Thoughtworks Technology Podcast
by Thoughtworks
Is this your podcast?Insights from recent episode analysis
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Insights are generated by CastFox AI using publicly available data, episode content, and proprietary models.
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Total monthly reach
Estimated from 11 chart positions in 11 markets.
By chart position
- 🇬🇧GB · Technology#1265K to 30K
- 🇲🇽MX · Technology#2530K to 100K
- 🇰🇷KR · Technology#3530K to 100K
- 🇮🇳IN · Technology#6610K to 30K
- 🇳🇬NG · Technology#623K to 10K
- Per-Episode Audience
Est. listeners per new episode within ~30 days
42K to 148K🎙 ~2x weekly·100 episodes·Last published today - Monthly Reach
Unique listeners across all episodes (30 days)
84K to 295K🇲🇽34%🇰🇷34%🇬🇧10%+8 more - Active Followers
Loyal subscribers who consistently listen
25K to 89K
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* Data sourced directly from platform APIs and aggregated hourly across all major podcast directories.
On the show
From 15 epsHosts
Recent guests
Recent episodes
Open-weight models: What are they and when should you use them?
Sep 3, 2026
Unknown duration
AI-generated code: What has to be true for us to trust it without looking at it?
Aug 20, 2026
Unknown duration
Scaling the enterprise harness: How to achieve AI agent controllability across an organization
Aug 6, 2026
Unknown duration
Embracing hybrid AI: How Lenovo is leveraging local, on-device AI
Jul 23, 2026
Unknown duration
What does the future of software engineering look like?
Jul 9, 2026
46m 25s
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| Date | Episode | Topics | Guests | Brands | Places | Keywords | Sponsor | Length | |
|---|---|---|---|---|---|---|---|---|---|
| 9/3/26 | Open-weight models: What are they and when should you use them? | We've seen a huge amount of increase in interest around open-weight models in 2026. The reasons for this are multifaceted, ranging from the switch to per token billing, the evolving privacy landscape and improvements in open-weight model capabilities. To unpack open-weight models and explore why and when we might want to use them, host Ken Mugrage is joined by Thoughtworkers Caer Sanders and Andre Almar. They discuss everything from the precise definition of the term and how they compare to other kinds of models, to governance and hardware challenges. | — | ||||||
| 8/20/26 | AI-generated code: What has to be true for us to trust it without looking at it? | We've been thinking a lot recently about the status of code in a world where it's increasingly written and read by AI. Could the spec, for instance, become the primary way we interface with software systems? And if it does, will that mean humans no longer need to look at code at all? At present, the idea of not looking at our code seems fanciful, possibly dangerous, but even within Thoughtworks there are conflicting perspectives about whether this might change. To some, code will always remain the primary artifact; to others, its role in how we build software is about to undergo a significant transformation. On this episode of the Technology Podcast, Thoughtworks' Caer Sanders and Razin Memon join host Ken Mugrage for a debate about how the relationship between developers and code might — or might not — change in the final years of this decade. For Caer, despite the clear capabilities of AI, paying attention to code will always matter; for Razin, meanwhile, code's relevance is likely to decline as harnesses become more sophisticated and specification techniques evolve. Whatever your view, listen for a frank and open discussion about an issue that will ultimately determine what the future of software engineering actually looks like. Listen to our episode on harness engineering from May 2026: https://www.thoughtworks.com/insights/podcasts/technology-podcasts/what-harness-engineering Read a recent blog post on thoughtworks.com arguing we still need to design code for humans: https://www.thoughtworks.com/insights/blog/programming-languages/should-still-design-code-humans | — | ||||||
