all that is new is to be learnt.

a few weeks ago i was trying out a new web app and clicked through their quiz to determine my ‘persona’. last week i happened to meet the founders of that startup who asked me if i remembered the persona that their site assigned to me (‘snap to grid’). i honestly could not remember despite remembering everything else about their site, design, and content.

it is an interesting flaw i find in myself – i think i find myself in constant state of being someone else. tracking time in my rearview mirror, i realize i didn’t know much a year ago. i have felt that way every year i think.

i am not sure why i think i am not a persona of formed interests and intent. i do think i am in search of various parts of a persona.

and i remain more interested in what i could be vs. who i am.


No Email please, we’re collaborating.

Startups rely on constant, open sharing of information across all functions in order to have a shot at becoming a company. However, the most common tool for communications – Email, like cubicles in office layouts, encourages silos of information rather than easy, frictionless, and continual sharing.

I believe collaboration only happens when it happens all the time. It is not an activity that can be scheduled in meetings or forced via specific/distinct applications foisted on employees. I  think it needs to be a central part of a primary nervous system used in a startup.

While multiple attempts have been made to ‘fix email’ (ShortMail, MinBox,…), I think a bolder new approach may be required – no email. Instead, replace email with a simpler communication system that enables open participation across all employees in a startup.

The idea is quite simple – all employees ‘publish’ everything they do, and others ‘subscribe’ to whoever they need to subscribe to – in order to do their work. I call it NAIL, a portmanteau of NoEmail.

There are three canonical streams of communications that need to flow in such a system:

Work/Activity: Everything an employee does is published here. Code/dev/test/get/push/A-B/Customer-prezo/Company Ops updates/HR/Admin
Collaborate: Anything that requires two or more people to work together. Includes click-to-video, click-to-talk
Educate: Everyone’s capture of what you learnt + what you want others to learn. resources, configurations, external-resources, blogs, faqs,…

Streams in the flow

The information flowing in this communications system can be presented in a simple way using a (Dave Winer’s) reverse chronological streams of the three categories. In the interest of fast browsing, snippets can be limited to 2 lines of text+links or even 140 chrs in a nod to the popularly accepted tweet limit.

Underlying these three flows are a robust message bus, calendar system, and other Voice/Video-over-IP support. (Think UDP-fast).

A minimum feature set for such a system is:

  • Allow anyone to subscribe to anyone else.
  • Accounts for people, groups, and systems (let the db NAIL its pain)
  • @reply, @group-reply, @DM, @Group-DM
  • Archive everything. Make it all searchable.
  • Click-to-multiparty Video Call, Single click-to-multiparty Voice call built in.
  • Recommendations section of suggested people + content to follow for new employees and all users. Min-list by function, then suggest by interests, activities.
  • Must be Mobile from day-1.
  • Encourage Photos/other-media capture (especially in collaborate stream)

For communications external to the startup, use email as a connector to/from the primary communications system. For incoming emails to a user, map it as @user in to their “Collaborate” stream.mapping email to message

For outgoing email messages, map the message and attachments to standard email and also publish to ‘Work’ stream. Private outgoing messages can be DM’ed which suppress publish. mapping message to email

I have no idea if something like this scales well to large organizations or large groups but for small (<10?) work groups, I think this just might work better than email. Of course, in true startup spirit, if you can hack together NAIL on top of Twitter, even better…



my values as an investor: an open letter to founders

dear founders,

over the past few years, i have invested small amounts of money where the founders have given me an opportunity to do so. for each such opportunity to share in their quest, i have learnt something – and i am thankful.

as i talk to the founder(s) and the team, i find that some teams are naturally curious and want to know why i’d invest and what my relationship to that startup would be. one word that rarely gets used in these conversations and questions is ‘values’. i have written previously about startup values and as an investor, want to make sure that founders talking to me about angel/seed investments understand my values.
my values are expressions of some simple viewpoints and actions i strive to live by and bring to the table as an investor. these are:

  • are you taking enough risk?
  • optimize for the long term – always.
  • do I identify with, understand, and agree with your mission, not just your idea, technology, products, and startups.
  • the small amount of money ($5K to $50K) i invest carries with it the ability to turn to zero or be padded with zeroes. if it enabled you to make an effort you couldn’t otherwise make, it will be well spent.
  • while i will make an effort to help whichever way I can, you should understand that:
    • i am not your product manager
    • i am not your rolodex. access without context means nothing.
    • i am not a visionary. i am investing in your vision which is tuned constantly, by every day interaction with your users, technologies, products, and your peers. chase what you see, not what i or others ask you to chase.
  • i have failed many times at many things. i have learnt from failures. successes taught me more, but failures caused me to learn more.
  • while you focus on user growth and customer associated metrics, don’t lose sight of personal growth metrics.  i pay particular attention to personal and inter-personal growth within your startup.

and finally, the most important metric for me – your success as a founder isn’t measured in dollars raised or valuation or money earned for investors, it is measured in how many other people did you make successful. this is my yardstick for a founder.


