--- title: The best tech podcasts for developers in 2026 | daily.dev description: 10 developer podcasts matched to your stack, role, and listening time, covering AI engineering, cloud-native, web, and data. canonical: https://daily.dev/blog/best-tech-podcasts-for-developers/ og:type: article og:url: https://daily.dev/blog/best-tech-podcasts-for-developers/ og:title: The best tech podcasts for developers in 2026 | daily.dev og:description: 10 developer podcasts matched to your stack, role, and listening time, covering AI engineering, cloud-native, web, and data. og:image: https://media.daily.dev/image/upload/s--9s6YIHC9--/f_auto,q_auto/v1/recruiter-landing/6aab2e70c5072cdcadb5b915_1789609945847_73086fb730?_a=BAMAMiB80 og:site_name: daily.dev og:locale: en_US article:published_time: 2026-09-17 article:modified_time: 2026-09-17T02:16:12.056Z article:author: Kevin Nguyen twitter:card: summary_large_image twitter:site: @dailydotdev twitter:creator: @dailydotdev twitter:title: The best tech podcasts for developers in 2026 | daily.dev twitter:description: 10 developer podcasts matched to your stack, role, and listening time, covering AI engineering, cloud-native, web, and data. twitter:image: https://media.daily.dev/image/upload/s--9s6YIHC9--/f_auto,q_auto/v1/recruiter-landing/6aab2e70c5072cdcadb5b915_1789609945847_73086fb730?_a=BAMAMiB80 --- **If I had to cut this list down fast, I’d sort it by _stack_, _role_, and _time_.** This roundup picks **10 developer podcasts** that show up on a steady schedule, stay close to 2026 topics like **AI engineering, cloud-native systems, [contributing to open source](https://daily.dev/blog/how-to-start-contributing-to-open-source-projects), web dev, and data work**, and fit normal listening windows from **15 minutes to 90 minutes**. Here’s the short version: - **For deep engineering topics:** _Software Engineering Daily_, _The InfoQ Podcast_ - **For open source and developer life:** _The Changelog_, _Stack Overflow Podcast_ - **For Python:** _Talk Python To Me_ - **For data and AI:** _Data Engineering Podcast_, _Practical AI_ - **For web and JavaScript:** _Syntax_, _JavaScript Jabber_ - **For Go:** _Go Time_ A few numbers stand out. Most shows here publish **weekly or biweekly**. Episode length ranges from about **15 minutes** on shorter formats like _Syntax_’s Hasty Treats to about **90 minutes** on deeper interviews like _The Changelog_ and _Go Time_. That matters because a podcast you can finish during a commute is easier to keep up with than one you save for “later” and never play. ::: @figure {Best Developer Podcasts 2026: Quick Comparison Guide} ## Quick Comparison | Podcast | Best for | Usual length | Schedule | | --- | --- | --- | --- | | **Software Engineering Daily** | Senior engineers, leads | 45–70 min | Near-daily | | **The Changelog** | [Open source](https://daily.dev/blog/how-to-contribute-to-open-source-projects-as-a-beginner), dev stories | 60–90 min | Weekly | | **Stack Overflow Podcast** | Early-career devs, career topics | 30–50 min | Weekly | | **Talk Python To Me** | Python, ML, web dev | 60–75 min | Weekly | | **Data Engineering Podcast** | Data teams | 45–60 min | Weekly | | **Syntax** | Front-end, full-stack | 15–60 min | Twice weekly | | **JavaScript Jabber** | JavaScript, TypeScript | 45–60 min | Weekly | | **Go Time** | Go developers | 60–90 min | Weekly | | **The InfoQ Podcast** | Architects, senior devs | 45–75 min | Weekly or biweekly | | **Practical AI** | ML, MLOps, LLM tooling | 40–60 min | Weekly | My read: **this list is less about “the one best podcast” and more about finding the right fit**. If you want broad engineering depth, start with **Software Engineering Daily**. If you want to [become a full-stack developer](https://daily.dev/blog/how-to-become-a-full-stack-software-developer-a-primer) or build UIs, go with **Syntax**. If you work on ML systems, pick **Practical AI**. And if you just want a low-effort way to stay in the loop, **Stack Overflow Podcast** is the easiest place to start. ## What makes these podcasts worth your time in 2026 Every show here checks a few simple boxes. It publishes on a steady schedule, features active engineers, researchers, or engineering leaders, and