How loveholidays is making everyone a builder with Codex

Discover how loveholidays uses OpenAI Codex to make software development accessible across the business, helping teams turn ideas into products faster.

loveholidays⁠(opens in a new window) is a leading online travel agent operating across eight European markets, using its technology to process 60 trillion package combinations every day to help millions of people find their perfect holiday. Behind that scale is a technology platform the company has spent years building to make finding and booking a holiday faster and more flexible.

Now, Codex is changing who gets to build on it.

Product managers, designers, and commercial teams are increasingly contributing directly to loveholidays’ codebases. Teams can prototype customer experiences, make data and infrastructure changes, and turn ideas into working software without every request first having to enter an engineering queue.

“Everybody is a builder,” says Dmitri Lerko, Head of Engineering at loveholidays. “Making changes to our applications, infrastructure, and deploying code is no longer an engineering-only activity. Product managers, designers, and commercial stakeholders are driving value and making deployments.”

For Mike Jones, CTO at loveholidays, that’s part of a bigger ambition: building what the company calls the general intelligence for travel by combining its technology with the expertise of its people—and making both more accessible through AI.

“At loveholidays, our platform vision is to build the general intelligence for travel. That’s bringing together the great technology we have with our people’s expertise—and democratising that with AI and Codex.”

—Mike Jones, CTO, loveholidays

From an idea to a live customer experience

One of the clearest examples is Search Playground.

Previously, someone elsewhere in the business with an idea for a new customer experience would need to persuade an engineering team to prioritise a prototype. Every experiment therefore came with an opportunity cost: engineering time spent testing one idea was engineering time unavailable elsewhere.

loveholidays wanted to break that dependency.

Its engineers created Search Playground using the company’s design system, frontend technologies, and Codex. It gives people across the business a way to turn an idea into a working customer experience, gather feedback, and test whether it delivers value.

More than ten new search experiences have already been developed through the Playground. Most were built by non-engineers, and at least three are now running on the loveholidays website.

Another came from marketing. For its recent Crisps from Abroad activation, the team wanted an interactive microsite to gather entries for a competition and share holiday inspiration. Previously, it would have relied on an external agency to design and develop a standalone digital experience, adding cost and time. Using Codex and Search Playground, the team built the experience itself in hours, while maintaining loveholidays’ existing design system.

“We wanted to decouple our ability to trial new ideas from actual engineering time,” says Lerko. The result isn’t simply faster prototyping. It means more ideas can earn the chance to become products.

Putting specialist engineering expertise on tap

The same principle applies behind the scenes.

loveholidays’ Data Platform and infrastructure were originally designed for technical users. Making changes required knowledge of specialist tools, repositories, source control, and internal processes. When someone got stuck, a specialist engineer had to step in.

Codex gives loveholidays another way to scale that expertise.

Engineering teams encode their best practices, instructions, and validations into workflows that Codex can guide other users through. Instead of needing to understand every underlying system, employees can focus on what they’re trying to accomplish while Codex helps propose a change, run checks, and guide it through the release process.

“We codify all the best practices. We codify validations, and continuously improve them as reality changes,” says Lerko. “The expertise of our data and infrastructure engineers is available through Codex—so anybody self-serving their infrastructure or data needs gets that expertise on tap, 24/7.”

The results are measurable.

Successful AI-assisted changes to loveholidays’ Data Platform have risen from 58% to 93% over the last year. At the same time, the team is seeing four times as many Data Platform changes for every support request.

Across its broader self-service infrastructure workflows, success has increased from 63% to 90%.

That changes the job on both sides. Teams can move without waiting for specialist help, while engineers spend less time troubleshooting routine requests and more time improving the platform itself.

“The more work you can hand off to AI, the more your job elevates. Your job isn’t to be handed a solution and implement it anymore. You have to get involved in the business problem.”

—Mike Jones, CTO, loveholidays

More software, without more engineers

That shift is showing up across loveholidays’ engineering organisation.

A year ago, around 7% of its code changes were AI-assisted. Today, that figure is 79%.

Over the same period, deployments have increased 73%, while engineering headcount has remained broadly flat.

For loveholidays, that capacity isn’t about producing more code for its own sake. The company deliberately measures AI against business outcomes rather than adoption alone.

“Technology is just a means to an end,” says Jones. “It’s not about the technology itself; it’s about the impact it has. We’re intentional about not just giving people access to tools, but helping them solve business problems—and measuring the impact.”

Some of that impact is already visible in the bottom line.

With more capacity to tackle optimisation work that previously carried too high an opportunity cost, loveholidays’ Data Engineering team has reduced cloud storage costs by around £36,000 a year and is saving approximately another £100,000 annually by reducing data-processing waste.

And the bigger effect may be what teams now consider possible.

“We’re noticing that what used to be too hard is now ordinary,” says Lerko. “The implication is that what’s too hard now will become more ordinary.”

Building the general intelligence for travel

For loveholidays, Codex is increasingly becoming a common interface between its people and the technology underpinning the company.

“Codex is becoming a single control plane—a single interface shared by engineers, data scientists and the business,” says Lerko. “There’s a lot of power in that, because you no longer need to teach everyone a different tool.”

That points toward a different model for building software: one in which specialist expertise can be made available across an organisation, more people can turn ideas into working products, and engineers themselves can move further up the problem-solving stack.

For loveholidays, that’s ultimately what “general intelligence for travel” means: combining the technology it has built with the expertise of its people, then making both available to more of the business.

And with Codex, the distinction between the people who have ideas and the people who can build them is beginning to disappear.