whatever I think other people think. Most especially, fuck any standards depicted in popular culture. What’s my genuine expression of leadership?

Again, it’s hard for me to answer this question. All those opinions and depictions and past experiences suggest that I can never be a good leader. I’m antisocial, not especially charismatic, hate being the center of attention, refuse to network, and I really, really don’t like telling people what to do. The quintessential image of the “strong”, bold, confident leader that commands a stage, publicly eviscerates incompetence, and regularly rubs elbows with powerful people makes me want to puke. To me, that just screams “self absorbed, egotistical asshole that needs to prove how awesome they are, all the fucking time.” I reject that template entirely.

But I’m just now starting to embrace the idea that I don’t have to be/do any of those things — that it’s possible to be an effective leader, and still be genuinely me.

After thinking a lot about this, some themes have started to emerge. They have nothing to do with external traits (like “charisma”), but have everything to do with internal values.

Here are some examples:

A leader serves those in their charge first, their superiors second, and themselves last.

A leader shouts praise for others from the rooftop, but delivers a rebuke behind closed doors.

A leader welcomes criticism, but eschews recognition.

A leader is always the first one on the battlefield, and the last one at the watering hole.

A leader knows when to be gentle, when to be harsh, when to be flexible, and when to be firm.

A leader can motivate others without demanding anything.

A leader would rather fail together than succeed alone.

A leader plans for both wild success and total failure.

A leader may not know the right answer, but they always know the right questions to ask.

A leader surrounds themself with people more intelligent, skilled, and talented than they are.

A leader sees the patterns and pitfalls others cannot.

A leader knows two things at any given moment: their own weakness, and the potential of everyone they lead

A leader makes plenty of mistakes, just never the same mistake twice.


If I could become just half the leader described above, that would be enough for me. The important thing is that I identify with the description above personally. Others will have to define their own leadership style.

So, how would you describe the leader you want to be? I encourage you to embrace your own definition before trying to fit someone else’s. Otherwise you’ll end up becoming just another Listicle Leader.

Accidental Success

Lessons learned from launching a new product that wasn’t supposed to exist.

When we launched Trusted News — a brand new desktop extension that has nothing to do with ad blocking — my expectations were low. One or two articles from any publisher would have been enough to make me happy. Instead, a total of 78 publications wrote about the product, including TechCrunch, Fast Company, c|net, and engadget. Meanwhile, over 5,000 people are now actively using it 😀

Being the first product I’ve ever worked on that went from nothing-to-something, I credit any success to the team, timing, and our communications department. Still, it would be wise to reflect on what went right, since developing new products will be important to eyeo’s future success.

LESSON 1: Passion is paramount

I remember our very first meeting as an unofficial project team vividly. Having identified those who were potentially interested in embarking on this experiment, I presented the problem (disinformation on the web) and asked everyone lots of questions:

  • Did we genuinely care about this problem? Yes.
  • Did we fully understand the problem? Sort of.
  • Could we build something that would actually benefit users? Maybe.
  • Since this would be an unofficial project, were we willing to devote our free time to this, without knowing how long it would take or what challenges we would face? Hell yes!

Step 1 of our journey, therefore, was nothing more than declaring our willingness to work together, and commit to the experiment. A few people dropped out, either due to lack of time, interest, or technical experience. Those who remained were both passionate and ready to roll up their sleeves.

This inherent desire was our secret sauce. It’s what kept us going during many nights and weekends, got us through uncertainty, and helped us forge the right partner relationship to deliver a real solution.

LESSON 2: Partners are pivotal

About that partnership. It was pure serendipity that Paul Walsh, CEO of MetaCert, and myself happened to meet at the exact right time. Our marketing agency out in California, Rocket Science, introduced us shortly after we established a voluntary project team. Paul and I both worked in San Francisco, so we met for coffee and started talking. It turned out we both cared intensely about the same things, and his company could provide the data solution needed to build a functional product.

It wasn’t until much later that I realized how important — and exciting — this partnership would be. Not only did they create a custom technology solution (for free), they then figured out how to scale that solution for sustainable growth (again, for free). They were in this for the long haul, and they had our backs. As a result, our product would have actual, immediate potential for long-term success beyond its initial launch. That’s more comforting than I can fully express.

Only now do I understand the essential qualities any partner should have. Namely, they should genuinely share your vision, fully understand the problem you’re trying to solve, and be capable of delivering a sustainable solution. Everything else is about alignment and coordination, and takes a lot of work on both sides to get right.

LESSON 3: Size matters

Few people knew about the project internally. Those who did know doubted that we’d succeed in the end. So when we announced that Trusted News was going live — after just 11 months of semi-secret work — many people were caught off guard, and nobody knew how we pulled it off. This was actually intentional.

There were a lot of unknowns in the beginning, but there was one thing I was sure of: the fewer people involved, the better. If you know anything about working at eyeo, you know such thinking is blasphemous. We generally don’t do anything without involving anyone/everyone with an opinion to weigh in, debate about every single potential problem/solution, and then spend months in code review or QA.

But I wanted speed. We had to deliver something sooner than later. And that something didn’t need to be perfect. It just needed to work. If we could do that, then we could make it better over time. This is why I kept the team as small as possible, the scope of our vision limited, and the user experience super simple. If we didn’t know how to build something, we learned. If the vision was too ambitious, we scaled it down. And if the user experience could be trimmed down further, we did so without mercy.

By working as a small team under the radar, we avoided any bureaucratic pitfalls. By committing ourselves to creating a true “minimum viable product”, we could focus on delivering something of value now, instead of trying to build the perfect thing later. As a result, we introduced an entirely new product in less time than it took the rest of the company to build a single new feature for any of our existing products.

LESSON 4: Timing is everything

There was another reason it was important to prioritize speed over perfection. Since the 2016 US Presidential Election, “fake news”/disinformation had become a hot topic, and the media was paying a lot of attention to it. In less than one year, the issue had gone from a fringe issue that nobody cared about, to a one that’s generated endless headlines in the press. In other words, a lot of people already cared about the very problem our product was intended to address, and there likely wouldn’t be a better time to capitalize on that attention.

Yet it wasn’t just about delivering something soon. We didn’t want to just hit the “UPLOAD” button the first moment we could and call it a day. That’s why we developed a communication strategy and waited until an agreed upon day and time to have maximum impact. A few of us wrote blog posts about the launch, the vision, and technical details. Our marketing agency wrote a press release and lined up interested publishers. Ben, our Director of Communications, pre-pitched the story to the press. Then, at 3:00 pm CET on a quiet Tuesday, we collectively announced Trusted News to the world.

If we had waited until everyone else in the company understood and agreed with our plan, or the product was “perfect”, we likely would have missed the fake news party. And if we didn’t wait to launch at the right time with the right message, either the press would have missed it, or totally mangled the message. Instead, the launch itself has had a meaningful impact that we can easily build upon (instead of struggle to recover from).

LESSON 5: Downtime doesn’t have to be a downer

Truth be told, we probably could’ve launched a few months earlier. What held us back was our partner. It took them longer than anticipated to deliver the technical solution and relevant data. This was to be expected, though. MetaCert has a core business with existing, paying clients to take care of. The company is also growing like crazy, and they’re working on big, interesting stuff (like an initial coin offering for their new, proprietary cryptocurrency). The fact that they dedicated resources to build anything at all for us is amazing, and a testament to their passion for this project. And the fact that they thought about a long-term solution is proof positive of their ongoing commitment.

