Today I launched my first tech company. This is going to be a tough journey with a high chance of failure. We use some pretty cool tech, message me if you want to join. brian@iris.finance

or download the app at: https://www.iris.finance

Would love to hear from you.


We are always looking for ways to build products faster, cheaper, and better. Outsourcing development to India or China are things we think of to solve one of these, i.e. build it cheaper.

However, most experienced in doing this cringe at even thinking of the idea, resulting in an attempt to convince management to avoid offshore development, and for good reason. But what if I told you it is no longer a compromise, but in fact a necessity to be competitive. If done correctly, ofcourse. It will increase the speed, decrease the cost, and be built better.

Let me explain…


Graphql is TRENDING! Tons of companies embarking on new development are turning to graphql, which is why its growing insanely fast. However, most tutorials go over the basics and don’t include some powerful features. One of those features is called directives.

Graphql directives helps support reusable code and tasks. Those tasks can be authentication, permission, formatting, and plenty more. Because of the lack of how to implement graphql directives with apollo server 2, I decided it will be beneficial to the community to create this.

Here is the repo to the project that has all the code. Click Here

I…


If you are here you probably already know. You know that Graphql is FREAKING awesome, speeds up development, and is probably the best thing that has happened since Tesla released the model S.

Here is a new template that I use: https://medium.com/@brianschardt/best-graphql-apollo-sql-and-nestjs-template-458f9478b54e

However, most tutorials I have read show how to build a graphql app but introduce the common n+1 requests problem. As a result, performance is usually super poor.

Really is this better than a Tesla?

My goal in this article is not to explain the basics of Graphql, but to show someone how to quickly build a Graphql API that does not have the n…


It is REALLY interesting using a technology that is so new that you can hardly find solutions to the most basic of problems. Like where to start when wanting to use pinch zoom for the camera in Flutter. This will be a brief and basic example aimed at showing one where to start to incorporate that functionality.

Clone the repo for an example. Click Here.

Basically, you must add to your Widget a GestureDetector, and a Transform widget. I am assuming if you are reading this article you have already looked at the basic camera example, that flutter released.


I never thought it would come to this! What you ask? That I would be learning the language dart, after investing so much time and energy into perfecting coding in javascript.

However, after AirBNB just announced they are moving away from react native with some really good reasons, I decided to try Google’s hybrid solution, Flutter. You can read their post here.

Flutter uses the language Dart which is like a mix of javascript and C++.

In Dart they support asynchronous style of programming with callbacks, and what they call “Futures”. Futures are basically(not exactly) what promises are in javascript…


Google is once again leading the space and defining how we build and develop technology. The rush to be the leader in AI is no joke, and they are not waiting for anybody. They recently announced Tensorflow Serving, which is an API that easily enables Data Scientists to launch a pre-built super fast RESTFUL API to serve their models in a production ready environment. It includes the ability to serve different models, AND the ability to serve different versions of the same model at the same time. Too good to be true? Its Google, so no.

Getting Started

Google has made it…


MACHINE LEARNING is fun, right?? Well.. most of the time, but putting models in production sometimes sucks especially in a rapidly growing field like Machine Learning. How do you keep track of your models? How do you implement source control on your beloved models? How do you serve them quick enough for real life cases?These are some of the issues I am running into on cool top secret project at Walmart Labs, Finding good examples and documentation on this topic is challenging, so I thought I would share my findings.

Tensorflow Serving is the obvious and best solution to bring…


So many tutorials on Machine Learning… yet some don’t work, and virtually none of them prepare you to save the model for production use.

Tensorflow serving, is currently the best way to productionize AI, hands down. However, because it is so new, most examples are complex and incomplete.

This is especially true when it comes to saving a model to do classification in Keras for Tensorflow Serving(TF Serving).

If you just want to learn how to train a model and save it for TF Serving, Click here for a tutorial on how to do that for prediction, this one is for classification and is a bit more complex.

Brian Schardt

Associate Director of Engineering Warner Music Group

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