Volume 31 of the Technology Radar will be released on October 23, 2024. As always, it will feature 100+ technologies and techniques that we've been using with clients around the world. Alongside them will be a set of key themes that emerged during the process of putting it together. We think they offer another way into the Radar and give a unique insight on some of the most interesting issues impacting the software industry.

In this episode of the Technology Podcast we discuss them: coding assistance antipatterns, Rust being anything but rusty, the rise of WebAssembly and what we describe as the "cambrian explosion of generative AI tools." To do so, Alexey Boas is joined by guests and podcast regulars Ken Mugrage and Neal Ford. Ken and Neal provide an insight into the conversations that happened during the process, and offer their perspective on the implications of these themes for the wider tech industry.

The Thoughtworks Technology Radar is, first and foremost, a publication. It's a document that anyone in the tech industry can read twice a year to learn about our experiences and perspectives on technology. However, it's also more than that: it's built on top of a process of deliberation, discussion and curation. We think that's particularly important — it's something we encourage technology teams and organizations to do and which we support with our Build Your Own Radar tool.

On this episode of the Technology Podcast, Neal Ford and Ken Mugrage join Prem Chandrasekaran to discuss Build Your Own Radar. They outline why the Radar process is just as important as the artifact that gets created at the end, and explain how organizations can use it to facilitate conversations about how and what technology they use and want to use in the future.

Learn more about Build Your Own Radar: https://www.thoughtworks.com/radar/byor

There are no shortage of options when it comes to relational databases. While the likes of PostgreSQL have proven enduring, even as the market has evolved, for data scientists and data engineers that need to manage and query particularly complex or large data sets, the most popular databases aren't always right for the job. Thankfully, this is where projects like DuckDB can help. Built for what's called 'vectorized query execution', it's well-suited to the demands of online analytical processing (OLAP).

To get a deeper understanding of DuckDB and how the product has developed, on this episode of the Technology Podcast, hosts Ken Mugrage and Lilly Ryan are joined by Thoughtworker Ned Letcher and Thoughtworks alumnus Simon Aubury. Ned and Simon explain the thinking behind DuckDB, the design decisions made by the project and how its being used by data practitioners in the wild.

Learn more about DuckDB: https://duckdb.org/why_duckdb.html

Explore Ned and Simon's book Getting Started with DuckDB: https://www.amazon.com/Getting-Started-DuckDB-practical-efficiently/dp/1803241004