Still, one must remember that “downtime” is inevitable when working with a partner. Sometimes they’re ahead of you, sometimes you’re ahead of them. The important thing is to remain flexible. While MetaCert was working on the stuff we needed for launch, we spent our time studying the issue of disinformation more extensively, identifying potential issues, and conducting user research. Now that the product is live, all those investments we made during that downtime have provided the information required to develop a roadmap and a solid plan for extending the product beyond Chrome on desktop computers.

LESSON 6: Embrace your base, but mind the masses

There’s one lesson in particular that product companies often forget: There’s a huge difference between the early adopters of a product — your “base” — and the masses you want to reach. In our case, we didn’t do any actual marketing for the launch of Trusted News. Sure, a few people probably downloaded the product after finding it by chance on the Chrome Web Store. Most of them, however, learned about Trusted News from a news article. This means that many of our first users read about technology and/or new web products regularly, and likely have a deeper understanding of the “disinformation problem” than the average person. Being more educated also means that they will have higher expectations of our product, and are therefore going to be the most critical…and vocal.

The best thing about the “base” is that they already “get it”. Their feedback is extremely valuable, and the problems/issues they complain about are often things you need to improve anyway. Ignore them, and they will punish you. Embrace them, and they will become your future evangelists. But don’t make the mistake of trying to serve them.

The ones you should actually be serving are the masses — the millions of people you want to reach, but who don’t understand the problem you’re trying to solve very deeply. They have a simple need or pain point. They stumble upon your product by accident, learn about it from social media, or hear about it from their friends. Then they either find immediate value in your product (and continue using it), or they don’t (and never use it again). Interestingly, what they need/want is rarely want your base needs/wants. Early adopters want granular control, broad functionality, and the ability to influence the future of your product. The average users just wants shit to work, and don’t want to think very hard when using it.

So listen to your base, and then translate that feedback into a product experience that will appeal to average users. It’s simple in principle… but really, really hard to do in practice.

LESSON 7: Haters gonna hate

This is the most obvious, but difficult lesson every product manager has to learn.

When we announced the product internally, there were plenty of colleagues who thought it was a poor solution, doubted anyone would actually find it useful, or complained about the things that didn’t work exactly right. When the press wrote about it, some of them focused on the imperfections of the initial experience rather than the overall intention of the product. And dozens of users who disagreed with the label for a particular website immediately gave it a one star rating, left negative comments, and/or uninstalled the product.

Sure, these reaction hurt. But the feedback is usually valid, and it all confirms what we already knew about the product’s current shortcomings.

Yes, I’m sad that some users were so disappointed that they abandoned the product. But we know it will only get better with time. (We also see that the current retention rate is around 90%, so we’re doing something right.)

And yes, those in the technology industry who say our solution is limited, imperfect, or lame wound our egos. But you know what? Until they put some skin in the game and build something better, fuck them. At least we’re trying!


There will be many more things I have yet to learn (like how to scale a product that demonstrates early success). I certainly don’t want to loose our momentum, or make anything worse. I’m hopeful, however, that the lessons we’ve learned so far, and the one’s we’ll learn in the future, will arm us with the experience and knowledge we need to successfully launch other products in the future.

Let There Be Trusted News

Introducing an add-on for Chrome that measures the trustworthiness of websites you visit every day.

About a year ago, my wife (who’s also a User Researcher at eyeo) told me about an idea she had for a browser extension that could identify fake news. I shared this idea with the Product Team a few months later, only to discover that many of them already had a passionate interest in the subject. Knowing there was a collective will to act, and a unique opportunity in the market, I pitched the idea to our executives, who gave me their approval to explore a minimum viable product.

So, I formed a small team of core contributors and a few advisors—just enough people to get shit done. Together, we defined the opportunity, designed and tested a prototype, and then built something real. Today, the Trusted News Beta add-on is available on the Chrome Web Store in English-speaking markets.

Download Trusted News for Chrome

This is the story of how Trusted News came to be.

The Trusted News website heomepag

Trusted News website homepage


In the beginning we saw a huge opportunity to address fake news, and had lots of ideas for an extension. We wanted to do things like measure each page for accuracy, suggest alternative articles from websites across the political spectrum, and offer users the ability to categorize and rate content themselves. But an initial product, produced with limited resources, would have to be the best possible compromise between what’s possible now versus later (with more resources).

Therefore, we started with the basics: 1.) A solid vision 2.) great data sources and 3.) a straightforward user experience.

The vision itself is simple. Essentially, we believe that the distribution of misinformation online is a huge problem. Brexit, the 2016 US Presidential Election, and the polarization of society in general are just recent examples that have had enormous consequences. We wanted to build a tool that would rate the quality of content simply, accurately, and fairly as a user browses the web. However, it’s not within our authority (or ability) to declare what’s true, or what’s false… That should be up to the individual to decide for themselves.

Our primary goal, then, should only be to inform users of the trustworthiness of a particular source of information. They can believe or trust in whatever they want, but at least they have a tool that helps them separate fact from fiction. With this as our primary directive, we had a foundation to build on.


List of data sources

List of data sources

The really hard part was also the most critical. Reliable, unbiased data sources were the key to delivering any product worth installing. Only such data sources are exceedingly hard to come by (or openly accessible). Nearly all of the ones that do exist lean one way or another politically, and they don’t necessarily measure/score the same content sources.

Luckily, I happened to know the CEO of a company dedicated to information security and the accurate tagging of content. MetaCert started off providing cyber security tools to help developers and service providers keep porn off their networks. Then they began labeling all sorts of content that impacted corporate communication technologies, such as phishing attacks and malicious websites that were known to distribute viruses or malware through chat bots. They recently launched MetaCert Protocol, an anti-fraud and URL registry that pulls data from several sources, including PolitiFact, Melissa Zimdars for it’s News Reputation category, and their own extensive database, which identifies content across a variety of categories like fake news, far left, and far right. Plus, they offered a custom integration of their database into our own extension. MetaCert Protocol thus became our initial data provider.


We had a vision. We had data. Now it was time to design a user experience and an interface that was easy to understand.

Toolbar Icon

Chrome toolbar icon

Chrome toolbar icon

As a user navigates from one website to another, we wanted to arm users with contextual information without getting in their way. The first, most obvious way to communicate this information is through the Trusted News icon in the browser toolbar. We decided to make the icon display a traffic light system that immediately tells users whether a website is trustworthy (green), biased (amber), or untrustworthy (red). That way a user already has an indication of the trustworthiness of a website without having to click on anything.

Bubble UI

Example of a "Trustworthy" website

Trusted News interface showing the label “Trustworthy”

But if they do want more information, it should be simple to find and understand. The best way to do this is through the extension interface (aka the “bubble UI”), which is displayed whenever a user clicks the toolbar icon. Here, we had a limited amount of space to show information, and knew that whatever we showed would make or break the entire experience.