stays close to the way teams work now, with topics like RAG, agentic development, LLM evaluation, cloud-native ops, AI engineering, and open source. It also fits into normal life: a commute, a workout, or a short block of focused time. Here’s what “good” looks like: | Criteria | What "good" looks like | | --- | --- | | **Consistency** | Weekly or biweekly publishing, no multi-month gaps | | **Host credibility** | Active engineers, researchers, or former engineering managers | | **Workflow relevance** | Covers RAG, agentic development, LLM evaluation, and cloud-native ops | | **Episode fit** | 15-minute briefings up to 60- to 90-minute deep dives, not marathon-length episodes | The idea is pretty simple: these shows turn small pockets of time into useful learning. Credibility matters just as much. The best hosts don’t settle for surface-level talk. They ask for the stuff that matters in practice: why a migration failed, which tradeoff someone would revisit, and how teams are handling AI-generated code in production. That’s what sets these podcasts apart. They’re less about hot takes and more about judgment, tradeoffs, and production decisions. With those standards in place, the podcasts below are the ones worth your time. ## 1\. [Software Engineering Daily](https://softwareengineeringdaily.com/) **Best for:** Senior engineers, tech leads, and engineering leaders who want technical depth across infrastructure, databases, distributed systems, and cloud infrastructure. This is one of the most consistent shows on the list. Episodes usually run **45 to 70 minutes** and come out on a near-daily schedule, a pace the show has maintained since launching in 2015 [\[1\]](https://www.youngju.dev/blog/culture/2026-05-14-developer-podcasts-curation-2026-latent-space-changelog-software-engineering-daily-deep-dive-2026.en)[\[4\]](https://rockstardeveloperuniversity.com/best-developer-podcasts/)[\[5\]](https://www.qodo.ai/blog/best-software-engineering-podcasts/). Most episodes focus on one company, one tool, or one technical area. The conversations stay technical without drifting into lecture mode. Guests are working practitioners from databases, platforms, and security, and the host tends to dig into _why_ a team made certain choices, not just _what_ they shipped. That makes the show useful when you're trying to understand trade-offs instead of just skimming surface-level product talk. In September 2026, for example, Software Engineering Daily featured Sailesh Krishnamurti, VP of Engineering at Google Cloud, in an episode that traced 50 years of database evolution, from relational systems to modern AI-driven infrastructure [\[3\]](https://www.signalcast.app/best/software-engineering-podcasts). That said, this is not the kind of podcast you need to follow episode by episode. Quality varies [\[5\]](https://www.qodo.ai/blog/best-software-engineering-podcasts/). A better approach is to treat the archive like a reference library: look up the technology, system design issue, or architectural pattern you're dealing with right now, then jump to the episode that fits. That's where the show tends to be most useful. ## 2\. [The Changelog](https://changelog.com/) **Best for:** Developers who care about open source, developer culture, and the human stories behind the code. If [finding open source projects](https://daily.dev/blog/10-ways-to-find-open-source-projects-to-contribute-in-2024) and developer culture are your thing, **The Changelog** is the strongest pick. It has been around since 2009, which makes it one of the longest-running developer podcasts out there [\[4\]](https://rockstardeveloperuniversity.com/best-developer-podcasts/)[\[5\]](https://www.qodo.ai/blog/best-software-engineering-podcasts/). New episodes come out weekly and usually run **60 to 90 minutes**. If that feels like a lot, there’s an easier option: the separate **Changelog News** feed, which is about five minutes a week. So you can either settle in for a deep listen or get the quick version and move on with your day. What makes the show work is its level of detail. The technical talk stays practical. Adam Stacoviak and Jerod Santo spend time on the stuff developers actually care about: decisions, blockers, and