Startup Lessons Learned

NOVEMBER 13, 2008

Because five whys kept turning up a few key metrics that were hard to set static thresholds for, we even had a dynamic prediction algorithm that would make forecasts based on past data, and fire alerts if the metric ever went out of its normal bounds. Case Study: Continuous deployment makes releases n.

Software Review 167

Software Review Technical Review San Francisco Continuous Deployment 167

Startup Lessons Learned

MARCH 16, 2009

This is a fairly simple approach to creating a weighting system using an Opportunity Algorithm. The algorithm is Importance + max(Importance - Satisfaction, 0) = Opportunity. Case Study: Continuous deployment makes releases n. I wont do the explanation justice so I suggest you grab the book.

Agile 111

Agile Customer Development Developer San Francisco 111

Startup Lessons Learned

JANUARY 30, 2009

Build a world-class technology platform, with patent-pending algorithms and the ability to scale to millions of simultaneous users. Departments were built and were even metrics-driven. But there was no feedback loop to help the company find the right metrics to focus on. Case Study: Continuous deployment makes releases n.

San Francisco 150

San Francisco Lean Agile Continuous Deployment 150

Startup Lessons Learned

SEPTEMBER 15, 2008

Focus on the output metrics of that part of the product, and you make the problem a lot more clear. To promote this metrics discipline, we would present the full funnel to our board (and advisers) at the end of every development cycle. Max Levchin of Slide and Paypal has noted that 10% of Slides headcount is devoted to metrics only.

San Francisco 166

San Francisco Lean Technical Review Continuous Deployment 166

Startup Lessons Learned

NOVEMBER 29, 2008

For the past couple of years Ive used a question that I once was asked in an interview, in which you have the candidate produce an algorithm for drawing a circle on a pixel grid. As they optimize their solution, they eventually wind up deriving Bresenhams circle algorithm. Case Study: Continuous deployment makes releases n.

San Francisco 146

San Francisco Lean Agile Java 146

Startup Lessons Learned

APRIL 7, 2010

At least, not in the traditional sense of trying to squeeze every tenth of a point out of a conversion metric or landing page. Even if it shows improvement in some micro metric, does that invalidate the overall design? Those of us with a computer science background call it the hill-climbing algorithm. No one feature is to blame.

San Francisco 154

San Francisco Lean Metrics Design 154

Startup Lessons Learned

JANUARY 4, 2009

More common is to use a one-way hashing algorithm to map the data to be accessed to one of the shards that store it. Theres no complex algorithm to go wrong, just a simple lookup table. Of course, you could use URL-based sharding to "wrap" a CH algorithm (or any hashing scheme you wanted).

San Francisco 151

San Francisco Architecture Startup Database 151