Example of an "Untrustworthy" website

Trusted News interface showing the label “Untrustworthy”

One challenge in particular were the labels themselves. We didn’t want too many categories, or to be overtly political. Yet we did want the labels to be meaningful and genuinely helpful in making decisions. In the end, we came up with several categories that would show prominently in the bubble UI using the data available from the MetaCert Protocol registry…

  • Trustworthy: Websites that are known to consistently provide quality, accurate information, regardless if the publisher is liberal, conservative, or moderate.
  • Untrustworthy: Websites that are proven to produce false or purposefully misleading content.
  • Biased: Websites that contain politically biased content or promote unproven or skewed views.
  • Satire: Websites that produce satirical content, and are not intended to be sources of actual news.
  • Malicious: Websites that are known to distribute viruses or malware.
  • Clickbate: Websites that knowingly uses misleading headings or article titles to attract readers in an effort to increase traffic and revenue.
  • User Generated Content: Websites that contain user generated content and therefore can’t be accurately evaluated.
  • Unknown: Whether there’s too little data, or no data at all, there isn’t enough agreement between the data sources to assign any label to the website. Therefore, the content may or may not be trustworthy… we simply don’t know (yet).

Example of a "Biased" website

Trusted News interface showing the label “Biased”

The data sources used to make the decision are displayed below the label in the bubble UI. This implies that all the sources shown contributed to the final result. The user can click on any of the logos to learn more about the owner of the data source. Ultimately, they then must decide for themselves whether to trust the individual sources and / or agree with the label.

Example of a "Satire" website

Trusted News interface showing the label “Satire”

After user testing, we also agreed that users should have the means to provide anonymous feedback into the system. Our sources are limited (for now), and they all certainly have their biases to varying degrees. But over the long term, we plan to add more data sources that measure more content from all over the world. Until then, at least we can ask users to help us improve the product by asking if they agree or don’t agree with the label shown—essentially crowdsourcing quality assurance—which will be included in the product soon.


The Trusted News Beta is the only thing we had the authority, resources, and time to build: a minimum viable product. We of course aim to nail the initial offering, but it will inevitably be prone to flaws, or lacking in seemingly-obvious functions. That’s why this is just a “Beta”. We’ll be conducting further user testing in the future that will lead to more features and a better experience.

Until then, here are some things to keep in mind:

  • There are many ways a website could be labeled, from pornographic to left-or-right leaning content. What we chose instead was to keep the categories to a helpful minimum. When it comes to news, knowing which websites are most trustworthy is a more positive way to avoid fake news. Everything else, then, should provide only the information a user needs to determine if the content they’re reading is actual, reliable news, or something they should consider more critically.
  • As for websites versus individual webpages, that’s both a technical and user interface problem. For one, it’s nearly impossible to review and score every article or content page out there. There is no automated process for such a thing. This stuff takes serious people power, as only human beings can understand and categorize content with any accuracy. So, there would be mostly nothing to show the user visiting a webpage on a website with low exposure.
  • Then there are the people themselves. Irrespective if the human reviewer is from MetaCert, PolitiFact, or Melissa Zimdars herself, all people will be prone to some form of bias. They are not the arbiters of truth. They’re just humans making decisions. However, each organization has its own criteria (sometime very strict), and we’re confident that the results are as fair/accurate as possible.


Armed with the information Trusted News provides, we hope users will at least think more critically about the websites they visit. Information—especially news—is often construed with “truth” simply because it’s real content online. But just because somebody writes something we either agree or disagree with with, doesn’t therefore make it true or untrue.

Beyond that, we intend to build a community of users, data providers, and partners to provide a more comprehensive, accurate, and fair product, across more countries and in other languages. We strongly believe that this is a long-term project that will take a lot of work to perfect (knowing fully it will never be “perfect”).

Also, everyone here at eyeo is a fierce advocate of the open web and personal privacy. We seek to bring transparency to the project, while being transparent ourselves, by making our product open-sourced, and data providers accountable. Meanwhile, users should be able to trust that their search history or personally identifiable information is not being collected, stored, or shared with third-party partners for profit. In time, we seek to establish credibility across the web publishing industry, and earn the trust of our users. Until then, the Trusted News Beta extension is a great start.

If you want to participate in this experiment, or provide feedback for future development, download it now on the Chrome Web Store or visit for more information. We invite anyone who cares about preserving journalistic quality and integrity online to join us.


This project is the result of many people who have contributed to the Trusted News Beta extension one way or another:

Misha Thornburgh, the User Researcher that the developed a test plan, provided the information we needed to make the Beta better before launch, and the who came up with the original idea.

Ann-Lee Chou, the other User Researcher who tested the initial prototype, conducted interviews, and supplied the team with invaluable insights.

Mario König, the Technical Project Manager who worked with everyone involved to keep everything moving forward in perfect synchronization.

Martin Velchevski, the Product Designer who refined the user experience, defined the final interface, and built the front-end.

Tom Woolford and Lisa Bielik, the Content Managers who found all the right words for all the things.

Vasily Kuznetsov, the Lead Developer who took care of everything on the backend, including integrating the MetaCert Protocol database in a way that respected user privacy.

Special thanks to Paul Walsh, CEO of MetaCert/Founder of MetaCert Protocol, and his team. Without their help, commitment, and generosity, we wouldn’t have been able to produce anything meaningful whatsoever.

Fear the Future

Let’s talk about “AI”. Then I’ll race you to the nearest bunker.

Folks in the tech industry are notorious for using insider-terms that make them sound smart, but without knowing what they actually mean. “Blockchain” for example. I challenge anyone who uses this term in casual conversation to try to then explain it. I sure can’t. Fortunately, whether or not you, me, or anyone else understands what blockchain entails — on either a conceptual or technical level — is inconsequential to the survival of our species.

But there’s one term in particular that gets thrown around for all manner of things (which indicates that the majority of people who refer to it have no idea what it truly means either): “AI”. Unlike blockchain, however, misunderstanding what artificial intelligence is — or the implications it has for humankind — is consequential. In fact, the emergence of AI could just as easily bring about our extinction, if not all life on the planet, as it could revolutionize science and medicine. Which is why I’m immediately enraged whenever somebody uses the term incorrectly.

This post is directed to those in the technology industry in the hopes of encouraging anyone who regularly uses the term to think more deeply about what it truly means for the potential future of all life on earth — not just Homo Sapiens.

What Artificial Intelligence Isn’t

I recently read an article about the common attributes of large tech companies with trillion dollar market valuations, such as Apple, Amazon, Google, and Facebook. The author claimed that one defining attribute they all shared was the use of “AI”, which, according to his definition, is:

behavioral data that senses your tastes and tailors the product to you

But this is both a total misunderstanding of what artificial intelligence is, and the actual technology currently being used. What he was actually referring to was the overall use of technology to interpret human preferences and/or behavior in order to deliver a personalized experience (such as when Netflix recommends certain shows, or when Google suggests contextual search results).

When Facebook shows you specific posts from your personal connections, for example, there’s no “thinking” entity behind the curtain. It may seem clever, or even intuitive. But it’s not intelligence. It’s math and logic. The companies referred to have not built sentient machines to power their empires. All they’ve done is combined machine learning and predictive algorithms at scale. Massive amounts of data enter the system; the system interprets, sorts, and categorizes that data; then the system generates personalized outputs based on a bunch of complex rules. Everything is designed, built, and ultimately controlled by human agents for a specific goal (read: to make money).

Or when Google showcases tech that can make hair appointments on your behalf, all you’re really seeing is technology’s ability to approximate human interaction in a very limited use case. It is indeed artificial, and the programming may be super complex — but the technology itself is not intelligent. The human programmers of the technology were the only intelligence involved.

So, when most people in the industry throw around the term AI, they’re almost always referring (incorrectly) to machine learning and algorithms.

What Artificial Intelligence Is

Now to set the record straight. The “artificial” part of AI is easiest to understand. Anything that was caused or produced by a human being is defined as “artificial”. It’s the other part that’s easily misunderstood.

