2 min read

LLMs are changing the nuts & bolts of software development

LLMs are changing the nuts & bolts of software development

The 21st century has been all about software development and still the present moment has sparked a new kind of techno-optimism.

The nuts and bolts of software are transforming because (for the first time) we have intelligent and responsive materials to play with.

Marc Andreessen says in the Techno-Optimist Manifesto, “We believe Artificial Intelligence is our alchemy, our Philosopher’s Stone – we are literally making sand think.”

LLMs are responsive, intelligent, complex pattern-matching machines with access to a sea of knowledge. Their adoption is bound to be similar to historic discoveries of new materials: bronze, iron, plastic, silicon chips, etc.

At KushoAI, we’re training LLMs to refine their patten matching abilities and aim them at specific purposes. The beauty of this approach is that you now have an intelligent counterpart that is really good at doing a task you’d rather skip. You can turn up the frequency of work you enjoy and delegate the rest.

Fixing small bugs? Testing? Ensuring release stability? Kusho's models are trained to understand API context, generate and execute comprehensive tests, and provide analyzed results for debugging, all in sync with the deployment process.

Each time you ask a developer which part of their job they'd rather delegate — testing is often the first answer. It’s a long-standing question in fast-shipping engineering teams: should we test more thoroughly or fix things on the fly as & when they break in production?

The consequences are borne soon enough with bugs that cause a loss in revenue and lead to bad customer experiences. Though, we’ve all settled into this compromise by now.

Our job is to ensure that you and your teams don’t have to compromise. Do you want to ship high-quality products at speed backed by stable releases? Now you can.

The Kusho model has refined pattern-matching abilities to ensure that the coverage and accuracy for your backend APIs are the gold standard. It adapts to the context of your codebase and it shouldn’t take more than a few hours for your organization to run Kusho autonomously.

Think of a transition we’ve all pretty much experienced: Cassettes —> Walkmans —> MP3 Players (iPods) —> Bluetooth Headphones — > Wireless Bluetooth Earbuds (AirPods). The measure of progress is a new capability, performance, and intuitiveness per unit of time.

We’re using LLM-trained special-purpose models to unlock new capabilities, greater performance, and higher intuitiveness per unit of time for your tech teams.