On relevance, guided discovery, and curating commerce for serendipity


a venn diagram

Relevance is one of the most sought after qualities for any kind of content presented to a user. Clicks are a user’s declaration of relevance within our conventional browser UX for presenting content, media, news, and information. Relevance becomes a critical tool for navigating information as the amount of information available on the Internet grows every second. Measured in terms of physical size, we are approaching ‘Nebula‘ scale, measured in lightyears for the amount of information available on the internet today.

Presented with this interstellar scale of information, the challenge in navigating the mass of information is no less daunting than figuring out information-entropy (Shannon entropy) of online content filtered/ranked by relevance. Put another way, all information is high entropy (high uncertainty) unless sorted, presented by relevance to each user.

Ideally, all content should be customized such that the presented content is relevant to that particular user and more likely to engage the user without requiring inefficient actions (searching, clicking, scrolling) on the part of the user or requiring a constant declaration of relevance on every tab and every site.

In this post, I attempt to understand how relevance works for content recommendations on some of the big sites and examine applying this model of determining relevance to commerce online.

In the context of relevancy, the 2D wall of content at Pinterest is very conducive to more browsing but not necessarily deeper engagement as content is not sorted (or sortable) by relevance. While categories help, they are not personalized and presentation of content does not sense any other evanescent declaration of user interest on their site or other sites. Thus, it is clear that:

Relevance != Social Proof

Quora’s UX surfaces high quality but not necessarily high relevance by relying on democratic votes (1 vote per user regardless of their Quora-ranking/clout/points). As their product evolves, I hope we will see more relevance – perhaps by picking topics as well people of interest. This is a form of declared relevance relying on declaration made by the user, not necessarily determined by a user’s ongoing interaction with content on the site. The takeaway:

Relevance != Quality of Content

Twitter’s #Discover tab is the most advanced relevance-filter yet with its mix of tweets by people you follow as well as people who share your interests as determined by cookie tracking on sites you visit + interests of people you follow. I think this is the closest determination (ongoing) of relevance in an online product.

Relevance = A mix of [Social Proof + Quality + Personalized-Interest matched Content + …]

Relevance and Commerce: curating for serendipity

While Google, Twitter, and to some extent Quora address relevance for the world’s entire corpus of information, e-commerce companies can and should apply similar techniques to determine the right products for the right buyers. While narrowing down choices presented to a potential buyer or browser, the content selection should permit some amount of delightful discovery. This need for counterbalancing narrow, algorithmic selection and presentation speaks to the emotional part of a user’s browsing experience.

Paraphrasing Tufte, all design is choice – and a failure to engineer correct information flow underlying presentation [balancing relevance vs. discovery] will surely result in clutter and confusion. The balancing act for narrow relevance in commerce is serendipity – let the user discover adjacent information/products albeit in a delightful way. And thats where I think we’re headed in commerce – augmenting relevance with sufficient serendipity to deliver the right user experience. While algorithms do well with determination and tracking social proof, quality, personalization using user-interests, serendipity requires blending in a measure of user and domain-expert curation. And, therefore

Relevance + Serendipity = Algorithms & Machine Learning + User curation + Expert Curation

Within online commerce, there have been three broad waves of innovation:

Wave 1: Digitization of product information, browsing, and fulfilment

Amazon is clearly the best example of this class of innovation with its broadly horizontal digitization of product information followed by a simple layer of product-interest matching and recommendations. If you saw product X, you may also be interested in product Y where Y may be the most viewed/purchased item along with X. There are no social or other user-level connections that Amazon seems to use other than the user’s history on its site. Currently it presents six items in at least six categories if I visit the homepage (logged in). It hasn’t even asked me a style wizard to narrow down ‘recommendations’ or increase relevance to me.

Wave 2: Propelling discovery by economic compulsion (ok, by surfing the curves of indifference)

Groupon and other daily-deal sites induce discovery by providing an economic compulsion for users. These intermediaries harvest a user at their point of indifference in the face of compelling economic value for the presented product. With enough data points, Groupon et al will have their own version of consumer demand curves. I expect they will move beyond offering a single daily-deal towards a smorgasbord of carefully chosen goods that are seen as acceptable substitutes given a certain budget constraint. They certainly have vast consumer purchase data to do so within local commerce – a valuable dataset vs. Amazon which is purely online. Groupon Goods, I hope is the first move in this direction. If I was at Groupon, I would hire Economists as well as statisticians and data-scientists to figure out indifference curves and match it to a variety of local commerce.