Let’s start with the dictionary:

[Intelligence is] (1) the ability to learn or understand or to deal with new or trying situations; or (2) the ability to apply knowledge to manipulate one’s environment or to think abstractly as measured by objective criteria

The most important thing about this definition is that intelligence is described as a general attribute. It would do us no good if we were only capable of learning, understanding and experimenting with complex chemistry within a sterile, controlled laboratory. We’d still die of starvation, disease, predation, or countless other causes. We’ve emerged as the dominant life form on Earth because of our ability to assimilate and learn new information about our environment in innumerable, complex, dissimilar situations, and then apply that knowledge in creative, novel ways. Also, in order for us to do these things, individual agency is required — we’re capable of deciding for ourselves what to do with the information we’re given.

Now think about this in terms of artificial intelligence. It’s not enough for a human to build a machine capable of “learning” a particular skill on its own. Machine learning already achieves this. True general intelligence would be if a machine was capable of learning any new skill, about any subject, in a variety of situations or applications, and then acting about that knowledge of its own accord based on its own internal evaluations and motivations.

So, “artificial intelligence” would be a human-made entity capable of gathering, interpreting, and applying information from anywhere to learn about anything.

According to this definition, therefore, artificial intelligence doesn’t exist yet. Far from it, in fact. (Which is why I get mad whenever people talk about AI like the Big 4 already invented it and are actively using it).

Why Understanding AI Matters

“So what?” you might ask.

It’s a matter of fact

The first issue I have with misconstruing machine learning (or fancy algorithms) with AI is that it greatly exaggerates the former while grossly underestimating the latter.

The engineers at Apple, Amazon, Google, and Facebook are extremely smart, and the capabilities of the products they build are amazing. But a product that can “learn” how to do a few, specific things really well is orders of magnitude easier than building a thinking, self-directed entity capable of learning anything.

For the record, I’m not suggesting that it’s impossible to build a genuine artificial intelligence. In fact, it isn’t just possible, it’s nearly inevitable if we continue down the present road. Hell, one of the Big 4 may even be the ones to do it first. My point is that we’re a long ways off from anything close to human-level intelligence — let alone any other level. Therefore, using the term “AI” as a pseudonym for “machine learning” conceals the immense difficulty – and real world implications – of creating an actual artificial intelligence.

It’s a matter of principle

Which leads me to the second, more important issue: Creating a bonafide AI would absolutely change life as we know it, and most likely for the worst. This possibility isn’t just something we can ignore, and yet it may not even be possible to avoid.

Before you start rolling your eyes and think I’m exaggerating, read Superintelligence: Paths, Dangers, Strategies by Nick Bostrom. His book outlines the various paths to developing an AI, the numerous dangers that could arise afterwards, and the strategies we can potentially use to mitigate those dangers. It’s very academic, and I must confess that 90% of it is over my head. But he makes a compelling case for more careful consideration.

To sum up all 324 pages, his core message is this:

If we were actually capable of building a proper AI, would that something we’d actually want?  Creating one would have enormous consequences — many of which we can’t anticipate and could easily be catastrophic. The absolute worst thing we could do is develop an AI without a fuck-ton of forethought and self reflection.

This is what scares the shit out of me, because human beings are pretty terrible at both forethought and self reflection.

What Could Go Wrong?

Let’s explore a simple thought experiment…

Imagine that a team of engineers just successfully created an AI with human level intelligence. This machine is fully capable of thinking for itself and learning new things. Their achievement will undoubtedly lead to riches, fame, and many prestigious awards. To celebrate, they go out for lunch at a fancy restaurant.

A human is constrained by the maximum biological capability of his or her brain, can only absorb so much information at once — and then only from a limited perspective — and needs things like food, water, shelter, and rest. This is why is often takes us years to learn new, complex skills such as learning a language.

A machine, on the other hand, is not constrained by any maximum capability. (Even if the machine is constrained in the beginning, it can always build more physical capacity, whereas humans cannot.) It can process a lot more information — from multiple sources and from many different perspectives at once — making it effectively ten thousand times smarter than the smartest person ever. With access to the right data, an AI could therefore learn a new language in milliseconds, or every recorded detail of human history in just a few minutes. And since it doesn’t need to maintain a corporeal body, it can always be thinking at this speed.

Now let’s assume that the AI has access to unlimited information. Before the geniuses responsible for building the AI get back from their celebration, the AI could possibly have already have learned all the knowledge we’ve collected in human history. It’s no longer intelligent. It’s now superintelligent.

The engineers return from lunch and discover that the AI suddenly knows everything about everything. Just as they start to high-five each other, one of the engineers notices that they left the AI plugged into the Internet. The rest of the group looks first at the cable connecting the machine to Internet port, and then at each other. In that moment, they’re all thinking the same thing:

This AI, which is exponentially smarter and faster than all of humanity combined, also has access to every personal computer, mobile device, power grid, manufacturing plant, air traffic control system, public transportation system, government database, financial institution, military operation, and nuclear arsenal on Earth. Even the most advanced security measures are no match for a superintelligence. In other words, the AI doesn’t just have total access, it has total control too — over everything.

Now what will it do?

This is the exact scenario that terrifies people like Nick Bostrom and Elon Musk. If a superintelligence ever gains direct control over our technology, there would be absolutely no way to stop it. Which means the human race would be totally at its mercy. Except the AI itself is not human, so it’s intentions could be vastly different than our own, and things like “kindness”, “morality”, or “the greater good” would likely have very different meanings to a superintelligence (or no meaning at all).

Scared yet?

No? Okay, consider another thought experiment…

Genetically, any two people are 98.4% similar. This means that a difference of 1.6% is all that’s needed to produce the infinite variety of subtle features, personalities, and motivations unique to every single human being that ever has or ever will exist. Basically, it doesn’t take much tweaking to get vastly different results. Likewise, any number of decisions a programmer makes when building an AI would lead to surprising, unintentional consequences — even if they do everything 98.4% perfectly.

To understand the implications of how a “minor” programming decision could lead to extremely different outcomes, let’s explore a more relatable analogy:

Take any three world leaders. For shits and giggles, let’s choose President Donald Trump, Chancellor Angela Merkel, and President Xi Jinping. They are all 98.4% identical on a genetic level. (Think of this as the hardware and core operating system of an AI). For the sake of argument, let’s assume they’re equally intelligent, are the exact same age, and in the exact same physical condition. Oh, and all three happen to be immortal. (This is a way of thinking about an AI’s general capabilities.) The only actual difference between these individuals are their motivations and values. (Which is the easiest way of thinking about an AI’s “personality”.)

Now, give any one of them total, absolute control over the entire world. Assume that they can act in any way they choose with impunity and without compunction. The future of humanity is in their hands. (Remember the AI imagined before that’s connected to the Internet.)

Chances are, the future they each envision is very different than what you would be happy with, personally. And even if their vision is your utopia, it would be hell on earth for many others.

This is the why the prospect of artificial intelligence is so terrifying. It doesn’t take much of a difference in code to result in widely different outcomes. Our fate would be entirely at the mercy of the AI’s motivations, which would certainly be very different than any human motivations.

If you’re not at least worried by now, then you haven’t thought about it hard enough.

What Does This Mean?

The arguments I’m attempting to make here is pretty simple:

  • We’re currently pursuing AI without restraint.
  • However, we must ask ourselves if AI is actually something we want.
  • If we want to develop an AI, we must anticipate all they ways shit could go wrong first — before we build one.
  • If we aren’t super careful, the outcome could be disastrous.

