Among the questions a head of technology may ponder are, what does it mean to be innovative, and perhaps, what technology can be used to drive an innovation strategy?
Given the main way people tend to place bets with Bet365 is via its mobile app, Alan Reed, head of platform innovation at Bet365’s Hillside Technology platform, says: “As part of the remit of platform innovation, we look at the world beyond the phone.”
In a recent Computer Weekly podcast, Reed talked about how generative artificial intelligence (GenAI) changes the way people interact with computers. “We are looking at the future of the workforce, and one of the things we have access to is the Ray-Ban Meta AI glasses.”
For Reed, one of the breakthroughs this technology offers is access to the Llama 4 large language AI models, which, he says, is simultaneously amazing and quite terrifying. “You can literally look at something, such as if you’re in a restaurant and you can’t translate the menu, and it will speak it into your ears.”
While he sees uses for such technology, Reed concedes that it raises privacy concerns.
It represents an interesting adaptation of the human-computer interface. The graphical user interface (GUI) that applications are built around, to paraphrase Sam Altman in his YouTube advert with iPhone co-designer Jony Ive, does not represent the best way to get ChatGPT to answer a question. The Ray-Ban Meta product shows the possibilities of using a voice user interface rather than relying 100% on a GUI, whether that is running on a PC or a smartphone.
“We’ve used our phones for the last 15 years to do anything other than speak to other people,” Reed adds, “But thanks to generative AI, we will want to use the phone button on our phones again.”
What to do with GenAI
Like many businesses, Bet365 is exploring how to use GenAI. For Reed, at an empirical level, a foundation model is something that reads the internet and turns the information it gleans into data, which can then be reconstructed into sentences when queried.
For the past few years, the betting company has been looking at using a large language model for coding, before it became one of the key use cases. “It’s very obvious what can be done in the coding space,” he says.
But while writing code is great, Reed says: “What we were more interested in is, if it could read code, what could you understand?” The particular problem Bet365 wanted to tackle was having the ability to understand its code base without the need for someone to read the code themselves.
“Like any large tech company or organisation that’s been around for a number of years, you start to think of your technical data and your legacy code base, and that there is a percentage of your workforce just maintaining this legacy code base,” he says.
“Once you can get a level of comprehension from the AI, you can start to look at a value construct against your code and ask the bigger questions”
Alan Reed, Bet365
The maintenance challenge is that people’s understanding of how an application is programmed diminishes unless they frequently look at the code. “Every now and again, you realise you don’t understand the code to the degree you need to for the task ahead,” he says, referring to the difficulty in maintaining application code long term.
There is another benefit: if the AI can understand the code, both as content and contextually, it becomes a powerful tool for IT transformation projects. “Once you can get a level of comprehension from the AI, you can start to look at a value construct against your code and ask the bigger questions,” says Reed.
Not only can GenAI be used to improve the maintainability and portability of code bases, but it can also help to identify common blocks of code to aid migration efforts.
Referring to Bet365’s migration programme, Reed says: “Over a period of time, we put a lot of our business logic into databases. One of the things that we’re looking at as we do a platform migration is to modernise this code in a similar way to how we did the cloud migration.”
Summarising databases
Given that it can read and understand code, Reed wanted to see how well GenAI could be used with the code base for documentation. While a GenAI tool provides chat-oriented programming and can understand the code base, Reed says it lacks an understanding of localised knowledge, which led the team to retrieval augmented generation (RAG).
“RAG is just the idea of supplementing whatever the large language model has with your own nuance, your own documentation, your own standards, and your own thought processes,” he says.
A paper published by Microsoft on how to use GraphRAG, which combines a graph database with retrieval augmentation generation, showed Bet365 a way to summarise its databases and the business logic coded in these databases.
Reed says the technique effectively builds a knowledge graph of its databases. “We put in everything we could think of that would be useful to a developer,” he adds, which allows developers to query the code and get back a meaningful response.
Reed says the system provides additional information such as which database tables are used the most and which databases use the most processing power. “We wanted to understand logical reads, physical reads. We wanted to make it a very, very rich model.”
Such information is key when ascertaining which parts of the IT infrastructure should be modernised to maximise value. Given that a database that has been around for several years will almost certainly be connected to numerous other databases that are also intertwined, working out what is going on is extremely difficult, which is why an AI tool that can read and understand what is going on inside a database is useful for Bet365.
“We almost immediately realised it was a fabulous way of showing people the size and scale of the issue they had in front of them. It was a very good way of getting a message across,” says Reed.
A careful path to tech innovation
Innovation may well be a dish that is best served cold. There are certain tech breakthroughs, like AI glasses, that grab public attention and can indeed offer a route to innovation, but truly innovating with AI requires careful consideration, as Reed has shown.
It may not grab the headlines, but having an AI that not only understands code and databases, but also enables developers to ask technical questions of the code, shows the potential of AI to do much more than augment workflows and existing business processes.
