One of the welcome additions to Amazon’s AWS offerings is a simplified server provisioning service to compete directly with Digital Ocean called Lightsail.  Lightsail provides a nicer web UI for launching instances, many quick launch options for common apps like WordPress or GitLab and simplified billing (yay!).  With Lightsail you don’t need to pre-pay for Reserved Instances to get a good price on an EC2 server.

Dokku is mini heroku you can run on your own servers.  It uses the same buildpacks that Heroku does to enable git push deployments. By building on top of Docker a collection of available dokku plugins make it easy to start up databases, caching or tie in other services.  In this tutorial I add Postgresql and get an SSL cert using Let’s Encrypt

Together, Lightsail and Dokku create an easy way to manage your application deployment on an inexpensive server.

Get started on Lightsail by starting up a new virtual server:

And then selecting an Ubuntu Image:

There’s a spot here for ‘Add launch script’ where you can drop in these commands to automatically install dokku on first boot:

sudo DOKKU_TAG=v0.7.2 bash

Give it a name and press Create to start booting up the server. You should be able to SSH to the new server very quickly though you can connect before dokku and package updates have been applied (it’ll take a couple minutes for the dokku command to become available)

After a couple of minutes have passed and things are installed and running visit your server in a web browser:

For the public key you’ll want to grab the key on your computer.  if you have linux or macOS you can grab the contents of ~/.ssh/  If you need to generate a key there’s a good How-To on Github about generating them.

Set the hostname you’ll use for the server if you have one and Finish Setup.

Next step is to SSH to the server and fiddle with it there using the private key you can download from Lightsail:

ssh -i LightsailDefaultPrivateKey.pem ubuntu@<YOUR PUBLIC IP ADDRESS>

And create the app you will be deploying:

dokku apps:create your-app

Add a postgres database (there are other great plugins available for dokku too)

sudo dokku plugin:install
dokku postgres:create database-name
dokku postgres:link database-name your-app

Now, back to your local app add a git remote to this new server and deploy it:

git remote add dokku dokku@<PUBLIC IP OR HOSTNAME> your-app
git push dokku master

If that is successful then the project should be visible online. Yay!

Then there are some next steps to help complete the app. Set any environment variables you need for the app:

dokku config:set your-app ENV=prod

You can install an SSL cert using Let’s Encrypt very easily:

sudo dokku plugin:install
dokku letsencrypt your-app

You can configure some pre and post deploy hooks inside the app.yaml file in your project repository to run checks or execute database migrations.

That’s about it! git push deploys to update your project whenever you want.

Recently I’ve been interested in finding a business investment – something like a B&B that allows me to put some of my retirement savings into a business that I have some control over its success.  The normal process for something like this would be to write a business plan or at least do some back of the envelop estimations for how much revenue is expected from the property.

The usual tool of choice is a spreadsheet.  And those are excellent ways to work through the numbers and visually see things.  However, the flexibility of a spreadsheet is somewhat limited for even more advanced analysis.

I wanted to take things to a different level.

What information could I get from looking at the market and scraping webpages that I could feed into a bigger model to see how other owners of similar businesses do.  By pulling in 1000+ comparables and running them all through a similar model to estimate each of their profitability it becomes possible to identify the traits of a successful business.

Applying this sort of ‘big data’ analysis is proving interesting.  There is an amazing amount of information freely available on the internet, but much of it exists in different silos.

In the example of running a B&B, there are lots of them listed on and similar travel booking sites.  These provide a partial picture of how popular a place is (from it’s availability) and the revenue (from the cost to stay there). Another big piece of the picture is the costs – which you can estimate by checking real-estate listings.  By putting all this information you can see many interesting things.

If your model is accurate then you can get answers to these questions:

  • What percentage of B&Bs turn a profit each year
  • Is there an optimal size / number of rooms
  • which attributes of the property correlate most to it’s profitability

You can take a deeper dive into the best performing properties to see if they do something unique – do they have nicer websites / photos? Do they do aggressive advertising? Are they active on social media?  Answers to these questions can help you find the strategies that are working best in the market – and perhaps things that are a waste of time.