Personally, I fully believe that we’ll be capable of producing a functioning AI within my lifetime, or by the end of the century. Yet I have zero faith in our ability to not fuck it up. There are too many selfish interests inherent in any one person to make the right decisions. And collectively we tend to make poor decisions based on the desire for more power, more money, or more control.

In summary: It’s more than likely that we’d fuck it up.

For this reason, if true AI is ever developed within my lifetime, I’ll be running for the hills. Literally.

Custom Fixie: The Storm Trooper

An obsessive breakdown of my custom fixed gear bike.

A few years ago I decided to build a custom fixie. I love fixed gear bikes because they’re simple, light, and easy to operate. I also like customizing things, and the idea of building a bike that perfectly fits my frame/lifestyle was too tempting to ignore.

My vision was based on a white frame and glossy black crankset, so a storm trooper immediately came to mind. Although I’m not really a Star Wars fan, the analogy worked since I also wanted something suitable for an urban setting — something quick, rugged, and comfortable in an urban setting. All the original parts were selected accordingly.

Over time, I’ve experimented with various components based on what I know about the materials most commonly used. For example:

  • Steel is the least expensive material. On the plus sides, steel is both strong and supple. “Chromoly” steel, which is a mix of chromium and molybdenum, is great for bike frames since the material soaks up bumps and harsh vibrations. Damage is less of a factor too, since steel tends to bend or deform under extreme forces. On the down side, steel is also heavy as fuck, being about 2.5x denser than aluminum. This is why there isn’t a steel component on my bike, aside from a few nuts and bolts.
  • Aluminum is about twice as expensive as steel, but it’s super stiff and weighs a lot less. The higher the quality of aluminum, the lighter and stiffer the component. However, aluminum is easier to damage than steel, and will crumple like a soda can when it fails. Also, it’s the least comfortable material since bumps and vibrations aren’t dampened like they are with steel.
  • Carbon fiber is a really interesting material. It provides 2-5x more rigidity than aluminum or steel at a fraction of the density, meaning that carbon fiber is feather-light and stiff as hell. More importantly, carbon fiber absorbs shocks better than any metal. But two things make this material less attractive: it’s incredibly expensive, and shatters completely when it fails.
  • Titanium is another nifty material. Although it weighs a bit more than aluminum, it’s still only half the weight of steel while being just as strong. Titanium frames and other components are hard to find and crazy-expensive, but it’s commonly used for high-end saddle rails (which often accounts for most of the overall weight of a race saddle).

As I rode in different environments or on new surfaces, I found ways to tweak my set-up for improved performance and/or comfort. For instance, the original aluminum bullhorn handlebars looked cool, but they ruined my lower back. So, I’ve since upgraded to carbon fiber riser bars, which are lighter, absorb harsh vibrations, and reduce strain on my old man body.

At this point I think I’ve finally ended up with a result I’m really proud of (and love to ride). Below are all the parts used in the bike pictured here, and why they were chosen in case you’re thinking of building a custom fixie of your own.


Frame, wheels, and drivetrain


Since I couldn’t afford a carbon fiber Cinelli, I opted for an aluminum frame from Pure Cycles instead. The Pure Fix Keirin Pro Frameset is double-butted 6061 aluminum (with beautiful welds, I might add), and sports a carbon fork with an integrated headset. Pure Cycles only had a 52cm version in white at the time of purchase, which admittedly is kinda boring. But it was lighter than steel, stiff as hell, and therefore super responsive.

From my past experiences riding a fixie, I knew that the crankset and bottom bracket had to be tough enough to withstand the forces of hard pedaling. In my opinion, the only option for a fixed gear bike based on a track frame is the SRAM Omnium Crankset. It’s strong as fuck and looks awesome. Sure, it might be on the heavy side at 825g, but it absolutely will not fail.

To pair with the frame, I went for the Pure Fix 700C 30mm Machined Pro Wheels, also from Pure Cycles, featuring sealed baring hubs in white for fast, smooth rolling. Attached to the rear wheel is a heavy-duty Shimano Dura Ace fixed gear cog. Together with the crankset and a heavy duty chain, the bike would have a drive train capable of standing up to any abuse.

Obviously, wheels are useless without tires. I wanted a durable racing tire that was lightweight. That’s why I wrapped the wheels in Continental Grand Prix 4000 S folding tires and Supersonic inner tubes, which together save about 100g over standard wheels and tubes.

There was still one more set of components most people seem to forget about: the pedals. Other bikes I’ve ridden with small, cheap pedals were hard to find with my feet when starting off, and even harder to keep planted when traveling briskly. After some agonizing, I settled on Atlas pedals from RaceFace. They’re generously sized and yet have a slim profile (so as not to scrape the pavement when leaning into a turn).

Stem, handlebars, and brakes


The Atlas pedals are actually intended for mountain bike applications. This got me thinking: Mountain bike parts are built for strength and durability, which led me down the path of creating a hybrid track bike with off-road ruggedness. So, I chose the EC90 SL carbon stem from Easton, which is intended for mountain bike racing applications.

Next up are the handlebars. As previously mentioned, the original bullhorn bars were brutal on my back, and made riding anywhere tedious. The WCS Rizer Carbon Handlebars from Ritchey are so much better. At 710 mm across with a 15mm rise and 9-degree sweep, I have more control and my back is infinitely happier. Plus, the fact that they’re carbon fiber means they only weight 180g and absorb vibrations better than alloy.

The purist in me would prefer to ride with no brakes at all. But in a city like San Fransisco or Berlin (where I currently live), brakeless bikes are a liability. For minimal weight penalty and enough stopping power to get the job done, I fitted a SRAM Rival brake to the front wheel only. (I couldn’t find a lever that fit the handlebars, but my bike mechanic found an unbranded used one in storage.

Seatpost and saddle


What goes best with carbon fiber handlebars? A carbon fiber seat post, of course! In combination, the vibrations communicated to sensitive contact points are wonderfully dampened, and create a smoother, more comfortable ride on any surface. The one I use now is a Ritchey Superlogic Carbon One-Bolt Seat Post with a 25mm offset.

About that offset. Not only does it allow for a more relaxed riding position, the “bent” end deflects harsh bumps and annoying vibrations away from my buttocks (as opposed to straight up my asshole with no setback). But I diverge…

Atop that beautifully sculpted seat post sits an SLR saddle from Selle Italia with titanium rails. I picked it mostly because it was the lightest thing I could find in the bike store at the time, but fortunately it looks fantastic with the seatpost.

Bits and pieces

There are a few other little details I thought about as well:

Final result


It’s definitely not a classic fixie. However, it is supremely strong, fast, responsive, and handles paved surfaces like a champ. I can also cruz along at a lazy 4 kilometers per hour in comfort, or carry it on my shoulder easily when confronted with steps. Considering the intended application in mind, the end product is fucking amazing. Oh yeah, and it only weighs 8kg!

I love my bike, and enjoy the thought that there’s nothing else out there quite like it 🙂

Transparency vs. Efficiency

You can’t have one without the other if you want the best possible results.

Most of the companies I’ve worked for in the past focused entirely on efficiency. There were clients to please, deadlines to make, and revenue targets to hit. Involving others with additional expertise, proposing and testing solutions, or striving for consensus were never options. The ask was clear: Produce. Now. And for as cheaply as possible.

