“Sunday Morning in the Mines” by Charles Christian Nahl (1818 – 1878)

An oil painting on canvas. Crocker Art Museum, Sacramento, California

The California gold rush of 1849 was significant event for wealth creation and technological progress. There were three phases in this revolution which determined wealth creation, and could be ranked by the difficulty of obtaining wealth.

Mining gold and the three stages 

1. Easy: Initially gold was found simply by looking at the surface level, being picked off by the first to come into the area
2. Medium: More sophisticated techniques like panning helped discover gold from streams of water
3. Hard: Capital was required to develop technologies which made it possible for the discovery of gold from more difficult places

The sequence of wealth creation in mining gold is exactly the kind of behavior that will be experienced in light of the decreasing cost of whole genome sequencing. While there are many potential applications of mining genomic information, the companies that exist today operate in the easy category. First order analysis exhibited by 23andme and Knome represent highly naive or simple approaches to making genomic data palatable - one for a consumer audience and one for a medical or research audience. Companies like DNAnexus exist to take very simple algorithms for analysis of sequence pipelines, basic visualization and make these tools available to more researchers for their use. This is simply repackaging and consumerizing existing approaches. 

The watershed moment is coming for Genomics

Genome sequencing is already undergoing a significant reduction in cost, but its watershed moment will come when we are able to migrate from expensive methods of sequencing (<$1000), which require taking samples to labs, to much lower cost sequencing that can happen remotely and do not take up a lot of space (>$100). Combining mobility in computing with mobility in sequencing will provide many compounding effects. This is very exciting to me.

Nanopores are the shovels

Fortunately, the enabling technology we are waiting for is nanopore sequencing. Two companies -  Genia and Oxford Nanopore - are going to be significant providers of infrastructure to enable others to build services more easily on top of genomic information. Continuing the mining analogy these are these companies are making shovels and customer engagement with these technologies will drive their continued evolution over time. Therefore these are key technologies to understand. 

In order to derive a genome sequence you have to read the exact composition of DNA and its component bases - A, C, T and G. Reading can be done directly (literally seeing the DNA; EM approaches like Halcyon Molecular and ZS Genetics are representative of direct sequencing), or more commonly indirectly, by determining the indirect presence of the sequence of bases (A, C, T and G) through a secondary chemical reaction.

Nanopore sequencing exists in the secondary reaction category where threading a single stranded DNA sequence through an artificial protein channel - the nanopore - exposes the bases. Depending on the base change the ionic flow and therefore changes the current passing through the membrane. The resulting current for each base allows us to indirectly derive the genomic sequence. 

Nanopore sequencers will be smaller because nanopores themselves are small, and as semiconductor coupled nanopores can be combined with cheap mobile computing, and wireless connectivity allow for reading of samples, as well as generation of data in a small package. This is a desired outcome, but portability and cheap sequencing will drive nanopore sequencing to be the breakout technology of genomic mining. 

Shovels need fertile ground for exploration

So with cheap sequencing where can we pan for gold? Panning is a suitable analogy for the next phase. Sequencing generates data, but the origin of the data is where value is created. One of the key lessons from starting Quid is that to build a valuable company one needs to have unique data and a unique methodology for panning for gold. Proprietary data and proprietary algorithms for transforming raw sequence data into valuable molecules for identification, and their validation is key to finding gold. 

Proprietary data comes from the population one chooses to sample. Complexity in deriving value from genomics is proportional to the complexity of the organism. Therefore the first phase of panning will start with simpler organisms like viruses and bacteria before moving up the chain to ourselves. There are many valuable populations to sample genomic information from. One example, is in finding new drugs, by sampling the natural diversity of molecules in soil. Some of our most significant drugs like pennicilin are natural molecules. Panning for drugs is already seeing applications of natural discovery - Warpdrive Bio is a company leading the way, with a trailblazing partnership with Sanofi. Sampling the genomic diversity of the ocean, or the many bacterial populations within us - the Microbiome- are fertile opportunities for mining and discovery. 