what maintainers would do differently if they had the chance. That gives the conversations more weight than a surface-level product chat. The guest list adds a lot too. Past guests include Linus Torvalds, Brian Kernighan, and Guido van Rossum. And the archive comes in handy when you want historical context before adopting a tool. ## 3\. [Stack Overflow Podcast](https://stackoverflow.blog/podcast/) **Best for:** Early-career developers and anyone who want a broad view of developer careers and industry trends without getting pulled into heavy technical detail. The [Stack Overflow Podcast](https://stackoverflow.blog/podcast/) is the easiest listen on this list. Episodes usually run **30 to 50 minutes** and come out **weekly**, so they fit nicely into a commute, a lunch break, or a short walk. Hosted by Stack Overflow staff and guest speakers, it gives developers a steady, low-friction way to keep up with software culture and career topics without diving too far into the weeds [\[1\]](https://www.youngju.dev/blog/culture/2026-05-14-developer-podcasts-curation-2026-latent-space-changelog-software-engineering-daily-deep-dive-2026.en). ## 4\. [Talk Python To Me](https://talkpython.fm/) **Best for:** Python developers, data scientists, ML engineers, and web developers building with [FastAPI](https://fastapi.tiangolo.com/), [Django](https://www.djangoproject.com/), or [Flask](https://flask.palletsprojects.com/). Hosted by Michael Kennedy, [Talk Python To Me](https://talkpython.fm/) digs into core Python, major libraries, and hands-on app development. It lines up well with the 2026 bar for steady publishing, practical depth, and current topics. Most episodes run **60 to 75 minutes** and come out **weekly**, so they work well for a commute or a focused work block. In 2026, the show leans more into AI engineering too, including LLM-based systems and GPU infrastructure [\[6\]](https://eg3.com/software/best-coding-podcasts/). The archive now includes **480-plus episodes** [\[4\]](https://rockstardeveloperuniversity.com/best-developer-podcasts/). If you want something shorter, Kennedy also co-hosts [Python Bytes](https://pythonbytes.fm/). ## 5\. [Data Engineering Podcast](https://www.dataengineeringpodcast.com/) **Best for:** Data engineers, analytics engineers, and platform teams who want practical, 45- to 60-minute conversations on pipelines, [orchestration tools](https://daily.dev/blog/orchestration-tools-for-developers), warehouses, and data tooling built for production, not just theory. ## 6\. [Syntax](https://syntax.fm/) **Best for:** Front-end and full-stack developers at any stage. If you work in JavaScript or TypeScript, Syntax is an easy podcast to keep in your weekly rotation. Wes Bos and Scott Tolinski host the show, and they stick to a steady twice-weekly schedule [\[4\]](https://rockstardeveloperuniversity.com/best-developer-podcasts/). The format is simple, which helps. Monday’s _Hasty Treats_ usually run about 15 to 20 minutes. Wednesday episodes go longer, often around an hour. That mix gives you both: short, useful updates and deeper conversations when a topic needs more room. Episodes like _"Server Components Explained"_ and _"Modern CSS in 2026"_ get enough time to be useful, not rushed. The tone stays conversational, but the show doesn’t water things down. It stays technical while still being easy to follow [\[4\]](https://rockstardeveloperuniversity.com/best-developer-podcasts/). The main focus is narrow in a good way. Syntax spends most of its time on React, Node.js, CSS, and deployment. So if that’s your stack, it’s a strong fit. If you spend most of your time outside the JavaScript and TypeScript world, the show may feel a bit too focused. ## 7\. [JavaScript Jabber](https://topenddevs.com/podcasts/javascript-jabber) **Best for:** JavaScript and TypeScript developers at every level, from front-end beginners to engineers working with complex architectures. JavaScript Jabber is a long-running podcast about the JavaScript ecosystem. It covers changes to the language, shifts across the ecosystem, and the frameworks and libraries developers use every day. Episodes usually last **45 to 60 minutes** and follow a panel format. That setup helps because