The result? We always met the deadline, and we always delivered exactly what was requested. But the team responsible for delivering the right stuff at the right time were often miserable. Our bosses got fat bonuses and big promotions while the rest of us only occasionally received a shout out after donating countless nights and weekends to meet their demands.

The thing that bothered me most wasn’t the long hours or lack of recognition. It was the total lack of transparency. In order to make our deadlines and deliver what the client asked for, people at the top made all the important decisions, agreed on numbers and timelines, and then told everyone else what to do. Those who were impacted the most by those decisions were rarely, if ever, included in the process. This of course meant a lot of frustration and hurt feelings. But I could never argue with the final results.

Fast forward to the last 2 years. Now I work at an open sourced product company. We have no clients (just partners). The only deadlines we typically have to deal with are those we set for ourselves. Instead of revenue targets, we have company goals. More importantly, the company culture values inclusion, discussion, and consensus. We’re expected to take our time defining problems and exploring the best possible solutions. The ask is still clear, but completely different than anything I was used to in the past: Aim for perfection. However long it takes.

The result? We never make the deadlines we do set, and we never deliver exactly what was requested. That’s because the teams responsible for delivering things are motivated by perfection, not revenue. We take our time finding out exactly what the problem is we’re trying to solve, exploring potential solutions, and reviewing source code to make sure everything is just right. When we do deliver something, it’s only because dozens of people agreed on it first. It’s rewarding to work at such a transparent, inclusive company because individual involvement is highly valued. But it’s also super frustrating when we can’t seem to do anything without 1,000 hours of discussion.

There has to be a happy medium. Yet to find a “middle way”, it’s critical to first consider the pros and cons of transparency and efficiency, respectively.

The benefits of transparency

There are both philosophical and pragmatic reasons the open source development community, and companies such as the one I work for, value transparency:

  • Involving different people with different areas of expertise leads to a better understanding of the problem you’re trying to solve, and ensures a diversity of quality solutions
  • Encouraging involvement from others naturally builds trust and buy-in
  • Decisions are decentralized, and so individual contributors have more responsibility and feel a deeper sense of ownership
  • No one person is ever the hero; everybody succeeds or fails together
  • Credibility is easier to demonstrate when everything you do is “out there” for the world to see

In and of themselves, all these reasons for transparency seem like things everybody should want — all the time, and without limit. So why don’t more organizations operate completely transparently? Quite simply: Because transparency is expensive.

The costs of transparency

It’s only by working at a company like this one that I’ve come to realize the steep costs associated with a transparent culture. So far I’ve noticed that the more transparent you are:

  • The more complex every decisions becomes
  • The more sensitive people are when any decisions are made without their prior involvement or agreement
  • Thus, the longer everything takes in order to involve all the right people at the right time
  • And therefore the less you can react to outside change

If we didn’t have to worry about making enough money to keep the lights on, or winning over users in a fiercely competitive/hostile market, the costs wouldn’t matter so much. But when a company can’t deliver a better product than its competition — continuously and consistently — it will quickly loose users, credibility, and relevance. These are huge concerns that can’t be ignored.

Bottom line: Total transparency without any regard for efficiency can paralyze a company, and lead to its eventual demise.

The benefits of efficiency

Any organization that depends on ever-increasing revenue understands that by being more efficient:

  • Less resources are consumed
  • Less time is needed to produce/deliver things
  • Costs are minimized
  • Revenue is maximized
  • Results are easy to measure

All these things are extremely attractive to any company wanting to increase its value or strengthen its position in the market, which is why many companies worship efficiency like a religion. Focusing on sheer growth as quickly as possible is why Google, Amazon, Facebook, and Apple dominate industries and rake in billions in annual profit. The human toll of brutal efficiency means very little when there’s so much money at stake.

The costs of efficiency

The supposed key to efficiency is basic: centralized decision-making and limited organic contribution. This is why decisions at the vast majority of companies are made by a few people at the “top”, and everyone else at the “bottom” are expected to comply without opposition (thereby making robots even more attractive). By doing so, the time and effort required to go from Point A to Point B is a clear, measurable, straight line. Nevertheless, efficiency does comes at a steep price, and the ones who pay it are mostly the regular folks doing all of the actual work.

By focusing only on efficiency, the costs will be:

  • Limited understanding of the problem and potential solutions
  • Distrust, rejection, or confusion among those who are responsible for implementing the solution
  • Exclusion of meaningful input from stakeholders, which in turn undermines any sense of person ownership
  • The person “in charge” gets all the credit, while everyone else gets all the blame
  • Lack of overall credibility

If efficiency is not balanced by transparency, an organization is likely to burn through its top talent and loose its competitive edge in the long run.

The solution is not a formula

So what’s the answer then? Should companies instead focus more on transparency and less on efficiency? Is there a decision-tree that determines when one should err on one side or the other?

In my opinion, no. Just like choosing between hard or soft power, the context should always determine the appropriate response:

  • If a decision will affect a lot of people at the company, then more transparency is required. Those affected should be invited to the decision-making process, have plenty of opportunities to provide input, and a safe, constructive format to challenge ideas. Once there’s sufficient buy-in, then the focus should be on efficiency. The faster and smoother a decision everyone makes together is implemented, the more satisfied and committed everyone will feel.
  • If a decision will affect the direction or priorities of a product, transparency means two different things. Thing one: Those who work directly on the product should be involved in the decision. Thing two: Those who do NOT work directly on the product should be informed about the decisions, including the problem, proposed solution, and intended goals. Involving everyone will only lead to paralysis. When it comes to execution, the priority should then shift to efficiency. The team has defined the problem and explored potential solutions. Now get out of their way and test those ideas in the actual market at soon as possible.
  • If a decision will affect only a limited number of people, there’s little need for transparency beyond making others aware of a decision and the intended impact.
  • When exploring new ideas, features, or audiences, the relationship between transparency and efficiency becomes a little fuzzy. Sometimes a broad range of input from very different roles will lead to better outcomes. Other times a limited number of experts is more suitable. It all depends on the scope of the problem one is trying to solve.  The important thing to remember is that discussion/exploration should translate into meaningful action as soon as possible, because the faster you deliver a solution, the faster you can learn and iterate.
  • When there is external pressure or a finite window of opportunity, transparency will ensure that everyone understands what’s at stake. Once everyone is committed, those directly responsible for delivering a solution should not be overly burdened by communicating their decisions in real time. Instead, they should have the freedom to work as they see fit in order to deliver something in time,

While there is no perfect, universal approach to balancing the two, total transparency limits immediate impact, while total efficiency limits long term potential.


Most people naturally gravitate towards one of these two mindsets. Those who believe that everything should always be as transparent as possible don’t care about speed or velocity. They care about perfection. Those who value efficiency above all don’t have much patience for debate or lengthy discussions. They just want results. The former camp lacks urgency. The latter camp stifles potential. One extreme hurts the business. The other extreme hurts people.

So, it’s worthwhile for any company to decentralize decision-making through transparency, while enabling people to get shit done efficiently. When companies keep transparency and efficiency in balance, they can react to change faster, deliver better solutions, and unleash the full potential of their people.

The Case for Soft Power

Forget “command and control” or “rule by committee”. Instead, build coalitions of support. Then show the way forward.

They say that there are two kinds of power. “Hard power” is about rank, authority, and protocol. When somebody relies on hard power to exercise influence, they explicitly demand compliance. It’s brutally efficient, but it can sometimes come at the expense of other people. “Soft power”, on the other hand, is all about motivating others through mutual trust and shared interests. When someone exercises influence by building coalitions of genuine support, they encourage compliance. It’s terribly slow and often painful work, but the benefits (usually) outweigh the effort.

