Early Signals

“What are you doing?”, my wife asked. Most of the time I grunt something. I think of this question as more of a greeting than a question. This time, however, I said enthusiastically “I am reading about the Wiki Wiki Web”.  This cracked up the entire family (two kids included). Wiki Wiki means quick in Hawaiian. This was in the early 90s before the days of Wikipedia. I was browsing through c2 wiki.

Wikis became mainstream when Wikipedia became popular and now my family does not laugh at me anymore.

There are times you have a hunch about certain trends. I felt strongly about – Databases in the 80s, Wikis and application components in 90s, XML, Python in early 2000 and now ML and Chatbots. This resulted in my working on an SQL database engine in the mid-80s, database components in 90s, an XML chip in the 2000s and on Python since 2006. Now, it is ML and chatbots and Natural Language Processing.

Not every thing I was excited about became mainstream. RDF and Semantic Web, OLE from Microsoft,  Domain Specific Languages and Pattern Oriented Languages did not go very far.

Over a period, I have built a few thumb rules about paying attention to early signals in emerging technologies.

  1. What is the research behind the technology and how long has it been going on? For example, neural networks and ML are several decades old. AI has gone through several difficulties.
  2. What is the volume and velocity of research papers?
  3. Is government funding research in this space? (Internet, Page Rank algorithm, self driving cars and many others started as funded Government research).
  4. Who are the major companies involved in the early adoption of these technologies? For XML it was Microsoft, Sun Microsystems, and several others.
  5. What are pilot projects being done for commercialization and who is working on those?
  6. Who is hiring in this space?
  7. Which business publications are covering topics about this space?
  8. What companies are getting funded? Funding is both a leading and lagging indicator depending on who is funding and why they are doing it.
  9. How is the information about this space being propagated? Who is propagating it?
  10. What are the conversations going on in Twitter?
  11. Are there books on the subject? Books are most of the time lagging indicators.
  12. Are these technology topics being covered in conferences?

Some of these indicators are easy to find. You need to look for others.

What do Product Managers do?

The term “Product Management” evolved somewhat. For me, it was a confusing term. Product Managers (AKA PMs) did not fit into either development or marketing roles. I list three good articles that demystify Product Management.
  1. Evolution of the Product Manager
  2. The Product Manager Contribution
  3. How product managers are becoming mini CEOs

There are also two books I like.

Product Management Books - Inspired

 

My son suggested that I read Inspired.  A few days later, I forgot the title and was searching for books on Kindle, when I found 42 Rules.

product managment books - 42 rules

Reading them, I realized that:

Product managers play the role of glue between customers, products, marketing, sales and engineering.