This type of analysis is something I think more people should be doing.  It provides some competitive advantage in terms of the information that you bring with you into a potentially big investment, and reduces the risk that you inadvertently buy a lemon.


There’s nothing quite like the feeling of starting a new project idea and seeing it all the way through to finished and published.  It’s a feather in your cap that you can look back on and say “I built that”.  Regardless of if it is a big hit or not, it will make you a stand out – very few people get something all the way to done on their own.

Ambition can act against you in this.  The larger the project the more opportunties there are to hit roadblocks which derail it. The size of a project is a risk that should be minimized.

That’s why I believe it’s important to create momentum with smaller projects.  A small win still gives you a great amount of confidence.

This applies both to home projects, or code projects or hobbies.

Small is a relative term.  You may be able to handle a small 40 hour project, while someone else cannot yet tackle something that big.  Small may be as simple as fixing a wall hook or creating a pull request to fix a typo in the documentation of an open source project.

By putting a lot of these small projects together you create something bigger than the sum of them.  Fixing all the small things around your house can turn it into a relaxing home, Contributing to Open Source projects could gain you some notoriety and help you get a dream job.

Derek Sivers said “the best option is the one with the most options” and doing many small projects gives more options than one big one.

37 signals (now basecamp) started out with 6-10 individual products. When starting they didn’t know which would be a success so creating many smaller ones diversified their risk and helped them succeed.

Small projects are going to be a core part of my strategy for 2017.  Launching micro-sites, simple tools, or open-source libraries that can be finished in 8-10 hours of effort.

Think small, get out there, and finish it.  It’s a step to something bigger.

Lately I’ve been thinking back on the past business opportunities that have been explored and which ones have been more effective than others.  This story about the confessions of a Google spammer reminded me of a project I attempted to build back in 2012 to build and control and automate lots of blogs. My project was much more whitehat than spamming google but it landed at the same time that Google cracked down on similar blog networks with their penguin update. It made me think about what ideas have worked best and worst of the things I’ve tried over the years.

By far, the easiest and most straight forward business ventures I’ve done have been consulting and freelance work.  People understand how this works so it’s easy to sell. “oh you need a website built? I know how to do that – will you pay me to do it for you?” That’s a great base for business and been the largest single source of income for Halotis. Companies are comfortable paying for your time and expertise to create new things and they’ll pay as long as you can convince them of your time availablility and expertise.

iPhone Apps were the next biggest success.  Getting in early and leveraging the distribution of the iTunes App Store was a big win.  Lack of time to maintain and improve the apps and the influx of AAA quality competition eventually killed things for me.  Now it’s too hard for a single developer to do without a lot of luck.

Creating real products and services were another profitable option for me. I used Product Launch Formula to help strategize a couple of sales which were a big success.  Big launches attracted a bunch of sales that ended up becoming a real product business.

Ad supported and affiliate sales based websites have been break even for me.  They cover the hosting costs – which is to say almost no money.

Those have been my biggest lessons.  Hopefully that is helpful to readers who are thinking about their own businesses.


The more that I learn about Deep Learning and other Machine Learning concepts the more intrigued by the idea that we could apply some of things we learn about how these ML models behave back onto human psychology.  This is not something I have heard discussed yet. They were, after all, roughly modelled on how our own neurons work and could be considered a crude model of how we work.

What are some of the behaviours and lessons we’ve learned from training AIs that could be applicable to how we learn for example.  AIs are obviously dramatic simplifications of our own minds but they learn in similar ways.

Machine learning algorithms can be divided into supervised and unsupervised learning models.  They are not equivalent and the things you can do with one are not possible with the other approach. Would it be helpful to identify topics in school that can be associated with each approach so that we can optimise our teaching approaches?

