Let’s build Product, not Software - Part 2

In the previous post, I have shown you a real example about how to solve the problem as a Software Engineer. This time, we gonna do it by the Product Engineer approach.

Make Agile great again!

If you refer to the first post that I wrote, Building Product is about delivering user values, collecting feedbacks and constantly adapting to the change of business. Does it sound like Agile? Yes, in my opinion, Agile seems to be the best fit out there for Product company at a small and medium size.

Don’t do this

Let’s start with the non-Agile way by this picture-by-picture story





When you put this into a Software perspective, it’s pretty much the same with the first example that I showed in my previous post. The way most people would choose is to implement the whole feature, from backend to frontend before delivering to the customer. Again, do NOT do this.

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Previous post: Let’s build Product, not Software - Part 1

In the first part of this series, I have walked you quickly through some differences between Building Product and Building Software and why Building Product is important. In this post, I’ll show you a simple example, analyze its problem and come up with a solution following the Product Engineer mindset.

A Software Engineer approach

Let’s take a look at this simple project

You are working for an Automation marketing platform for E-commerce merchants. The product needs the data about the sales orders of the merchant and your task is to build a 1 way Sales Order integration feature to sync data from Shopify to your system

After going through several discovery steps with your customers and the PO, you decide that it’s time to make the implementation plan. You now come up with this plan

Milestones Details Duration
Backend Build the backend to handle auth & webhook requests from Shopify 1 month
Frontend Build the frontend for the users 1 month
Beta Release to some beta customers 0.5 month
Bug fixes Handle issues reported from customers 0.5 month
Go live Release to everybody 0.5 month

Sounds good? Yes, this is a perfect plan from a Software Engineer perspective, but…

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This may not always be true. It really depends on the type of company that I will go through in this post. This also sometimes sounds strange from a Software Engineering perspective, but as we get used to, it really did help FMG (my old company) grow to the leading player that niche market

Software engineers love technology, for sure. We love building things, love applying the latest technology into our product. However, we usually forget one important thing: The technology that doesn’t fit in the product, cannot make a profitable business, is a useless one. That sounds obvious, right? Surprisingly, a lot of Software Engineers that I’ve met made this mistake, especially the talented ones.

Let me walk you through the 2 approaches, compare the differences between them and analyze some real examples. In latter posts, you can also find some techniques that I’ve applied in order to help build a better Product Engineer mindset.


This is converted from a presentation that I made at work

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Leetcode Rotate Array

Given an array, rotate the array to the right by k steps, where k is non-negative.

Example 1:

Input: nums = [1,2,3,4,5,6,7], k = 3
Output: [5,6,7,1,2,3,4]
rotate 1 steps to the right: [7,1,2,3,4,5,6]
rotate 2 steps to the right: [6,7,1,2,3,4,5]
rotate 3 steps to the right: [5,6,7,1,2,3,4]

Example 2:

Input: nums = [-1,-100,3,99], k = 2
Output: [3,99,-1,-100]
rotate 1 steps to the right: [99,-1,-100,3]
rotate 2 steps to the right: [3,99,-1,-100]


- 1 <= nums.length <= 105
- -231 <= nums[i] <= 231 - 1
- 0 <= k <= 105
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Leetcode: Search Insert Position

Given a sorted array of distinct integers and a target value, return the index if the target is found. If not, return the index where it would be if it were inserted in order.

You must write an algorithm with O(log n) runtime complexity.

Example 1:

Input: nums = [1,3,5,6], target = 5
Output: 2

Example 2:

Input: nums = [1,3,5,6], target = 2
Output: 1

Example 3:

Input: nums = [1,3,5,6], target = 7
Output: 4

Example 4:

Input: nums = [1,3,5,6], target = 0
Output: 0

Example 5:

Input: nums = [1], target = 0
Output: 0


1 <= nums.length <= 104
-104 <= nums[i] <= 104
nums contains distinct values sorted in ascending order.
-104 <= target <= 104
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Leetcode: Move Zeros

Given an integer array nums, move all 0’s to the end of it while maintaining the relative order of the non-zero elements.

Note: that you must do this in-place without making a copy of the array.

