Category: Uncategorized

I am not an economist, but I tend to believe there is a real estate bubble in Egypt. 

This bubble is mainly driven by the fact that buyers pay the down payment, few installments, sell the house at a higher price for someone who will finish the installments, repeat.

When the real estate bubble happened in US in 2008, some people could predict it by looking into the individual loans (mortgages) that people took and compared latency, and default rates to the great depression in 1920s.

The Egyptian situation is more complicated. The devaluation of the Egyptian pound is raising prices anyway.

Yet, I believe the crazy increase in prices isn’t only a result of what’s happening with the Egyptian pound.

The problem is there is no data to back my claim.

There is no data on default rates for real estate loans.

There is no data on occupancy rates of sold units. What’s the ℅ of buyers who actually live in the house?

There is no data on the average length of ownership. How long before a new house owner sells it?

Are there any indicators of sellers who had to lower the price to find a buyer?

This could be a great topic for investigative journalism. Someone who goes after real estate development companies, banks, buyers, sellers, and tries to find what’s going on.

Until this happens or the bubble burst, I will be the bubble boy.

Bonus: this post explains the mechanics of the current bubble (Arabic).

The Dutch complain about the weather all the time. 

The problem with the Dutch weather isn’t that it is too cold or too hot. It is totally unpredictable. 

You can literally see the four seasons in one hour. In one hour it could be hailing, sunny, rain showers, cloudy, then sunny again before it is back to cloudy cold.

One of the main drivers of uncertainty is the rain. You don’t know whether it is gonna rain or not, and for how long? If it is small drops now, will it get worse? Or stops? You don’t know.

The Dutch has a solution: Buienalarm

This app tracks your location and if it feels it is going to rain heavily where you are, it notifies you at least 30 minutes in advance.

If you go out at this peak you will get wet as if you just came out of the pool. Knowing this in advance is a life saver.

I still can’t figure out how it works and where it is getting the data from. The app can only predict 60-90 minutes in advance. Probably this is the reason it is this accurate.

It was only working in the Netherlands and Belgium, and recently it launched for Germany under the name “Drops”.

It is totally free which I don’t understand. There is no other app I know of that solves this problem with this accuracy. I would pay to use it.

Anyways, thank you Buienalarm, and welcome Drops. Hope you are as accurate as your father.

The first lecture I attended in computer science was about finite state machines.

A finite-state machine (FSM) or finite-state automaton (FSA, plural: automata), or simply a state machine, is a mathematical model of computation used to design both computer programs and sequential logic circuits. It is conceived as an abstract machine that can be in one of a finite number of states. The machine is in only one state at a time; the state it is in at any given time is called thecurrent state. It can change from one state to another when initiated by a triggering event or condition; this is called a transition. – Wikipedia

I met someone who is building a new app. The app is supposed to have different states depending on which action the user has taken. It is not a typical funnel overview although you can still see it as a funnel.

Looking at the screenshots I asked him, did you ever hear of FSM? Do you have a diagram for the different states of the app and the transitions between them?

I tried to draw an Uber FSM. Uber simplifies the experience by making the system on one state at a time, giving user the ability to take one action/trigger at a time to transition the system from one state to another.

This is what I came up with. It is not accurate as some of the states should be triggers like set location which after you do, you are still on the initial state.

You get the idea.

That’s the beauty of computational thinking. It is this ability to abstract concepts to the bare minimum, paving the way for clear thinking.

Sometimes I miss being an engineer.

I am surprised until now, Uber didn’t implement a messaging feature between the rider and the driver. 

SMS is still considerably expensive in developing markets.

The ability to send voice notes and maybe call over the internet could be even better.

I hope they are working on it.

There is a scene on the Egyptian streets where someone tries to stop a taxi. After stopping a few all of them refuse to drive the person.

Sometimes I wish there is a version of the Uber driver app where a driver can just pick up random people on the street, drive them, and the app calculates the fare. Think of it as a fare calculator.

Sounds counter intuitive, and stupid. But it might solve the problem of the lack of economic incentive to pick random people off the street.

If you have a weekend, maybe you should cyber it.

I am not happy by Twitter being sold. Big companies have a lot to preserve and Twitter is a place where ideas clash and controversy flourish. 

It is not easy to navigate a platform of opinions specially if you have a core business you want to protect.

I understand there are many problems the platform faces such as slow growth, slow product development, and moderation. I don’t understand how an acquirer is going to fix this.

Maybe I am wrong.