How fine be thy sieve?

However, just like panning, filtering the data intelligently, and applying techniques to transform a messy sample into an understandable result is key. Metagenomics is the application of statistical learning techniques to determine individual sequences from a sample that contains the fragments of diverse organisms. Bioinformatic techniques to identify known molecules, and network analysis to identify the population of related molecules can be applied. I have some understanding of data analysis techniques from network analysis from my work at Quid, and so the application of these approaches in mining of genomic data is very interesting. Its also not just enough to determine important molecules computationally, but high throughput molecular biology, and some synthetic biology work can help characterize important molecules and truly seperate the wheat from the chaff. 

Polymathic collaboration

More broadly, mining and panning efforts will require the interdisciplinary collaboration of software engineers, computer scientists, biochemists and more applied practitioners such as medical professionals and those in the Pharma/Biotech industries. The potential reward for an ambitious group like this is discovering new drugs, treatments, and data which may increase our lifespan, fight disease, and in turn generate great wealth. 

I’m thinking a lot about the issues presented here, have thoughts or want to chat? email me on sumon [dot] sadhu @ gmail [dot] com  

May the Goldrush commence. 

p.s. I intend to go into the topic mentioned here with more technical depth in future posts. This is merely an introductory narrative. 

I was reminded by Andy Rachleff’s post of the perspective I’ve gained both from experiencing both successful execution as well as making mistakes. 

Experiencing success and failure while remaining cognizant of cause and effect is an exercise in being aware.  Perspective cannot be gained without exploration. Imagine painting or designing in the dark. Without looking, or even looking both left and right, up and down you cannot size up what you are about to make or transfer what you know to another work of Art.  Experiencing failure alone creates risk aversion, and suggests the absence of learning. Experiencing success alone, generates blindness about how you got there. Therefore a blended experience coupled with awareness is critical. 

A successful startup is an optimization exercise. Value is a function of market size, momentum and having the right team to capitalize on the market opportunity. Optimization of startup function is stage dependent. At the early stage the risk is not falling apart. Once initial momentum has been generated it is important to catch flight. Once a company is growing fast and has some success, long term value is created by continuing to build new products, without succumbing to the internal stagnation that can happen at scale. 

This essay explores dysfunction at the early (0-10 employees) and mid stages (10-100 employees) of a company. Arguably these are the most critical stages to traverse, and also I haven’t experienced the late stage yet with Quid so my experience at this stage is only conjecture. 

Early Dysfunction

The early stage is about not falling apart and catching wind of a market. So what are the main sources of dysfunction?