you get more than one point of view on tooling, frameworks, and architecture. Instead of a quick update, you hear people talk through the tradeoffs, which is often where the useful stuff lives. That makes the show a solid pick if you're trying to compare ecosystem choices or think through architecture patterns with a bit more depth. If you want a different language focus, the next pick moves to Go. ## 8\. [Go Time](https://changelog.com/gotime) **Best for:** Backend engineers, systems developers, and experienced Go developers who want a deep dive into the Go language and the tools around it. Go Time zeroes in on Go, [cloud-native systems](https://daily.dev/blog/cloud-native-basics-for-developers), and open source. It sticks closely to the Go world, which is part of the appeal if you don't want side trips into every corner of software. Episodes usually run **60 to 90 minutes** [\[1\]](https://www.youngju.dev/blog/culture/2026-05-14-developer-podcasts-curation-2026-latent-space-changelog-software-engineering-daily-deep-dive-2026.en) and come out **weekly** [\[1\]](https://www.youngju.dev/blog/culture/2026-05-14-developer-podcasts-curation-2026-latent-space-changelog-software-engineering-daily-deep-dive-2026.en)[\[3\]](https://www.signalcast.app/best/software-engineering-podcasts). If you'd rather get a broader view of software instead of a Go-only show, the next pick opens things up a bit. ## 9\. [The InfoQ Podcast](https://www.infoq.com/the-infoq-podcast/) **Best for:** Senior developers, software architects, and engineering leaders who want long-view architecture discussions instead of trend-chasing. If Go Time is language-specific, **The InfoQ Podcast** takes a broader view. It leans into architecture, platforms, and engineering strategy, not just whatever topic is hot this week. Episodes usually run **45 to 75 minutes** and come out **weekly or biweekly** [\[1\]](https://www.youngju.dev/blog/culture/2026-05-14-developer-podcasts-curation-2026-latent-space-changelog-software-engineering-daily-deep-dive-2026.en)[\[5\]](https://www.qodo.ai/blog/best-software-engineering-podcasts/)[\[4\]](https://rockstardeveloperuniversity.com/best-developer-podcasts/)[\[7\]](https://lemon.io/blog/best-coding-podcasts/). So this is the kind of show you queue up when you want a deep discussion, not a quick how-to. If you want a more applied AI focus next, the final pick heads there. ## 10\. [Practical AI](https://changelog.com/practicalai) **Best for:** ML engineers, MLOps engineers, data engineers, and developers who want applied AI knowledge, not hype. Practical AI is about _doing the work_, not just talking about it. The show digs into implementation details, failure modes, and tools teams actually use, like [LangChain](https://www.langchain.com) and [LlamaIndex](https://www.llamaindex.ai). Hosted by Daniel Whitenack and Chris Benson, it stays approachable without feeling watered down. Most episodes run **40 to 60 minutes** and come out **weekly**. If you want a fast side-by-side look, check the comparison table below. ## Quick comparison table Use this table to line up each show with your role and the time you have. | Podcast | Primary Audience | Main Focus Area | Typical Length | Cadence | | --- | --- | --- | --- | --- | | **Software Engineering Daily** | Senior and mid-level engineers | Infrastructure, distributed systems, databases | 50–70 min | Near-daily [\[1\]](https://www.youngju.dev/blog/culture/2026-05-14-developer-podcasts-curation-2026-latent-space-changelog-software-engineering-daily-deep-dive-2026.en)[\[4\]](https://rockstardeveloperuniversity.com/best-developer-podcasts/) | | **The Changelog** | Open source contributors | Open source ecosystem and dev culture | 60–90 min | Weekly [\[1\]](https://www.youngju.dev/blog/culture/2026-05-14-developer-podcasts-curation-2026-latent-space-changelog-software-engineering-daily-deep-dive-2026.en)[\[4\]](https://rockstardeveloperuniversity.com/best-developer-podcasts/) | | **Stack Overflow Podcast** | General and entry-level developers | Developer life, industry pulse | 30–50 min | Weekly [\[1\]](https://www.youngju.dev/blog/culture/2026-05-14-developer-podcasts-curation-2026-latent-space-changelog-software-engineering-daily-deep-dive-2026.en) | | **Talk