Example 1:

Input: nums = [0,1,0,3,12]
Output: [1,3,12,0,0]

Example 2:

Input: nums = [0]
Output: [0]


1 <= nums.length <= 104
-231 <= nums[i] <= 231 - 1
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Leetcode: First Bad Version

You are a product manager and currently leading a team to develop a new product. Unfortunately, the latest version of your product fails the quality check. Since each version is developed based on the previous version, all the versions after a bad version are also bad.

Suppose you have n versions [1, 2, ..., n] and you want to find out the first bad one, which causes all the following ones to be bad.

You are given an API bool isBadVersion(version) which returns whether version is bad. Implement a function to find the first bad version. You should minimize the number of calls to the API.

Example 1:

Input: n = 5, bad = 4
Output: 4
call isBadVersion(3) -> false
call isBadVersion(5) -> true
call isBadVersion(4) -> true
Then 4 is the first bad version.

Example 2:

Input: n = 1, bad = 1
Output: 1


1 <= bad <= n <= 231 - 1
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Just a collection of tips to make working with Postgres (and other SQL-like databases) easier

Integration data

Usually when you build a system that integrates with other 3rd party service, you will need to store integration information related to the entity, for example the id of the entity on the 3rd party system or some of its configuration on that system. Imagine that you are building an e-commerce related product, you may want to sync the Sales order information from Shopify to do the analytics on customer behavior. The first solution you can think of is to add a column like shopify_entity_id on that table.

  • What will happens if you introduce another integration later? Does the name shopify_entity_id still make sense? You may consider renaming it to external_entity_id. How do you know where it comes from? Adding another source column? How do you store extra 3rd party information about the sales order? Keep adding columns like external_something? Do those columns actually belong to the sales_order table itself?
  • What will happen if an single entity exists on multiple 3rd party system? For instance, the sales order may be presented on both Shopify and on another Shipping service. How would you deal with it? Keep adding more columns? What if we introduct another integration?
    • A Json (Jsonb) column could solve the above issue but also creates a whole new problem. How about schema enforcement and constraint? How do we make sure that nobody will accidentally update it the an incorrect schema? How about null and undefined values (in case you are working with Javascript)? How about indexing the values for quick access? You can index inside the json but it just makes things more complicated due to those schema problems mentioned above.

The solution, of course, is a SQL approach: make an entity integration table (sales_order_integration in this case). It’s a 1-N relationship, 1 sales order could have 0 or multiple integrations

sales_order table

id shipping_address price weightMg
1 Ho Chi Minh city 10 20
2 Hanoi 20 30

sales_order_integration table

id sales_order_id external_entity_id source
1 1 external-id1 SHOPIFY
2 1 external-id2 WOOCOMMERCE
3 2 external-id3 SHOPIFY
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Just a collection of tips to make working with Postgres (and other SQL-like databases) easier

Measurement Unit

Take this case for an example, you have a product table and you want to store product information like its size and weight by adding these columns to describe such properties: width, length, height and weight.

id name width length height weight
1 ipad 10 20 0.1 0.5
2 macbook 20 30 0.5 2

So what’s the problem with the above table? We are assuming that the size props (width, height and length) are measured in cm and the weight is measured in kg. Usually, we could put this logic in application layer to make sure we convert everything to cm and kg before inserting into the database. However, it could lead to even more problems

  • What will happen if a new dev join the team? How can you make sure that person will know when to convert and when not?
  • What will happen if a dev using pound join the team?
  • What will happen if a dev accidentally assume the value in weight is in mg?
  • Sometimes, you could do a double conversion, making thing worse.
  • You need to remember adding comment to every place in your code, just to remind people which measurement unit that function is using.
  • Which data type to choose? Integer, of course, is not a good choice. However, working with real, double, decimal or numeric is always harder compare to int. They could cause some problems with parsing and datatype for languages/libraries like Nodejs.
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Leetcode: Squares of Sorted Array

Given an integer array nums sorted in non-decreasing order, return an array of the squares of each number sorted in non-decreasing order.

Example 1:

Input: nums = [-4,-1,0,3,10]
Output: [0,1,9,16,100]
Explanation: After squaring, the array becomes [16,1,0,9,100].
After sorting, it becomes [0,1,9,16,100].

Example 2:

Input: nums = [-7,-3,2,3,11]
Output: [4,9,9,49,121]


1 <= nums.length <= 104
-104 <= nums[i] <= 104
nums is sorted in non-decreasing order.
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