• Founders are misaligned on ambition, reactions and intentions. Founder misalignment happens on how decisions are made, because founders are disagreeing on something inherent in their personalities. A long term focused founder can be misaligned with someone who thinks too small. How founders react under pressure can also create misalignment, so when the going gets tough founders may react differently, one giving up while the other wants to persevere. Founder misalignments exist on levels of ambition, reactions to pressure and intentions (short or long term perspective). If you react the same way on all these fronts then you are aligned. If you have significant differences you aren’t. No two people are identical, but at least you can align philosophically. Founder misalignment can make it such that under signs of stress, the founders would rather not work with each other. If that is is the case, you can split a team even before you get going.
• Team has no momentum. In the early stage, you have to make momentum from a standing start. A team that doesn’t do that will not succeed. Momentum comes from having external deadlines, shipping and getting feedback, having focused releases, getting money or new users. Momentum comes from interacting with the outside world. The faster a team can be motivated by external forces and getting to a pattern of behavior of reacting and improving from the outside world. This means selling before you have a product. Or building a product and showing it off to users. Or setting a very public milestone like a press launch with a hard deadline to create pressure can be useful. My Y Combinator experience taught me how great a forcing function having tight deadlines can be. Creating a rhythm of reacting to cycles of momentum can help create a healthy habit. But generating momentum from a standing start is the responsibility of the leadership. Successful founding teams are like tornados of momentum - convincing external stakeholders to participate in shaping a vision into reality.
• Team is working on the wrong thing. This is the easiest to change if you can generate momentum from scratch and will work with each other through thick and thin. A market is a proxy for the number of customers, and the money in aggregate they are willing to give you. Starting with the wrong initial Market Size can limit your potential. It takes the same effort to work on very small idea than a big one. Depending on the ambition alignment of the initial team, as long as you start in a broad enough market initially, you can make your idea bigger. Starting in a small market can stunt your potential. There are hundreds of entrepreneurs who will not succeed because they are aiming for the wrong thing. Valuable ideas have proxies. E-commerce when it started had the proxy of physical retail. Sharing idle bedrooms had the proxy of vacation rentals and travel. Its easy to validate that something is valuable if it has an old world proxy. Being able to listen or proactively ask customers if this is valuable is a forcing function. Often this is tied to asking for money from customers.
• Team is undercapitalized: Runway allows for experiments. Runway, also gives you some buffer to add resources once things work. The more runway you have the more you can experiment. Having more money can also make you lazy, as you know you can run as many experiments as you want. Also more money can bring too much investment oversight. So the amount of money a company has at the early stage allows for the right incentives to be created. A team with less money is definitely motivated to either make money or in danger of not having enough to prove to raise more money. The right amount allows for experiments and resources to find a source of momentum in the business, and grow into it. Too little money increases the probability of failure, or can create incredible survivalist incentives. My Y Combinator experience with Snaptalent showed that we could build a functional product, and get to customers on less than $50k of funding.

Mid Stage

Assuming you have managed to avoid implosion during the early stage, you now have some revenue, or momentum, and a focused team that has overcome the initial uncertainty. The mid stage is about co-ordinating resources, and scaling human interactions to manage conflict, as well as doing more of the thing that worked by setting processes. The key to growing mid stage startups are in building a machine for generating revenue, building a team and a rhythm for momentum. If the number of potential units of dysfunctional behavior from one person is n, adding more people requires vigilance of n times n. 

• Team cannot manage and co-ordinate projects: Any company’s output can be broken down into distinct projects. Organizing projects, setting deadlines and standards, and co-ordinating output to completion is a skill that few people explicitly focus on. Companies like Asana and the use of individual productivity techniques like the Getting Things Done (system) help institutionalize execution. Even worse is a functional organisation that is simply working on too many projects. Cutting projects and evaluating effort spent are important aspects of management. Feature creep is common in product development, well on an organizational front the same phenomenon is known as project creep. Focusing output on the core value that the company is driving through effective communication of priorities as well as education throughout the organization is also a core skill. Defining the focus of the company and saying no, requires discipline and deliberate design. Hiring in project managers, operating leaders who can say no, or changing the culture through education of existing individuals. 
• Team forms political silos: A self correcting team is a functional one. A team that has information silos of negativity, or politics like cancer start to invade the organization and slow it down. Having clear information flow and trust up and down, which leads to corrective action is a must for a functional organization. Political or negative individuals with high influence must be fired or shown a path to transition.
• Team is not reshaped to suit direction: Over the journey of a company there is course correction that comes as a result of learning what is valuable to the market and what isn’t. Good companies are servants to their customers and love doing so. As a result, some parts of the organization aren’t necessary any more. Either those team members change roles and adapt, or have to be let go. For example shifting your focus from web to mobile means adapting to market conditions. If you have a team that was focused on the  web, and you cut the web product entirely you may not need all those engineers. You have to have them adapt or let them go. Similarly, in identifying problem individuals you have to offer them a way out or fire them. The team is an evolutionary thing with selection pressure being what drives value for the business. It isn’t uncommon to reshape the team a few times, or have attrition through forced or organic circumstances.

The principles of momentum, capital and market also apply in the mid stage as processes are built and revenue is created. 

The late stage
If you have got this far, the late stage is about capitalizing on your foundation. Enjoying the critical mass of people you have and continually improving. With continued effort hopefully one day you will be rewarded with a financial event worth telling your family about and looking back fondly at your hard work. 

