Happy Eggs and Algae — Moving from Idea to Problem
Startups can be more impactful when working in problem spaces than they are when just working on ideas. Working on problems enables them to use their advantages of being able to decide and act without delay, and to take risks that having a more mature business makes more challenging. But at the same time ideas are easier to both generate and communicate. A visual of an idea — even a work in progress visual such as happy eggs and algae — is more narrative than “distributed solar energy to address protein gap and agricultural input effectiveness for customers with concern about sustainability and ethical sourcing”.
The motivations and specific trigger for a startup come from a number of places. Most people (at least those without a consulting background 😉) need to map how they normally think into a more useful structure to reason about for a startup. The trigger for me for this startup has come from two existing areas. The first a long term but non-expert fascination with the potential impact of synthetic biology. Synthetic Biology is generally biotech but with a particularly generative and design perspective rather than growing out of an analytical perspective. And a broader focus, for example with designed biological organisms producing non-biological materials like concrete deposited by algae or new textiles that can replace or extend the role of leather, or even biology aiding in metal production. Futurists talk about how bringing small samples of future versions of these biological components out of the gravity well into space to “grow” our space stations will be more effective than relying only on large launches. And I should shout out the book Soonish if you like thinking about this kind of scale of change. My second trigger was getting exposed to some specific and novel facts about algae. The credit here goes to 4th year design group at UW who had produced a cost effective and modular bioreactor and grew high protein food grade algae. They shared their design and some of the cool properties of this microorganism.
In my case this hit me at a time where I had some space to make connections on this and be curious — this kind of intentional space really matters! It turned into a cascade of connections “what could you use this for”, “what is needed to make it work”, “who needs something with these properties”. Basically the process of building relationships and mental models of what could exist in an imagined reality and contrasting it to what exists today and near future. Essentially a version of learning but with hypotheticals. A shout out to a course I attended with Greg Wilson, a good human whose course helped give me a structure to think about learning in what I would call an “applied conceptual” way. There are other formal techniques such as lean canvas, and I use the questions from leand canvas as prompts. I only go through the structured version when I need to use them as an alignment or communication tool with others.
There are a lot paths explored briefly and not shown in the sequence below but for me the specifics of the idea were:
- Algae is super efficient at turning solar energy into biomass, especially protein (like 7X more efficient than other crops). The student group was able to design and manufacture a bioreactor that successfully resulted in growing a lot of algae on low inputs
- It seems like a big risk in wide transformational tech in early stages is to stay in the abstract and not have a driving problem to be solved. Or to not have the problem correspond to a meaningful business between zero and the 25 year transformation — so I focused a lot searching on customers and needs. This is where there were a lot of specific ideas “making flour with algae” and google searches to understand what is being done. I even tried to order Umaro algae based bacon to Canada so I now have a restaurant supply account 🙂.
- I was most excited about a specific scenario that checked the most boxes: Use a distributed production system on farms to produce protein from modified algae for cage free chickens — lots on why this is so cool later.
I _then_ spent more time organizing my thoughts on major trends and “why that might win”. This is relevant to understanding the overall options in a startup (you will pivot!) and the impact you could have. And especially understanding where you will be rowing with the current or against it when it comes to customer trends, competitor trends, and technology changes. It seems like a backwards order (and you do have to be careful you aren’t _just_ fitting the data to the bad reasoning) but without some specific ideas I am testing against the trends I find the breadth unmanageable so I start with ideas. For example I could have emphasized the fossil fuel transformation trend from the same “algae + synbio” starting point — but it is likely not a key trend to reason about this idea. There is certainly a degree of iterative co-creation that would make someone in experimental design or statistics weep — which will need to be resolved in following steps. The trends I synthesized are mix of “confident prediction” and “contingent”. Contingent trend in this case is a term I use meaning I am not necessarily suggesting they are already demonstrated to be true, and different people will place different bets on the likelihood or desirability of a trend, but something to let you reason about _if_ this trend is true so you can evaluate the space more broadly. A former colleague used the “what needs to be true to expect outcome X” as a similar framing. Trends I think are most relevant:
- Biomass, especially protein is a key food security consideration to feed population growing to 11 B people (another book recommendation Wizards and Prophets)
- Consumer concern for ethical food and competing pressure on family budget
- Climate change and competitive uses of arable land — basically how to avoid ineffective climate tech that diverts existing cropland
A structured version of this process is Where to Play and How to Win that is a great source of mindset and thinking, but used only informally in what I have done at this stage.
At this point I have translated some personal goals and perspectives combined with some specific ideas into a sketch of trends. But I don’t really know if anything is likely to work. I really resonate with the idea of a startup process to be progressively de-risking (i.e. learning) about a problem and solution and there needs to be a validation pass here that might either take me back to restart, or to refine, or to move forward. The biggest items I am thinking about here are customer related (do people want it, how many people, how valuable is it) and feasibility of some tech pieces (it would be powerful to make changes to the algae to make it more nutrient efficient by borrowing genes from different algae, how cost effectively over time can the distributed bioreactor and growing be, what will the yield be in practice)
My intended process takeaways for people are:
- It’s fine to just have preference and personal excitement and ideas, and for the trigger for a startup to be random rather than a billion dollar idea
- It is valuable turn that “idea” into a market opportunity, trends, and why it might win to reason about its potential and to communicate
- Expect the idea to change, and expect to lots of work at this stage (combo of spreadsheet models, indirect research, and direct customer interviews) to get to something specific enough as part of engaging other people and other resources. And most importantly to satisfy yourself that it _can_ work and under what conditions.
My intended specific startup takeaways for people are the major trends above:
- Solar to biomass to protein matters
- Ethical, sustainable, good, and affordable food matters
- Solutions should be holistic as possible and consider second order effects like arable land use