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Posts Tagged ‘people:Jaideep-Singh’

Looking at the rain outside my posh Sand Hill office, my co-founder Jay Bhatti and I wondered how we could assemble the right team to build the company we had envisioned. Every entrepreneur confronts this challenge. The vision, in my opinion, is the easy part. Getting it done is a lot harder. My experience in venture capital had taught me first-hand that building a market leading company requires a great team and a great company culture. That is what separates winners from also-rans! But it’s also a lot easier said than done.

Every founding team brings different skills to the table. Knowing your strengths and weaknesses is really important. Jay and I were past our productive engineering days, and were now business guys. As a VC at Clearstone, most of my current network was other entrepreneurs, execs, and other VCs. Jay, an exec at Microsoft, was moving from Seattle, and didn’t bring too much local engineering talent to the table either. But we had great chemistry, and trust, dating all the way back to B-school. And that was a great start.

The first move we made was put together a strong advisory board. We looked through our network, identified the strongest people we knew, and began pitching them. We realized that some got the vision instantly and some didn’t.

I have noticed that in technology we’re surrounded by very smart people. IQ is virtually a commodity. However, there are those who are analysts – can ask 1 million questions, and be skeptical of everything; then there are doers, people who apply their intellect and resourcefulness to find solutions. Find those people and keep them close to you. Stay a 100 miles away from the former.

We got Siva Kumar, serial entrepreneur, who had started 8 companies not only to advise but also take a board seat. We got Suneet Wadhwa, also a serial entrepreneur, and a friend to encourage us, and push us to to think more deeply about the user, and what problems to solve first.

Being at Clearstone was also a strong asset. Clearstone’s David Stern and others there were active and helpful in introducing us to well connected people. However, our engineering network was weak! We knew no great search guys personally.

Therefore, Jay and I next set about becoming full time “head hunters” - calling all the engineers in our network and asking them to recommend others. We got some leads, some relevant people, but not everyone is into taking risk. They loved the concept but didn’t want to leave their cushy jobs, especially when we’d raised no money.

Just like any large endeavor in life, we set up a process, and fine-tuned it over time. Pushing our contacts and cold calling people become the tasks of the day. We used LinkedIn, and Google, both great resources, judiciously. Each person, and each email was researched and personally crafted. Soon we began to build a large pipeline of qualified talent. Our advisors became a great resource not only to interview candidates, but also introduce us to others.

Siva introduced us to Jeff Winner, a well known VP Engineering with search and consumer background, who was sought after by every VC on Sand Hill Road. We knew we couldn’t close him right away, so we enlisted his help in interviewing candidates. This was a perfect arrangement for both parties. Try before you buy.

In a matter of 60 days, we had contacted over 200 engineers, spoken to about a 100, interviewed 40, and got 7 good guys who very interested. Hongche Liu was the star. He was a hands-on engineering manager and superstar at Yahoo!, a PhD with 10 years of complex IR product experience, in addition to research. Most importantly, he was excited about doing a startup and had a great work ethic and attitude. We put all our force into convincing him to forget his high paying job, de-prioritize his wife and 3 kids, and take a whopping $90k salary!

Vision and concept aside, Hongche, like most engineers who aspire to join startups, realized that the risk of not joining a startup was way greater than being a cog in the wheel at a large company. His learning and therefore value would be a lot greater by being a key member of a venture backed team.

We got lucky with our next hire. Wayne, a teenage entrepreneur, who had built dawsonscreek.com in high school, with over 2m page views a month, was at Microsoft working on the undo button in Powerpoint! He was aching to get back into the web, learn Ruby, and apply his energy while having fun. He blew us away within 15 mins of interviewing; he signed an NDA; 15 minutes later he was blown away by the service Jay had mocked up in Powerpoint.

Wayne was very smart and decisive, and so joined us after his two weeks notice. I realized that the most valuable people are those who are decisive, smart, and have a great attitude. Wayne had all three. Jay calls this the BAD principle – Brains, Attitude, and Drive.

The one thing that frustrated me was that I’d find Jay searching Craigslist for engineers and sending email upon email, with no responses. I pleaded with him not to waste his time doing “stupid” things. I called it adverse selection. I was proven to be the idiot!

Jay found Sam Williams, a young Caltech CS guy, who had goofed off two years in Europe, but was a Ruby on Rails star. Jeff interviewed him, and within 30 mins he walked into my office and said, this is one of the smartest guys we’ve interviewed. He’s a consultant but loves the Spock idea and can start immediately. Like Wayne, Sam was smart and decisive. The only difference was that he started in two days.

Meanwhile, Jeff Winner was spending more and more time with us. He helped us interview and hire. He began to spend more time architecting the product, and in the process began to evolve our product concept. He was also now fully sold on the vision and the team (that he had helped hire). He threw in the towel, and joined full time.

We were now a very strong 5-person core team. On the way we had raised $1m from my colleagues at Clearstone, and were off to the races. Today we have 16 full time people, have raised $9m, and get over 50 resumes a week.