| 8/6/26 | Scaling the enterprise harness: How to achieve AI agent controllability across an organization | Harness engineering is still a new concept, but already we've noticed a challenge being consistently faced by technology leaders: how can a harness be used at scale across an organization to ensure consistency and controllability without undermining autonomy? To some extent it's a discussion that's reminiscent of platform engineering and, before that, DevOps, but, given the nature of AI agents, it's also unique to this particular moment. On this episode of the Technology Podcast, host Ken Mugrage is joined by guests Thomas Squeo (Chief Technology Officer and Head of Advisory for the Americas) and Matt Kamelman (Innovation Choreographer) to explore why it's so important to scale harnesses effectively and the steps and processes that will allow you to do just that. Thomas and Matt recently wrote an article outlining how organizations should think about what they call 'enterprise harness engineering'; here, they unpack their ideas and explore what's required of engineering leaders and their teams. Read Thomas' and Matt's article: https://www.thoughtworks.com/insights/articles/operating-system-enterprise-ai | — | ||||||
| 7/23/26 | Embracing hybrid AI: How Lenovo is leveraging local, on-device AI | Cloud was one of the main drivers of the early waves of AI adoption. However, as AI has become more and more embedded in systems and devices — in both consumer and enterprise contexts — it's becoming a bottleneck. This isn't just about costs (although yes, that issue is certainly surging up the agenda), it's also about how we optimize our architectures and improve device performance. This is why conversation is turning to hybrid AI: embracing a hybrid approach that combines proprietary cloud services with local or on-device AI can help organizations deliver better experiences for users, whether they're consumers, other businesses or internal teams. One company exploring this space is electronics giant Lenovo. In this episode of the Technology Podcast, host Prem Chandrasekaran is joined by Girish Hoogar, Lenovo's Global Head of Technology for Cloud and Software, to discuss why the company is embracing hybrid AI, how it's approaching implementation and what the implications are for other technologists. As industry attention turns to local AI, listen for a first-hand perspective on what the trend actually means for engineering teams and their organizations. | — | ||||||
| 7/9/26 | software engineeringAI assistance+3 | Kief MorrisAndrew Harmel-Law | ThoughtworksMartin Fowler | Switzerland | software engineeringAI+3 | — | 46m 25s | ||
| 6/25/26 | codeAI+4 | Unmesh Joshi | Thoughtworksmartinfowler.com+1 | — | codeAI+5 | — | 40m 16s | ||
| 6/11/26 | database branchingdeveloper workflow+4 | Cam CasherKevin Hartman | NeonSupabase+5 | — | database branchingdeveloper workflow+7 | — | 39m 09s | ||
| 5/28/26 | spec-driven developmentAI-adjacent practices+3 | Laura Tacho | AWSThoughtworks+1 | — | spec-driven developmentAI+3 | — | 45m 39s | ||
| 5/14/26 | harness engineeringAI agents+4 | Birgitta Böckeler | martinfowler.comYouTube | — | harness engineeringAI+5 | — | 40m 51s | ||
| 4/30/26 | AI securitysoftware development+3 | Chris Kramer | Anthropic MythosProject Glasswing+1 | Discord | Anthropic MythosProject Glasswing+3 | — | 48m 50s | ||
Want analysis for the episodes below?Free for Pro Submit a request, we'll have your selected episodes analyzed within an hour. Free, at no cost to you, for Pro users. | |||||||||
| 4/15/26 | AI technologiessoftware engineering+3 | Alessio FerriJim Gumbley | ThoughtworksTechnology Radar Vol.34 | — | AITechnology Radar+5 | — | 44m 07s | ||
| 4/2/26 | software engineeringAI+3 | Nate Schutta | ThoughtworksFundamentals of Software Engineering | — | software engineeringAI+3 | — | 41m 17s | ||
| 3/19/26 | AI maturitytechnology trends+3 | Rickey ZacharyThomas Squeo | Thoughtworks2026 Looking Glass | — | AItechnology+5 | — | 46m 18s | ||
| 3/5/26 | durable computingdistributed systems+3 | Brandon CookJohn Coleman | Thoughtworks | — | durable computingdistributed systems+3 | — | 37m 42s | ||
| 2/19/26 | AI developmentsoftware engineering+3 | Bharani SubramaniamShodhan Sheth | AI/works™Thoughtworks | — | AI agentssoftware solutions+3 | — | 40m 05s | ||
| 2/5/26 | AI agentsengineering rigor+5 | Nathen HarveyPatrick Debois | Google CloudTessl | — | AIengineering practices+5 | Thoughtworks | 39m 20s | ||
