The rage of the (app) machine: unlocking developer productivity in a world of apps

Even though I utilize SPAM filters, I still get several unsolicited emails a week asking if I want a new app developed. The combination of cloud and SaaS has made it vastly easier to create apps, which are an encapsulation of physical machines and the code that runs on top of them. But from a maker’s [meaning developers, product managers, general managers, and founders] point of view, we’re experiencing a rage of the machines that is making work harder, not easier.

Many startups are funded every year, and most of these companies generate apps of some kind. Crunchbase data shows that over 2021, investors put $329.5 billion into startup investments across all stages. Today, with tools like open source libraries, AirTable, low code, and no code, someone can write an entire app very quickly with minimal (if any) coding. But when an enterprise adopts a new app, they need a specialist to manage it, creating more complexity and organizational layers.

These machines lack intelligence as they work in isolation and without recognizing context. A log might generate an alert that someone views and then determines the app has a bug, and it’s randomly assigned to a developer. This process creates both a lot of noise and mindless work.

Or, a customer might be upset with a company’s service and rants on an app like Twitter, even though the problem has nothing to do with actual functionality. The CEO sees it and shoots a message to the COO that there must be a problem, and the unhappiness trickles down the executive hierarchy until the C-suite holds a meeting that includes developers. In that meeting, it’s finally determined that the Tweet was simply a rant, and nothing actionable needs to happen.

The abundance of apps in today’s organizations has created more work than ever for devs. Sales and marketing use apps that tell them about customers from the customer perspective, and so does product marketing, along with other teams. Each of the apps used eventually comes to the back of the kitchen, meaning more work for the devs.

Converting Confusion into Delight

Today, the surplus of applications generates a cacophony of noise, inefficiencies, and duplicate work. Shouldn’t there be something we can do to fix it?

We live in the “age of AI” — this HBR article from late 2021 notes adoption of AI has skyrocketed over the last 18 months — so machines should be able to recognize a duplicate, an actual issue, or just a rant (which would require nothing actionable). An ideal state is when we apply intelligence to the issue and assign it to the right person — ideally, the person who did the recent coding. If it goes to the right team member, this developer is far more likely to resolve the issue faster than someone randomly assigned to it. This means enhanced efficiency and more time freed up for developers to work on relevant projects that drive a higher ROI across the organization.

To turn rage into delight, intelligence needs to be applied to replace this noise. For example, if developers write an app, they rely on libraries which have their own versioning system. Say an app breaks because the library uses an old version; the fix could be as simple as upgrading the library to a recent version. The machine should automatically figure out if it’s a real issue, apply the fix if possible and then notify the developers to approve/reject the changes. Think of this as similar to a bot working off a Google Doc article that spots grammatical errors, proposes the fixes and notifies the user, thus eliminating all the human driven processes.

It should also be able to determine if there’s an issue with the exact same problem somewhere else. With the right tools, ultimately, the maker is happier, and so are all employees and customers.

Solving the Rage of the Machine in Practice: a Real-World Example

A developer shared his experience of churning out feature after feature with an already burned-out team — a process that created internal chaos and stifled innovation. The team was executing on the playbook to become another unicorn, but when the rubber met the road, things started to spiral downward. They couldn’t convert free users, and the few that converted churned very quickly. The big accounts for whom they made all the features told them all they had were “table stakes, but no differentiation from the current product they used.”

The slow revenue growth quickly demoralized the already overburdened team. Such is the story of countless SaaS companies who don’t get to the elusive product-market fit. Churning out features has become easier with the cloud and open source, but it’s even more important to differentiate and show value to your customers quickly. The traditional siloed approach of customer requirements and feedback between the front and back office leads to data overload and information loss which causes misaligned priorities and goals.

It takes the right technology to gain control and solve the rage of the machine. There is a new school of thought emerging around the notion of a Developer-focused CRM. Imagine a system that connects the developer to the customer through the product. The machines, powered by AI, prioritizes all work items by the impact to the company so that developers can focus on what matters.

Today, a system like this only exists when you connect 10 different apps across task management, support tools, code repository, and traditional CRM with custom code. However, there is a new breed of companies that is actively working in this space to make this into a seamless platform. Most of these startups are focused towards companies that see themselves as product-led, for example, Prodcamp and Calyxa.

Yet, not all of these are targeted towards the developer persona. One such company is DevRev that came out of stealth a few months ago and promises to be building the first Dev CRM aka CRM for developers and promises to connect the trinity of developer, product and customer. According to their website, they plan to use AI to make work for developers more meaningful by removing barriers between the developers and their customers.

Powering Teams with Intelligent Software

Turning machine rage into delight requires applying AI and harnessing the right technology to keep developer teams most productive. Companies like DevRev are at the forefront of our next evolution of software involving intelligent machines that empower teams with the tools they need to do their best work. It will be interesting to see how solutions like these shape the next generation of product-led companies.