Low code/no code. Just another fad? What does it really mean for you?

Paul Doherty
6 min readMay 7, 2021

Low code. No code. PowerApps. UIPath. Workflows. Automation. You’ve heard the terms, you know the names. No code. It’s the latest industry buzzword. But what does it really mean for your business. Should low code/no code be part of your strategy. In this article I’ll take a look at what industry analysts are saying about the market leaders and provide our take on the state of play.

Over recent years, as a technology industry, we have been inundated with buzzwords, new vendors, unicorn tech companies and combinators pumping out software startups quicker than a 3D printer can print a concrete home. I know my google news feed is filled every day with news on new products, new terms and new companies - from AI and machine learning, to workflow automation and cloud platforms - it can quickly becoming overwhelming.

Microsoft have created a firestorm with its marketing machine, pumping out fresh content on why everyone is or should become a developer in the new normal in which we live. One could almost argue that we have entered a new-new-normal era of app development. Where global behemoths put the power of cloud, AI and machine learning in an easy to use interface, empowering everyone, everywhere to create.

But just because we can, does it mean we should?

Lets take a quick trip down memory lane and look to some of the guiding principles of software development to try to answer the questions that are yet to be asked.

In years gone by, before platforms existed to quickly develop software, apps and integrations, if you wanted to connect two or more disparate systems together to share data, you would engage a reputable development house, with a track record in software development, to uncover your requirements, design a spec, build a pilot and evaluate the business case. These projects were lengthy, complex, involved multiple teams, frequently required bolt-ons (or "enhancements"), to build your middleware application capable to translating how application Y needed to talk to application X. It was costly and fraught with danger and quite often, initiatives failed due to archaic data models, silos of information, unpublished or complete lack of API's and other hurdles encountered along the way.

And how each individual project was run, varied. While we have some standard practices for software development and testing such as Waterfall, SCRUM and Agile methodologies, it was really left up to the experts to influence or determine how software was built, tested and supported.

So then what is low code/no code? How does it change the game? Is it different from workflow automation? Where does AI fit in and how is that different to machine learning? And importantly, what should I do about it?

The Power Platform from Microsoft, to highlight one of several low code/no code platforms available today, enables us to use WYSIWYG tools to build user interfaces that connect to back end data through a standardised model or framework, namely, a database, a list (such as SharePoint lists) a data lake/pond/warehouse or a proprietary common data model such as the Microsoft Dataverse, which for all intents and purposes, is simply a cut down version of a database. But let’s not over simplify. The work that Microsoft has put into to developing a "one-size-fits-all" development environment is simply put - compelling.

With the Power Platform, Microsoft, have completed all the necessary grunt work behind the scenes, to enable you to simply create apps and user interfaces that connect to data.

So where does workflow automation, AI and Machine Learning fit in?

Well, in layman's terms, machine learning (ML) is the basis of AI and also a product of it (Schrödinger sends his regards). ML is a function, that operates within a set of rules, or uses a model rather, to enable machines to predict an outcome through classification of data. There is a great article on Towards Data Science that provides a good introduction to ML . Forbes tells us that AI, or the ability for machines to present as having the capability to make intelligent decisions, has enabled the rise of machine learning. One could argue that without data and a model, how was a machine to make a decision and learn from that decision in the first place?

When it comes to automation, and you consider the structure and capabilities of ML, you can now begin to understand how an AI platform, with access to a neural network such as what project Brainwave and Microsoft's AI builder offer, we can begin to see how building apps with a low code/no code platform, enables technologists to put the focus on the important issues - creating value.

Imagine an environment, where you can focus on building your app, leveraging the power of cloud, AI, ML, automation and deep neural networks to produce a solution that can learn how to identify business processes ripe for automation - and then execute the work. Always learning, always improving. Sounds compelling, right?

So then let's consider some use cases. Say I want to build an app or create a service that integrates my CRM, my marketing platforms, such as Adobe cloud, my website, PR and media releases, GoogleAds and CSAT results and exchange data between all these systems and present intelligent findings on a dashboard. With a low code/no code platform, all you have to worry about is plugging the pieces of the puzzles together, training your ML model, integrating your data and developing a reporting and presentation layer. Simple.

Well, maybe not.

There is a great video of an interview between Adobe and ServiceNow that talks about how together those two vendors have built integration and workflows to achieve a majority of what I have just described. That's great if you use both of those platforms. But what if you don't?

The Power Platform and the intelligent cloud that Microsoft have built is a fantastic set of products and tools. Likewise ServiceNow and Adobe Cloud. However the Power Platform, as you are now acutely aware, is just one component of the overall solution architecture. Especially when considering integrating AI and ML into your solution.

And it doesn't stop there. Gartner tells us that there are many more players in the market and some emerging leaders in this space to watch. So what do we make of it all? And how does one move forward?

Start with your digital strategy.

Over the last 6 years, Wrive have consulted with countless CIO's, CTO's, business leaders and organisations to assist companies with defing and achieving their digital initiatives. What we have found is there is commonality across all organisations at the beginning. Where do I start? How do we identify opportunities for digitisation?

There is another great blog piece on Power Automate Desktop that can help to answer some of these questions, however we like to draw on the guiding principles that are at the foundation of solution architecture:

What problems are we solving and is it a problem worth solving?

How will we manage the ongoing support and releases in our CI/CD pipelines?

What does our roadmap look like for the solution?

Will the product scale and how will our organisation support that scale?

How reliable or resilient is our code base?

You can begin to see how utilising no code/low code platforms will address some of these concerns and enable more agility in your development pipelines. However CX and UI development is simply one piece of the puzzle.

Ensuring you have the right partner to work with, underpinned by a clearly defined strategy, will go a long way to helping you deliver on your digital initiatives.

Good luck!



Paul Doherty

I am on a mission to help people and organisations create valuable, relevant, purposeful solutions that improve the way we work