| 1/22/26 | AI agentssoftware engineering+4 | Ben O'MahonyFabian Nonnenmacher | O'ReillyBuilding AI Agent Platforms | — | AI agentsplatforms+5 | — | 37m 59s | ||
| 1/8/26 | software architectureantipatterns+3 | Mark RichardsRaju Gandhi+1 | O'ReillyArchitecture Patterns, Antipatterns and Pitfalls | — | software architectureantipatterns+3 | — | 35m 22s | ||
| 12/23/25 | age of intentdigital interaction+3 | Sarah Taraporewalla | Thoughtworks | — | age of intentdigital interaction+3 | — | 45m 24s | ||
| 12/11/25 | AI-assisted software development in 2025: Inside this year's DORA report | This year's DORA report focuses on AI-assisted software development. While one of the key themes is just how ubiquitous AI is today in software engineering, that's only part of the picture. In fact, the report outlines many of the challenges the adoption of these technologies are posing and explores the barriers and obstacles that need to be addressed to ensure AI-assistance leads to long-term success. In this episode of the Technology Podcast, host Ken Mugrage is joined by Chris Westerhold — Global Practice Director for Engineering Excellence at Thoughtworks — to discuss this year's DORA report (for which Thoughtworks is a Platinum sponsor). They dive into some of the reports findings, and explore the risks of increasing throughput, the changing demands on software developers, the importance of developer experience and how organizations can go about successfully measuring AI impact. You can find the 2025 DORA report here: https://cloud.google.com/resources/content/2025-dora-ai-assisted-software-development-report Read Chris Westerhold's article on this year's findings: https://www.thoughtworks.com/insights/articles/the-dora-report-2025--a-thoughtworks-perspective | — | ||||||
| 11/27/25 | We still need to talk about vibe coding: Reflections on 2025's word of the year | Vibe coding was, remarkably, named word of the year by the Collins English Dictionary at the start of November 2025 — pretty good going for a term that was only coined in February. We first discussed it on the Technology Podcast back in April, and, given its prominence in the collective lexicon this year, thought we should revisit and reflect on the topic as 2025 draws to a close. Lots has happened in the intervening months: MCP adoption, the evolution of agentic coding tools and practices like context engineering have had a significant impact on the way the world is thinking about and using AI. To talk about it all and reflect on the implications, Thoughtworkers and regular podcast hosts Prem Chandrasekaran, Lilly Ryan and Neal Ford reconvened for a follow up to our April conversation. Taking in everything from the term's semantic slipperiness, its security risks and the challenges of maintaining AI-generated code, this is a discussion that, despite going deep into vibe coding, also touches on a huge range of issues in the technology industry today. Before we enter 2026, looking back on the good, the bad and the ugly of the last 12 months of experimentation is essential if we're to build better software for the world in the future. This episode aims to be a guide through that process. Listen to our April episode on vibe coding: https://www.thoughtworks.com/insights/podcasts/technology-podcasts/vibe-coding Read Ken Mugrage's blog post exploring the shift from vibe coding to context engineering in 2025: https://www.thoughtworks.com/insights/blog/machine-learning-and-ai/vibe-coding-context-engineering-2025-software-development | — | ||||||
| 11/13/25 | How developers can get the most from new AI coding workflows | One of the biggest stories in software engineering in 2025 is the impact of generative AI on the software development lifecycle. From advances in coding assistance to the emergence of so-called agentic coding, there's undoubtedly a lot for software developers to process, learn and experiment with — not to mention rapid change to contend with. On this episode of the Technology Podcast, host Ken Mugrage is joined by Brandon Cook to discuss not only how AI has been shaping the way software developers work but how developers can play an active role in ensuring the technology is leveraged safely and successfully. Taking in everything from sensible defaults and best practices to evaluating how much autonomy you should give up to an agent in any given problem, this episode offers both a snapshot of where we are today and the role we all have to play in deciding what the future will look like. Explore the Thoughtworks Technology Radar: thoughtworks.com/radar Listen to Brandon's last appearance on the Technology Podcast from July 2024: https://www.thoughtworks.com/insights/podcasts/technology-podcasts/sensible-defaults-way-think-technology-practices | — | ||||||