This is the fun stage. This is where we are with Quid. 

Please comment if you think i’ve missed any big sources of dysfunction.

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Established companies have momentum. Therefore essential team members for a new company must be momentum makers.  

Momentum makers can create activity for a company from a standing start. Every early function that gets built within a company requires a momentum maker. New initiatives require momentum makers, so sustained progress is inherent to the proliferation of momentum makers within the organization. 

Momentum makers are like cardiac muscle. Their beat, makes the organization hum. As a group momentum makers are responsible for creating activity which allows the company to start having a rhythm independent of their effort. 

Arguably founders should be the ultimate momentum maker. Founders are supposed to be generalists but I would argue that the specialist skillset that a founder has is as a momentum maker.  If you are founding a company you should judge your (potential) cofounder’s ability to generate momentum from a standing start. 

Momentum makers are unfazed by solving chicken and egg problems.  When you have a product with no customers, they understand the art of leverage to persuade early customers to buy without others. This may be by faking social proof. Or by offering a discount, knowing that early customers will attract others at a higher price. Momentum makers can hire the first employees on the promise that something great is being built. Momentum makers can generate press by getting early outlets to cover them and using them as proof to generate a media frenzy. 

Momentum makers can also incubate key functions within an organization before they become departments. A full stack engineer who can build the first version of the product himself is a momentum maker. She is responsible for proving that something is feasible and can be delivered without the help of others. A sales person who can define what customers need, adjust the messaging of his pitch, and act with independence until finding the first customer is a momentum maker. 

A painting by The Renaissance artist Titian (artist) of the greek king Sisyphus rolling a boulder up a hill

Momentum makers have conviction. They are unafraid to act. With action, they are willing to adjust their output in response to the environment. The starting decision however requires conviction. Conviction allows momentum makers to define projects and priorities and reduce uncertainty through their decisions. 

Momentum makers are able to take undefined problems and define them creating clarity and purpose for those around them.

Momentum makers are the most important talent any company has. Are you a momentum maker?

Reposted from my Quora profile

Paintings by the artist Rachelle Reichert, see her work here 

This is an introductory post to publicly declare my interest in Synthetic Biology. This will serve to define the field, and my exploration, which is primarily focused on developing significant new business opportunities in this greenfield market. Having built and designed software, started venture backed companies the creator in me, coupled with my biochemical training is incredibly attracted to the idea of creating with biology and building technology and interfaces to make this easier. The consequences are untold for a new industrial revolution which will outshine anything seen in the past era of molecular biology. 

The first concept I will define is a redefinition of the term of parasynthesis. One of the lessons I learned at Quid, was how one can take a word with a modern and classical definition and own mindshare for this. Quid stemming from the latin for the essence of or “something for something” ie Quid Pro Quo also has a modern financial reference. Now when you search for Quid in Google you get our website. Our intention is that in the future Quid will exclusively remind you of intelligence software, or a new frontier of human knowledge augmented by the power of computers. 

Now for defining parasynthetic and extending its OED definition

noun 1. the formation of a word by the addition of a derivational suffix to a phrase or compound, like greathearted, which is great heart plus -ed. 2. the formation of a word by the addition of both a prefix and a derivational suffix to a word or stem, as demoralize. 3. Created through Synthetic Biology

Foundations

Just like the first moon mission, the applications of Synthetic Biology have significant opportunity to redefine how we live. As a discipline, it is an enabling technology to create new things on top of thousands of years of evolution. Biological design is elegant, often very complex. Breaking that down, simplifying it, refactoring it, and controlling it to do what we want is a seductive idea. This is synthetic biology. 

For a biochemist, synthetic biology brings the same power and feeling of creation that software engineers have. Imagination, creativity, and an engineering mentality transform simply understanding nature to building what we can imagine on top of it. This is what excites me. To finally have that creative power, but coupled with the foundational passion which brought me to the field in 2001 is very exciting. Post human genome, we had the potential to understand whole biological systems as systems. 