Wave 3: Guided discovery – engineering serendipity

Faced with an unprecedented data storm, consumers need/want fewer choices but the right choices. Balancing this need for narrow personalization is serendipity. Serendipity is pleasant and welcome because it helps users make a useful discovery even though they were not explicitly not looking for it. This middle ground is guided discovery. Lets examine how information/content sites deal with engineering for serendipity.

Serendipity doesn’t happen on a Google search results page as a user (and PageRank) explicitly rules it out in favor of surfacing the information users are searching for from a sea of information.

Amazon recommendations hint at some serendipity but is strictly dependent on user’s previous purchases, items browsed, and most popular items related to a user’s purchases. The form of guided discovery on Amazon doesn’t leverage a user’s behavior or interest-profiles that exist elsewhere.

Pinterest at this point (May 2012) is random serendipity which is not very time-efficient pursuit for the user though it yields great time-on-site and other vanity metrics for Pinterest. In effect, there is no incentive for Pinterest (yet) to boost relevance vs. pageviews. Guided discovery only takes place along canned categories or along content classified by the users in various boards.

Quora in some ways is guided-serendipity by walking the user along the axis of quality content. The only axis of serendipitous discovery is following people and their Questions/Answers/Boards/Posts. If one could do Quora score/votes based recommendations for products/brands and integrate some level of sentiment analysis of Quora answers, it could become a compelling front-end for products with better insights vs. Consumer Reports.

Twitter brings together some nice elements of guided discovery by mapping interests, people, and recent events/topics of interest to your chosen geography at city/national levels of the twitterverse. I think Twitter is ideally placed to guide users towards all kinds of media in addition to news and discussions. It can help me find media, content, news, and information based on:

  • Interests I follow (on/off Twitter)
  • People I follow
  • Interests of People I follow
  • Activities of People I follow (people followed by them, their retweets, favorites, …)

As far as I know, there are no equivalent efforts in online commerce applying data mining based recommendations to guide the users towards the right mix of guided and serendipitous discovery. Merely suggesting some ‘recommendations’ in a side-bar don’t suffice. What we need is a relevance based content-display and navigation system.

This I believe is the next big wave of commerce – data curated commerce to help the users browse less, find more.



The best question VCs can ask you and you can ask VCs.

When founders and startups meet with Venture Capitalists, Angel investors, or potential advisors, most of the time is spent talking about the founder’s insights, technology, product, or the market they intend to innovate, disrupt, or create. In my experience across both sides of the money-table as a VC and as a founder, the hardest and the most insightful question is often not about the knowledge founders or startups have, but rather, what have they learnt. This concise question embodies just about everything the VCs want to know about you as well as your company.

What you “know” is the platform that you stand upon and the framework for building your product. What you “learnt” is the  valuable part that allows you to create something of value, hopefully – a lot of value – for your customers. This is where you have the opportunity to figure out something that others have not understood yet. Thus, ‘learning’ is your unfair edge in an otherwise irrational pursuit where the odds are against you most of the time till you trump them with your learning, not knowledge.

If knowledge is velocity, what you have learnt determines your acceleration, i.e. the second derivative.

(Thanks @jessefarmer)

This seemingly simple question is in fact quite complex. When a VC asks you this question, they are judging multiple things at the same time:

what does it tell them about your learning style and pace of learning
what does it say about your willingness to learn
what does it say about your willingness to fail while learning
how does it educate them about your market, your technology area, your competitors

And when VCs ask this question of their portfolio companies, they are keenly focused on the acceleration (or deceleration) of your company, not the somewhat static ‘knowledge’ you started off with when they invested.

I also think this is also the question founders should ask potential investors. Rather than talk about fund size, investing philosophy, market-trends,.. (all things you must know before meeting them), ask them the following two questions:

1. What have they learnt in the past 2 years.
2. What new behavior, investments, or market developments do they expect to occur given that learning.

If you hear answers that are rambling, unfocused, or evasive, it will tell you more than their past record or their current investing ‘thesis’.

When you hear clueful answers, it should signal to you that the VC asking this question is more likely to be thinking ‘long-term’ vs. ‘flavor of the day’. VCs that can discuss what they have learnt and how they see it influencing the next few years are rare and good for early stage startups.

p.s. The words ‘learnt‘ and ‘learned‘ are interchangeable here. i have a preference for using ‘learnt’, having learnt my english language skills reading newspapers and listening to the BBC in India and later during graduate studies in Canada. “learned” is the more commonly used form of the word in U.S.A.