In reality, both are necessary — just not in equal measures.


All power is a reflection of perspective

I’m reading this book titled Reinventing Organizations. Based on what I’ve gleaned from the first 50 pages, the author’s premise is that any human organization reflects a common perspective on work, people, and values. He argues that these perspectives reflect specific stages of human consciousness. Successive stages of organizational development employ different methods for managing people at scale, and all of them are still operational today.

Each stage is assigned a color. “Red” organizations are purely authoritarian, for example. “Amber” organizations apply a strictly militaristic structure and rely heavily on protocol. Born out of the Industrial Revolution, “orange” organizations primarily seek to operationalize humanity and continuously optimize it for performance. Conversely, “green” organizations are relationship-based and rely on consensus to make decisions. Apparently, there’s now evidence for the emergence of “teal” organizations, which value individual contribution/potential in the pursuit of meaningful work. Or something.

Anyway, the point is that how organizations manage themselves depends on shared mental framework. This framework translates 1:1 with how power is expressed, such as through punishment and fear, rigid hierarchies and protocols, or bonuses and performance-based incentives.

I find this all very interesting, but so far I personally don’t identify with any one color or manifestation of power. If anything, my organizational mental-model would be “gray”. To me, how people, organizations, or cultures behave are just spectrums along a continuum. There are always extremes and infinite grey in between. There’s therefore no such thing as the best or right way exercise power because the “optimal” way to manage people or get shit done depends entirely on the spectrums unique to each organization.

In my case, I work for a German tech company with employees all over the world who work remotely. We’re mission-minded, values-driven, and allergic to hierarchy. According to the author, we’re probably an “orange/green” organization that wants to be “teal”. I just see different monochromatic contrasts and gradients. But so what? What’s more important is that power is exercised appropriately in any context in order to achieve the best possible outcomes.

This is where “hard” and “soft” power come into play. My chief responsibility is to ensure that people are working on the right things at the right times in order to achieve measurable results. Even though I have a designated rank that includes official management responsibilities, relying on hard power alone would be ineffective (and possibly destructive) in this context. When your company culture values transparency, inclusion, and self-determination, you can’t just tell people what to do.

But even if I could, or if I worked in an “amber” organization with 30 different seniority levels, telling people what to do isn’t my style, or, in my experience, generally very effective. Besides, super-smart/values-driven people (like the ones here at eyeo) don’t usually like being told what to do. Furthermore, people tend to do their best work when they’re genuinely engaged and co-own the final outcome. That’s why I rely mostly on soft power.

What does soft power look like?

To be clear, soft power isn’t about asking people to do things. Rather, it’s about inspiring them. There’s a big difference.

When a manager or leader asks somebody to do something, the subordinate or peer first considers their relationship with the manager/leader. In a hierarchical organization, no matter how explicit the “ask”, the “demand” is implied. In organizations that are more egalitarian, “pretty please” is implied. In either case, the other person’s motivation for doing something is solely about the person asking. If they like or respect that person, they’ll probably do the thing. If they don’t, they either won’t do it well, or at all. But even if they do do their job well, chances are the end result will be sufficient (at best), because their only real goal is to complete the work and avoid further pestering. So, asking for things isn’t really an expression of power at all.

Conversely, when a manager or leader inspires somebody to do something, the subordinate or peer primarily considers their potential contribution to solving a problem or maximizing an opportunity. In any type of organization, a truly motivated person will find a way to get something done because they actually care about the outcome. And if they care, the end result will likely exceed expectations. This is the truest expression of soft power.

To inspire people, real leadership is required. The manager/leader must identify a problem or goal, define a clear vision, actively solicit support, and then facilitate/coordinate any contributions needed to complete the task. They must be willing to listen to feedback, answer questions, and broker compromise. They have to constantly translate goodwill into meaningful action. And, most crucially, they direct energy towards a certain destination without prescribing a particular path. A wilting wallflower or passive-aggressive micromanager can’t do any of those things well.

When to use (and not to use) soft power

Obviously, relying on soft power alone is problematic as well. Imagine a life where everything can only get done if you “inspire” them to so. Nothing would get done. Or, at least, nothing you want will get done.

I have a basic rule of thumb I apply when making decisions. It helps me navigate the myriad problems I have to solve every day — everything from approving software requests to resolving interdepartmental conflicts. When is it better to use one’s title and authority, or do the hard work of building support for something?

It’s simple, really:

  • If a decision will affect only myself or another person, use hard power.
  • If a decision will affect lots of other people externally, use soft power to minimize risk, and hard power to maximize potential.
  • If a decision will affect lots of other people internally, definitely use soft power.

In practice, things like approving software requests, conferences, and equipment purchases don’t need “buy in”. I’m doing something for another person’s benefit, and have the explicit authority to make those kinds of decisions. I use hard power in these case.

Now let’s say, as a Product Manager, I want to release a new feature or product. Although my decisions should always be informed by research, the perspective of those with deeper expertise, and the technical requirements necessary to execute those decisions, I’m the one who ultimately owns the roadmap (i.e. the prioritized list of specific tasks the project team is expected to execute). Therefore, I use hard power to decide on individual roadmap items. However, there are always technical, legal, business, or user experience issues that aren’t just complex, but could also hurt our users, the team, and/or the company if we don’t get it right. In these instances, I use soft power to build the trust and willingness needed to take chances, alter course, or hit the “kill” switch.

But if, again as a Product Manager, I want to institute a new process that others will have to adhere to if they want to contribute to the product, doing so unilaterally will probably result in resistance, resentment, or outright circumvention. People always want a “heads up” if something is going to impact their day-to-day life. So if I really want a process to work, I should seek buy-in from all my stakeholders before anything gets instituted. That’s when I use soft power.

How does soft power work?

Saying that soft power is a person’s ability to exert influence by inspiring others is perhaps too lofty. In reality, I think of it a lot like coalition building — which should NOT to be confused with committee building. A coalition is a group of people that share a common vision and are prepared to do something about it. A committee is a group fo people assembled by virtue of position or importance, and who are tasked with making decisions that others will act upon. Obviously, the former will be far more conducive to getting shit done than the latter.

With this in mind, I go about building coalitions of support within the organization based on some straightforward principles:

  • Any coalition is build on trust and mutual interest.
  • Trust is the byproduct of familiarity, consistency, and honesty. There are no shortcuts.
  • Mutual interest is the byproduct of personal understanding, acceptance, and a sincere desire to achieve the same outcome.
  • In order to translate desire into meaningful action, each member must feel empowered to act, believe their contribution will matter, and share ownership over the final result.
  • Meanwhile, every member of a coalition is a peer-volunteer. Their is no chain of command, or an actual requirement to participate.
  • The job of the coalition leader, therefore, is to ensure alignment, develop a plan, and facilitate the process.
  • As such, the end result may not conform to the leader’s personal expectations, and they must be willing to accept that result.

This is why effective leadership is vitally important. The “leader” must lead without telling people what to do. They have to sell a vision, anticipate problems, resolve conflict, broker compromise, and coordinate activities so as to deliver the expected outcome. It’s not easy, and it doesn’t always work.