| 10/30/25 | Themes from Technology Radar Vol.33 | In every Thoughtworks Technology Radar we feature three to five themes that represent the core issues and topics that emerged from the conversations we had when putting the publication together. This time (Fall 2025) they're all united by AI. They are: infrastructure automation arriving for AI, the rise of agents elevated by MCP, AI coding workflows and emerging AI antipatterns. On this episode of the Technology Podcast, Bryan Oliver joins Neal Ford and Ken Mugrage to discuss all four of volume 33's themes. They dive into what they mean, how the team arrived at them and what they tell us about the state of software engineering and AI in 2025. Read the latest Thoughtworks Technology Radar: thoughtworks.com/radar Volume 33 will be published November 5, 2025. | — | ||||||
| 10/16/25 | What does an AI strategy with humans at the center look like? | Everyone knows an AI strategy is important — but how do you build one with humans at the center? That's a question Tiankai Feng, Thoughtworks Global Director for Data and AI Strategy, has been pondering ever since the publication of his 2024 book Humanizing Data Strategy. Now, just over a year later, he's outlined his thinking in a follow-up, Humanizing AI Strategy. With the subtitle "leading AI with sense and soul," it's a practical and thoughtful guide aimed at helping the industry rethink the way AI is embedded and leveraged across organizations. In this episode of the Technology Podcast, Tiankai joins host Prem Chandrasekaran to discuss his new book. He explains why he wrote it, how it compares to his first book and discusses the framework it puts forward. Listen for a fresh perspective on AI in business and some practical strategies for leaders to bring purpose and conscience to AI initiatives. Learn more about Humanizing AI Strategy: https://www.thoughtworks.com/insights/books/humanizing-ai-strategy Read a Q&A with Tiankai: https://www.thoughtworks.com/insights/blog/data-strategy/how-put-human-center-ai | — | ||||||
| 10/2/25 | What we're talking about when we talk about context engineering | Everyone seems to be talking about context engineering. That was certainly the case in our recent discussions for the upcoming edition of the Technology Radar (volume 33, due early November 2025). And although we ran into the term on the Technology Podcast just a few weeks ago, we thought it would be useful to try and tackle exactly what people are talking about when they talk about context engineering. We know context is important when it comes to AI, but what does it mean to engineer it? On this episode of the Technology Podcast, host and Thoughtworks CTO Rachel Laycock is joined by Thoughtworkers Alessio Ferri (Lead Software Engineer) and Bharani Subramaniam (CTO for India and the Middle East) to discuss what context engineering is, how it's being done and what it tells us about the evolution of AI. This certainly won't be the last word — ours or anyone else's — on context engineering, but it might help clarify and cement your understanding as the term comes to dominate technology conversations. | — | ||||||
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Chart history for Thoughtworks Technology Podcast
Peaked at #25 in Mexico, currently #25 in Mexico.
| Market | Genre | Peak | Current | Trend |
|---|---|---|---|---|
| Mexico | — | #25 | #25 | — |
| South Korea | — | #35 | #35 | — |
| NG | — | #62 | #62 | — |
| India | — | #66 | #66 | — |
| PL | — | #88 | #88 | — |
| TH | — | #109 | #109 | — |
| TR | — | #118 | #118 | — |
| United Kingdom | — | #126 | #126 | — |
| AE | — | #137 | #137 | — |
| PT | — | #187 | #187 | — |
| RO | — | #190 | #190 | — |
Chart Positions
11 placements across 11 markets.
Chart Positions
11 placements across 11 markets.