A concrete example of this is how we learn a new language.  A common suggestion for language learning is to immerse yourself in it.  To that end people will listen to radio and music in their target language. Is that an effective way to improve your understanding?  This would be considered mostly unsupervised since we have no answers for what a particular sound we hear might mean (unless we can guess from a context of other words we already know).  If we fed 10,000 hours of voice recordings into an unsupervised machine learning algorithm what kind of things would we be able to learn?  It might be able to pick up some common words or phrases that are used, it might be able to find words that are often used close together.  It would get a feel for the ‘sound’ of a language.  But that is likely as deep of an understanding as it could make.

Given this insight we could hypothesis that immersing yourself with just recorded audio is not particular effective at learning what words mean.

If we wanted to teach a computer to hear a word and turn it into text we need to have the sounds and the matching text.  This is a supervised approach and can be quite effective. However, we know that this is much more effective if we have lots and lots of training data.  For a particular word it helps to have the word spoken by many different people, spoken quickly and slowly, varying pitches and accents.  The more examples we have to train on the better the accuracy is going to be.  You’ve probably experienced listening to a song and hearing a word you can’t quite make out. You listen over and over but still can’t get it. Then someone else tells you what the lyric is or you hear a different recording of the song and suddenly it becomes crystal clear.  Now you can hear it.

Given this, perhaps we could ensure that training programs on a computer don’t just replay the same recorded words over and over again but instead give lots of variations.  It would be interesting experiment to have a 1 page story in your target language recorded by 10-20 different people. Would listening and reading along to all the recordings help with your listening comprehension?  How much better would you learn listening to 1 recording 20 times vs 20 different recordings?

Several studies have looked at the efficacy of same-language closed captioning to reading and listening comprehension and prove that it can help.  Similar application of supervised learning applied to people.

Another area that generates much concern in machine learning is how to identify and prevent over-training.  Over training happens when the algorithm essentially memorises the answers and has difficulty applying to new input it hasn’t seen yet.  There are techniques for testing that are used to help diagnose over training. One such approach is to separate the training data from the testing data.  Trying to determine if students have memorised the answers or really understand a concept is critical to their ability to move forward and build on those lessons. Could we apply our machine approaches to humans to help identify memorisation vs understanding?

I’m sure there are more fascinating ways we could take what we have learned from teaching machines and apply it to how we teach people.

Time is our one major limited resource and so it’s important how we decide to use it.  One of the biggest questions we ask ourselves as developers is often what kind of cool stuff could we do on evenings and weekends.

Here are my considerations for any side projects that I feel are worth saying ‘yes’ to.

  • It should align with your broader goals
  • It should ideally provide an incremental step towards those goals
  • It should be fun and interesting
  • It should have a number of quick wins
  • It should be something that you can’t or won’t get experience with during work hours

One thing to consider is conflicts with your job.  It would suck to be working on a passion project at night and find the need to hide it from co-workers and your boss or risk some sort of discipline. Co-workers can be great sounding boards and strong supporters of your success with these personal projects and it’s awesome to be able to take advantage of that.

The key to being one of those people who seems to get a lot of stuff done is to be continually walking in the same direction rather than running scattered from place to place.  It’s not as easy as it sounds.  There’s always a new hot idea to pursue or a reason to give up on the project you haven’t yet finished.  For that reason it is good to pick a project that hits as many checkboxes as possible for you and that you believe you can see through to the end.

One of the most understandable agreements is that we trade our time for money.  This is the standard that most employees agree to when they take a job.  They are selling their expertise and trading their limited resource of time to the company for a salary.

There are ways to get your time back by de-coupling income from time.  What kind of things allow you to get paid without requiring time?

Products are perhaps the most obvious option.  There are products that can be created or replicated (software) that do not require incremental time to deliver to a customer.  Automated services can help customers without a human’s time involved.  Brokering deals can generate large commissions with very little time effort.