Since 2001, there are foundational ideas that are enabling for synthetic biology.

1. DNA synthesis: The cost of DNA synthesis is going down, and becoming faster
2. DNA sequencing: The cost of sequencing is going down, and becoming higher throughput
3. Big Data & Bioinformatics: We can store, process and manipulate large amounts of data more effectively; we can run algorithms and visualization on this data to help us make better engineering design decisions
4. Systems Biology & Circuit Design: Our understanding of genetic control and our understanding of the central dogma (DNA —> RNA —> Protein) is improving, as our our experience in controlling it
5. DNA manipulation & transfection: We can construct larger fragments, insert them into our choice of biological chassis - bacteria, yeast, algae, mammalian cells etc
6. Output reporting: Our ability to construct circuits, and see their output through optical or non optical techniques is improving
7. Directed Evolution: Instead of knowing what we to build, we can evolve organisms towards a stimulus, and run forward nature to find an optimal design solution in combinatorial space

I will be exploring topics in these foundational idea spaces, as well as dissecting what has been built using synthetic biology and the design principles that underlie them. This is everything I am learning. 

Image by illustrator Danny Haas. See his work here

In a determinate world, calculus dominates. You can calculate specific things precisely and deterministically. When you send a rocket to the moon, you have to calculate precisely where it is at all times. It’s not like some iterative startup where you launch the rocket and figure things out step by step. Do you make it to the moon? To Jupiter? Do you just get lost in space? There were lots of companies in the ‘90s that had launch parties but no landing parties.          

Peter Thiel, at Stanford

Technology macro trends and their intersection give us a view to the future. It is their intersection that enables for a deterministic view of the future. At some point in the future, those macro trends will come together creating a new possibility. This is a framework to determine entrepreneurial opportunity. 

Problems are ever present. Markets don’t just get created. Possibilities do. Analyzing Facebook reveals this pattern. Arguably something new like Facebook builds on the intersection of macrotrends that create a new possibility. These include widespread internet access, the abundance of digital cameras and location sensors to construct an accurate representation of the social graph of the planet online. It’s business is built on utilizing the assets it has created to do business in established sectors; real world identity and the size of its channel allows it to make money in payments and advertising. Its in the channel business, which is effectively the media business. It comparable to a very large TV channel. Facebook’s business is built on a deterministic possibility that the social graph on the planet will be available online in its entirety. 

So the theory is that markets stay constant and technology progress is changing and creates new possibilties. That would mean that there are old markets and new possibiities for old markets, which are defined as opportunities.

As long as those markets have enough value and there is an initial beachhead that can be guaranteed then its a very good market to go after. Markets can be quantified by counting their composition. Markets may be composed of consumers and businesses. How much you can get from each of these customers bounds your revenue outcome. 

For example the market for pre-natal, or pre pregnancy genetic testing is every couple having a baby. Since these tests have to be administered locally and tested at a remote facility the market size is geographically constrained. So the market for a company like  Counsyl or Natera is for every child being born in the US. Natera and Counsyl are enabled by advances in the read length of DNA sequencing, lab robotics, bionformatics algorithms, and data storage and processing. Also local markets have nuances. The US market for genetic testing may be possible because of attitude shifts or legal conditions. That may bound its market timing in Europe or Asia. 

The market for a mobile application that can distribute to users globally is the number of people that have devices that you can download that application. Also of all of the users what proportion of users satisfy the use case for the application determines its addresible market. So a dating application addresses the % of the mobile population that is single. Or a application for gardeners is bounded by the number of gardeners who have iPhone or Android devices. 

Deterministic views of the future also ensure some kind of security. In the future Computer vision algorithms will have the information processing capability of a small child. It will happen, is the pitch for Vicarious systems. Their work is bounded by this asymptote. It makes it easier for teams to focus on a deterministic vision. Its just human nature to be able to adapt our unconscious thinking to a deterministic outcome. 

Thinking of what you wish to build in a non deterministic fashion shows an inability to have a stance on the future. A deterministic future is better.