An antipattern that I see in startups constantly is Senioritis. This normally happens when the startup finds some success and wants to upgrade its product and engineering teams. Typically at this stage, new leaders are hired and there is a we need to grow up vibe. These new leaders typically are hired from established companies/startups and bring with them their approaches. Continue reading “Premature optimization is the root of all evil”
Accountability is one of those topics that sounds super easy but is the hardest to get right in practice. A recurring pattern in organizations is
- The top of the totem pole (exec team, org VP’s) get together and decide the strategy for the year
- It gets broken down into priorities and goals for the year
- Its gets documented and passed downwards via some process
- The entire organization references the document and should have visibility into priorities and be completely aligned
- Starting from the top every node in the hierarchy points to the document and downward and says I hold you accountable to this. This process continues until you reach the individual contributor at the bottom of the tree.
- The organization achieves 30% of what’s on the priority list
- The accountability stack unwinds upwards with the feedback that either
- The goals were not clear
- Stuff changed midstream
- Reasons why the goal was missed
- Go back to Step 1
This loop repeats like clockwork. Welcome to accountability theatre.
We need to have a great brand– Every startup
In the last few weeks, the tech world has been abuzz with GPT3. There has been a Cambrian explosion in demos that look super cool. A16Z has a great podcast that goes through the details that is a must-listen.
How GPT3 works. A visual thread.
A trained language model generates text.
We can optionally pass it some text as input, which influences its output.
The output is generated from what the model "learned" during its training period where it scanned vast amounts of text.
— Jay Alammar (@JayAlammar) July 21, 2020
You start by providing GPT3 a few example questions and answers that prime the model. After priming you can ask it questions and it correctly (mostly) predicts and generates the right answer. You could think about GPT3 as a super generalized inference model for text. You now how a generalized text-based interface that can understand what you are trying to ask/do well! Continue reading “A seismic shift in product management | GPT3 is the abstraction we deserve”
What is lending at its core?
What is Shopify’s business model?
When a management with a reputation for brilliance tackles a business with a reputation for poor fundamental economics, it is the reputation of the business that remains intact. – Warren Buffet
As I age in the business world, I have internalized this buffet quote. I superficially understood it early on in my career, but now I understand it! With fintech as the backdrop, this post is a view of my mental model on business models and gross margins in general. What makes a good high gross margin business?
Let’s start with a 30,000 ft view of what forms a business. Businesses exist to provide value to a set of customers via the products they create. A firm solves a need and customers pay them to solve that need. At its core, a company is a machine that takes raw ingredients (physical widgets, human capital, and intellectual capital) and transforms them into products that customers pay for. Raw ingredients cost money (cost centers) and customers pay money (revenue centers) for the finished product. A good business, in the long run, generates a consistent profit i.e (revenue – cost) is a positive number. Profit takes various forms such as free cash flow, EBIT or EBITDA – but the simple model holds, value creation only happens when what you get for the product is higher than what it costs to make it.
A question I wonder a lot about is, What is the long-run curve of a direct response paid marketing channel? The intuitive theory is that in the beginning, you expect your cost to be high relative to your LTV. The starting curve looks like the below
In this post lets delve deeper into the mechanics of channels. As mentioned in my previous post, do not start this exercise before you have locked down your product value proposition and positioning.
Think deeply about LTV and set guardrails
What does the economics of your business look like? The most important thing is to align on is the value of your customer to you. What is the long term value of the customer (LTV)? Don’t be confused by the term “Long”. It’s up to you on how long you consider a customer to be using your product. Early on in a startup, it is better to have shorter periods. The more mature you are, you will have actual data on how long users use your service. You have to start by nailing down the exact equation on how you calculate LTV. This also forces you to think about the unit economics of the business. The biggest issue isn’t in creating the equation for LTV rather it’ getting a broad agreement with the team on the equation. Everybody has to believe in the assumptions and understand the specifics of how LTV is calculated. Continue reading “Shouting from the rooftops, Channels 101 for Product Managers”