Recently I did some financial analysis of business models to see how they might work out if I decided to pivot my business efforts.  I was trying to understand the costs and risks associated with a consulting business compared to a product business or a hybrid of the two.

The resulting insight made me rethink my priorities and preconceptions.

The value created by a moderately successful business can be astonishing. A business that generates a profit of $5k/month would make $60k/year and might be able to sell for $300-$600k to be acquired.  How long would it take for a lone developer to create such a business? Working 40-60 hours/week could you create something in 3 months? 6 months? 12 months? That has potential for this kind of revenue?  If you figure it would take a year to accomplish would you be willing to use $60K of your savings to bootstrap it?

With the right product idea once launched you’d be able to scale back development work and maintain the business and the steady trickle of income it generates.  Or sell the business for the capital gains.

The consulting business on the other hand may present less risk and a shorter path to profitability, but as a single developer consulting your ability to sell the company would require you to transition to a job to maintain the cash flows.  As a consultant you remain tied to the dollars for time equation and experience has showed me that doing both consulting and products is a difficult balance.

Finding time to live, to succeed, to love, to eat, to play, to work, to read, to escape is a perpetual set of trade offs we all have to make every day of our lives.  Finding a balance between all the things we need to do and the things we want to do is not simply about deciding yes or no to a list of things.

We all have to deal with human psycological falicies that affect our decision making.  Turning down a bowl of ice cream is much more difficult than a bowl of brocolli.  This subconsciously plays into all of our momentary decisions.

At every moment of the day we have the opportunity to make an infinite set of choices for how we spend the next moment. I could continue to write the next sentence in this blog post or stand up, go to the airport, buy a one-way ticket and move to Thailand.

The choices truly are endless and yet most of us find a pattern and stick to it.  Work 9-5, eat 3 meals a day, watch TV and go to bed.  How uninspiring.

Everything with time requires a trade-off.  Most of us trade the productive hours of the day for money instead of being with our families, we trade progress on our goals for watching re-runs on TV.

Breaking out of these habitual patterns is hard.  It requires mental effort to make decisions about how to direct your life.  The people who do it are often so far ahead with their accomplishments that they truly stand out.

Of course we will never get more time.  We must do what we can with the time that is given to us.

A goal without a process to back it up is just an idea.  It is the process which actually will help you reach that goal and it’s more important to focus on developing on an actionable process than to have the best idea or goal.

A business idea is worthless unless you do something with it.  The process you come up with could be to start a business around the idea, or to licence it to someone else.

If you had a goal of running a marathon but skipped the process of signing up for a race and training for it then it’s likely that your goal would sit on your bucket list until you abandon it.

Though it’s also the case that parts of the process also entail their own sub-goals. The process of training for a marathon involves sub-goals of going out several times a week for a run. It’s worth considering what the process would be to make sure the training happens which might require carving out some time from other priorities.  If these processes don’t happen it puts the goal at risk.

Consider your own goals, do you have processes to back them up?  Are those processes actionable given your time and money contstraints?

Personal passion is an undervalued driver of productivity. Experience has taught me that when you work on something that you are passionate about it becomes easier to focus, you care more about the quality and are less distracted.

If you can find your passion, it means you will never have a job – Richard Branson

When someone is extremely passionate it becomes possible to do 60-80-100 hours a week and not feel drained of energy. It is a powerful motivator and one which many businesses could stoke.  Although getting more overtime hours out of your employees isn’t a goal we should strive for.  Passion can overcome the draw of Facebook or milling about at the water cooler.  This can produce substantial gains.

The six-hour-work day increases productivity

Sweden is proof that there is still much productivity to be gained from the hours we do put into work.  Working fewer hours per day can help many people maintain the energy they need to stay focused and committed. The math of productivity is not simply about working harder and longer.  Finding other ways to drive energy such as cultivating passion in yourself and your employees can have a similar effect.  Getting stuck in a perpetual mid-afternoon slump is something that everyone should avoid.