As a VC, I had seen my investments do well when the teams were outstanding and the culture was great. But having gone through it myself, I realized the vast difference between analysis and doing. I have now internalized a few key lessons:

Lessons summary:

1. Find good co-founders, people you trust. Don’t be greedy. In my venture and entrepreneurial experience, many people mess this up.
2. Have an exciting vision. It’s the only thing you have to offer. If you’re not super stoked, nobody else around you will be either.
3. Have conviction and be passionate about your vision especially in the face of adverse feedback. High IQ analysts are a dime a dozen, and will raise a million exceptions. Ignore them; both as employees and as advisors.
4. Get the best and most experienced advisors around your company who share your passion. If u don’t know anyone, cold call until you find them.
5. Have a very high bar for recruiting, both talent and motivation. Don’t let fear and temptation get the better of you. It’s easy to convince yourself that the person has worked at other places and is probably good enough. Good enough is not good. You’ve got to be excited. Remember Jay’s BAD principle.
6. Pay lower than market in the early days; it’s a great filter.
7. Age is not a factor but motivation is. People who don’t work hard, will never be the key drivers in your startup. Perfection comes from hard work.
8. Don’t undervalue engineers from top schools. We got guys from Berkeley, MIT, Stanford, Caltech, etc. and they are all really good. There are lots of great engineers from average engineering schools (like myself) too, so don’t over-emphasize school either. It really is about talent, hard work, and great attitude.
9. There are those who look for problems and those who look for solutions. This becomes clear in interviews very quickly. Hire people who look for solutions.
10. Grow a thick skin for rejection.

Updated

spock.bmpSpock, a secretive Menlo Park start-up incubated with $1 million from Clearstone Venture Partners, will unveil a search engine for people by the end of the year.

From a demo we’ve seen, we think it could be a powerful addition. Spock could take this in some interesting directions. Its main challenge will be to wean users from Google as a first stop, though more on that in a sec.

When Spock launches, it will have 100 million profiles of people in its database, by far the largest open repository of profiles anywhere. Spock delivers a mixture of facts and research on a people, but also opens a profile to social input, giving it a touch of Wikipedia.

This move is a no-brainer, and it makes you wonder why no one has done this yet.

LinkedIn, ZoomInfo and other people-contact related sites were built in different eras, and have focused on specific subsets of people (LinkedIn and ZoomInfo on business execs, for example). Spock, however, exploits all the latest tagging technology and the exploding number of public profiles on the Web since social network sites like MySpace became popular last year.

Scrubbing millions of profiles from the Web wasn’t an obvious thing to do when Palo Alto’s LinkedIn launched several years ago. LinkedIn began as a contact site, allowing people to request meetings through their layers of relationships. It has since tried to move toward a more open model. Indeed, LinkedIn is aggressively building out its people profiles even as we write. (Last week, it also kicked off a major expansion into Europe and Asia as part of a land-grab, with a German version to go live soon.)

Spock starts from the other end. Spock dispenses with the “contact” element of LinkedIn. It is an open site, for people seeking information about other people.

ZoomInfo, which you must pay a subscription for, has 29 million profiles. LinkedIn has about 9 million profiles, and wants to grow to 100 million by 2008. Spock’s 100 million, meanwhile, will only grow, according to co-founders Jaideep Singh and Jay Bhatti.

If Google is a place to find Web sites that are relevant for your search, and Amazon is place to find goods, then Spock wants to let you find people, they argue.

huffman.jpgHere’s an example of how it works: If you type in “actress,” Spock returns results like Google — with listings down a page. In this case, the first entry is Felicity Huffman, who Spock’s engine finds as the most relevant for “actress.” (Now, if you type in “actress” into Google, you’ll see why Spock has a chance; there are few actresses in the results, except for the annoying site ActressArchives at the top). Moreover, as both Spock and LinkedIn make their profiles more popular, these will rank higher in Google’s results anyway.

Continuing with our “actress” example, you first get a photo of Huffman, but you also get a bunch of tags underneath telling you how she is relevant. For example, there’s tag for “Oscar nominee for best actress,” and “Desperate Housewives,” for which she is well known. There’s a “Wikipedia” tag. If you click on these tags, Spock will take you its relevant results for that tag. This gives users a way of searching for information related to the Huffman.

The tag font size gets smaller if Spock’s engine detects the tag isn’t relevant for the person. So if users create a “sexy” tag for Huffman, the tag may get larger or smaller, depending on how many people agree. Spock gives users an option of clicking on the tag and selecting “yes” or “no.” If they select no, Spock factors this into its database. Then, if you type in “sexy actress,” Huffman will have fallen slightly in the ranking. Spock has built ways to keep people from gaming the system. If you want to add tags, for example, you have register — one way for Spock to monitor usage.

Nicole Kidman is the second result under “actress,” even though she won an Oscar (Huffman was only a nominee). Why would an engine rank a nominee higher than an actual winner? Chief executive Jaideep Singh says Spock’s engine factors in hundreds of variables for its algorithm on determining relevance. This is Spock’s secret sauce, he says. We asked if his algorithm takes advantage of Google’s APIs. He said yes, but there are many other sources, he said.

Spock will make money by running relevant advertising beside the profile results.

Spock has seven employees in Menlo Park, two in India, and six more part-time.

Singh and Jay Bhatti met in business school. Bhatti has a background in consulting, having worked at Accenture, Deloitte and Microsoft. Singh was a VC at Clearstone and worked at WindRiver. Jeff Winner, VP of engineering hails from Friendster, eGroups and Netscape.

David Stern, the investor at Clearstone (who contributed an op-ed to VentureBeat here) said the investment is a return to his firm’s roots as in investor in consumer companies — eToys, Overture, PayPal, United Online, MP3.com and eMusic are among them.

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