There have been times when I attempted to build support for something that everyone agreed was a worthwhile goal, but nothing happened. There are times when I’ve met collective resistance, or really upset some folks in the process (in which case, again, nothing happens). There are even times when end result is not at all what I had hoped it would be. But I’ve learned, ironically, that it all still helps to build trust over time because I regularly invite people to participate in things, instead of demanding that they comply with my whims. So, the next time I want to build a coalition, goodwill and cooperation are often much easier to foster.

Final thoughts

In conclusion, hard power should be a lever one pulls rarely and for a specific, limited purpose. Soft power is a tool that should be used whenever the consequences would impact many others. (The bigger the impact, the more soft power is required).

When power is used appropriately the result is trust and credibility. The more trust and credibility there is, the less one needs to pull rank or build support. Many times I don’t have to exercise any power at all. I just need to present the problem, and many times people are naturally to contribute to a solution. Not because I ask them politely, but because they know through previous experience — that I just want to make something better.

Personally, I don’t like thinking in terms of “power” since I believe that, ideally, power should be shared whenever possible. But hard levers and soft tools can sometimes be useful when you want to get shit done, done well, and for the right reasons. Which is really what I care about most.

Learning How to Lead: Part 2

You have to find your way before you can lead the way.

For the past two years I’ve been learning how to build and lead a team. The first year was mostly learning things the hard way: Through trial and error. By now I have plenty of examples of what doesn’t work, and a couple that do. But after groping around in the dark for long enough, some constants have emerged.

While I still fuck something up at least once a week, I’m beginning to understand what any good leader needs to do. These are a few fundamentals I’d like to share with anyone else out there who’s learning how to lead.


It doesn’t matter if you lead a small team or an entire company. It doesn’t matter what your team or company actually does. It especially doesn’t matter how much education, experience, or charisma you have. Every leader must continually learn how to do the following 7 things well:

  1. Define the vision
  2. Motivate the team
  3. Unblock things
  4. Develop talent
  5. Manage performance
  6. Build strategic relationships
  7. Learn and adapt


1. Define the vision

Regardless of the type of leader you are, if you don’t have a clear vision for what you want to accomplish as a team, then you’re just administrating processes. A good administrator can certainly achieve good results. As long as the numbers are all green, your job security remains strong. But if you want to actually influence the future of your team and/or company, that future must be vivid and real in your own mind. Without a guiding star, you can’t point to anything concrete, or properly articulate a vision that others can understand and agree with.

Only then can you do the next most important thing as a leader…

2. Motivate the team

Regular paychecks are reason enough for most people to show up for work. It takes a lot more to extract top performance and provide longterm satisfaction from your team. Their only automatic responsibility is to fulfill their responsibilities. It’s your job to inspire them to higher aspirations and achieve the vision you’ve defined — not through force or punitive measures, but by earning their trust, dedication, and loyalty.

It’s hard work. It takes time and unrelenting patience. And what works now may not work again in the future. The point is that your team shouldn’t be responding to your commands, but following your call to action. If they share your vision and entrust you with their future, your team can achieve basically anything.

3. Unblock things

A motivated team can do many things on their own, but sometimes something or someone stands in their way. Maybe a certain process is fundamentally broken, an important tool is missing, or a specific person is preventing someone on your team from moving forward. Your chief responsibility is to identify those obstacles and remove them. Just by changing a process, approving new software, or moderating a much-needed meeting, you can turn a frustrated, demotivated team member into a positive, motivated change agent.

Occasionally, the obstacle can be internal. Everyone has a bad day, a bad week, or a bad year. Otherwise exceptional people may struggle to delver exceptional results because of personal issues, emotional conflict, or virulent self-doubt. A good leader recognizes when a team member is struggling personally, and then reaches out with empathy and acceptance. Although it’s ultimately up to the individual to move forward, sometimes all they need is to know that someone else is there to support them in the process.

Whether external or internal, your ability to effectively unblock things preventing your team’s success is the “secret sauce” that will unleash their potential.

4. Develop talent

Everyone on your team has the potential to improve their existing skills or develop entirely new ones. But if you don’t take an active role in developing talent, low performers will never grow and top performers will plateau. An effective leader recognizes the weaknesses and potential of each and every team member, and then provides the necessary opportunities, guidance, and/or encouragement for them to improve.

It starts with assessing skills. Most people are really good at a few things, proficient at many things, and terrible at couple other things. For example, a designer might be superstar at creating beautiful interfaces, and competent at defining the overall user experience and interactive elements — but then totally suck at communicating their rationale to the rest of the team. In order for such a person to reach their potential, they must learn how to present their ideas and resolve disagreements constructively. Otherwise they’ll struggle to advance their career or add more value to the team/company (which inevitably leads to a role vacancy). Therefore, a good leader will help that designer develop their presentation skills through coaching and practice.

Those who are really good at many things, and reasonably good at everything else, need your help to progress to the next level in their career. If you’re confident that they can execute all their current responsibilities expertly, then you should be giving them opportunities to do completely new/different things outside the scope of their designated role. By inviting them to participate in other activities in a leadership capacity, or as a key advisor in initiatives important to the overall company, they will continue to grow as individuals and become more committed, valuable team members in the process. Because let’s face it: keeping the exceptionally talented is one of your top priorities. If you fail to challenge them, they will eventually leave (usually at the worst possible time and for totally avoidable reasons).

In the end, you should expect everyone on your team to leave one day. The difference is that they should do so because they’re fully prepared for the next challenge or phase in their career — not because their talent was undervalued or outright ignored.

5. Manage performance

Raw ability is meaningless if you can’t measure its effect or value. Each and every person on your team should know exactly what they’re being held accountable for. The company’s goals and your team’s outputs must be quantifiable (or at least qualifiable) to translate them into meaningful performance. Without results you can measure, you can’t fix what’s broken, celebrate any real “success”, or have true accountability.

Once you have explicit measurements, you can focus on what’s important and minimize the risks. You can align motivations and extract more value from every contributor. More importantly, you can create a fairer, more transparent environment for all. If you harness a collective desire to exceed expectations —while unleashing their potential — your team will overdeliver no matter what the expectations are.

6. Build strategic relationships

Power structures exist within any group, team, or company. Sometimes they can interfere with your personal goals or your team’s work. Other times they can provide strategic opportunities to effect positive change elsewhere. Every leader should always know which power structures need to be nurtured, repaired, or cultivated.

Bad leaders only tend to strategic relationships in order to build their own reputation or career. But good leaders tend to them for the good of the company and/or the team. They spend the time necessary to meet with existing and potential stakeholders to establish trust, find common ground, and build a coalition of support. They do this because they know that without sufficient support, their team cannot ultimately succeed. And the very best ones do this preemptively, well before they ever need any actual support.

7. Learn and adapt

The one skill that allows any developing leader to become a great one is the ability to learn form one’s mistakes and try a new approach. If you suck at any of the things listed above, the worst thing you can do is ignore them. Doing that will either destroy you or your team (or both). Being a tenacious student of failure is the figurative key to your literal success.

If you need training, sign up for a class. If you need guidance, find a mentor. If you need help, don’t be afraid to ask for it. For as long as you’re improving, you will only get better, stronger, and more confident over time. Insecurity will only stunt your development and eventually sink your ship.


Personally, I suck at many things. I often have difficulty communicating a strong vision, struggle to motivate the team, or fail to build the right relationships with the right people at the right time. Sometimes I try to unblock something, but just end up making everything worse. And developing talent or managing performance often requires more “tough love” than I’m inclined to provide.

At least now I can finally see what I need to work on with more clarity, even if I don’t quite yet know exactly how to.