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

It's widely accepted that, in most cases at least, software systems should be modular, consisting of separate, discrete services. But what about the size of those services? How big or small should they be? This is where the question of service granularity comes in: too small and your system will become needlessly complicated; too big and you lose all the benefits of modularity you were seeking in the first place.

In this episode of the Thoughtworks Technology Podcast, host Ken Mugrage is joined by Neal Ford and Mark Richards — authors of multiple books on software architecture — to discuss service granularity. They explain why it matters and how software architects can go about getting it right, through the lens of granularity integrators and disintegrators.

Learn more about Neal and Mark's 2021 book Software Architecture: The Hard Parts (co-authored with Zhamak Dehghaniand Pramod Sadalage): https://www.thoughtworks.com/insights/books/software-architecture-hard-parts

Find out more about Neal and Mark's second edition of The Fundamentals of Software Architecture, set to be released in early 2025: https://www.oreilly.com/library/view/fundamentals-of-software/9781098175504/

Trying to measure developer effectiveness or productivity isn't a new problem. However, with the rise of fields like platform engineering and a new wave of potential opportunities from generative AI, the issue has come into greater focus in recent years.

In this episode of the Technology Podcast, hosts Scott Shaw and Prem Chandrasekaran speak to Abi Noda, CEO of software engineering intelligence platform DX, about measuring developer experience using the DevEx Framework — which Abi developed alongside Nicole Forsgren, Margaret-Anne Storey and Michaela Greiler.

Taking in everything from the origins of the DevEx framework in SPACE metrics, to how technologists can better 'sell' the importance of developer experience to business stakeholders, listen for a fresh perspective on a topic that's likely to remain at the top of the industry's agenda for the forseeable future.

Read the DevEx Framework paper: https://queue.acm.org/detail.cfm?id=3595878

Read Abi's article (co-authored with Tim Cochran) on martinfowler.com: https://martinfowler.com/articles/measuring-developer-productivity-humans.html

Listen to Abi's Engineering Enablement podcast: https://getdx.com/podcast/

Artificial intelligence has been presented as a technology with the potential to transform many different fields and professions. One of the most notable is design — but if we want to design in a way that's truly human-centric and inclusive, to what extent can artificial intelligence really help us do better work?

In this episode of the Technology Podcast, hosts Rebecca Parsons and Lilly Ryan speak to Thoughtworks design leaders Kate Linton and Esther Tham to get their perspective on how AI might be able to support designers. They discuss what AI tools could help the design process, how these tools could fit neatly into current practices and what the emergence of this technology could mean for design practices more broadly.

If you work in technology, you're constantly making decisions: not just what you should do, but also how you should do it. That's why we developed the concept of "sensible defaults" — practices and technology decisions that we generally see — in most scenarios — as the right way to do things.

Although we've been talking about sensible defaults internally for a few years now, we recently decided to share them publicly on our website. We did so because we believe it can help organizations think through their own approach to technology decision-making, something which is becoming increasingly challenging in a rapidly changing and complex world.

So, to discuss sensible defaults and explain precisely why we want to share them with the world, hosts Rebecca Parsons and Ken Mugrage are joined by Brandon Cook and Kief Morris, two Thoughtworkers that played an important role in putting our sensible defaults together. They discuss the origins of the sensible default idea, some examples, as well as the challenges of putting them into practice.

Explore Thoughtworks' sensible defaults: https://www.thoughtworks.com/insights/topic/sensible-defaults

Understanding your technology estate and how it's being leveraged is critical for organizations; it impacts everything from financial planning to capability development. But given the rapid pace of change — even inside a single company, let alone the wider industry — how can this be done effectively? One approach we've landed on at Thoughtworks is something called a Tech Dash: it's a method of internal research that surfaces information about an organization's technology use, and even software developers' experiences.

In this episode of the Technology Podcast, Camilla Crispim and Renan Martins talk to hosts Alexey Boas and Ken Mugrage about the value of a Tech Dash and explain how it can help track technology use. They also discuss where the idea came from and how they put it into practice across Thoughtworks Brazil.