Python To Me** | Python developers and data scientists | Python ecosystem, ML, web dev, automation | 60–75 min | Weekly [\[4\]](https://rockstardeveloperuniversity.com/best-developer-podcasts/) | | **Data Engineering Podcast** | Data and analytics engineers | Pipelines, orchestration, data warehouses | 45–60 min | Weekly | | **Syntax** | Frontend and full-stack developers | JavaScript, CSS, React, web tooling | 30–60 min | Twice weekly [\[3\]](https://www.signalcast.app/best/software-engineering-podcasts)[\[4\]](https://rockstardeveloperuniversity.com/best-developer-podcasts/) | | **JavaScript Jabber** | JavaScript and TypeScript developers | JS ecosystem, frameworks, architecture | 45–60 min | Weekly | | **Go Time** | Go developers | Go ecosystem and tooling | 50–80 min | Weekly [\[1\]](https://www.youngju.dev/blog/culture/2026-05-14-developer-podcasts-curation-2026-latent-space-changelog-software-engineering-daily-deep-dive-2026.en) | | **The InfoQ Podcast** | Senior developers and architects | Architecture, platforms, engineering strategy | 45–75 min | Weekly or biweekly [\[1\]](https://www.youngju.dev/blog/culture/2026-05-14-developer-podcasts-curation-2026-latent-space-changelog-software-engineering-daily-deep-dive-2026.en)[\[4\]](https://rockstardeveloperuniversity.com/best-developer-podcasts/)[\[5\]](https://www.qodo.ai/blog/best-software-engineering-podcasts/)[\[7\]](https://lemon.io/blog/best-coding-podcasts/) | | **Practical AI** | ML and data engineers | Applied AI, MLOps, LLM tooling | 40–60 min | Weekly [\[1\]](https://www.youngju.dev/blog/culture/2026-05-14-developer-podcasts-curation-2026-latent-space-changelog-software-engineering-daily-deep-dive-2026.en)[\[2\]](https://www.castfox.net/blog/best-tech-podcasts-2026) | If you want a faster way to scan developer updates between listens, the next section covers when text feeds make more sense than podcasts. ## Podcasts and text feeds serve different moments The same fit-first idea applies to podcasts and text feeds too. Podcasts make sense during hands-free parts of the day: a commute, a walk at lunch, or time at the gym. Shows like [The Changelog](https://changelog.com/podcast) and [Syntax](https://syntax.fm/) are made for that kind of window, when you’re not sitting in front of a screen. Text feeds do a different job. When you’re at your desk, between pull requests, or stealing a few minutes during a short break, you usually want something you can scan fast and use right away. [daily.dev](https://daily.dev/) is a free, personalized feed for fast discovery and stack-specific reading, but it can’t replace the context you get from a podcast interview. [dev.to](https://dev.to/) fits neatly alongside both. It’s a place where developers publish tutorials, opinions, and ideas, which makes it a natural match for feeds and podcasts. Use podcasts when you want depth, and feeds when you want speed. ## Conclusion Choose podcasts based on your stack, your role, and the gaps you want to fill right now. If you work in [full stack development](https://daily.dev/blog/full-stack-development-complete-guide-2024), pairing [Syntax](https://syntax.fm/) with [Software Engineering Daily](https://softwareengineeringdaily.com/) gives you a solid mix of day-to-day industry pulse and deeper architecture talk. If you're building with machine learning, add [Practical AI](https://practicalai.fm/). If Go is the language you use most, [Go Time](https://changelog.com/gotime) makes a lot of sense. A simple rotation is often the easiest way to keep up without overloading yourself: one weekly show, one topic-specific pick, and one deep-dive archive listen. [Software Engineering Daily](https://softwareengineeringdaily.com/) fits that last slot especially well. The FAQ below shows the fastest way to narrow the list. ## FAQ Still narrowing the list? These quick answers cover the picks people ask about most. ### Which tech podcast is best for beginner developers in 2026? The [Stack Overflow Podcast](https://stackoverflow.blog/podcast/) is the easiest starting point for beginner-friendly developer news and career context. ### Which podcast covers AI and machine learning best in 2026? [Practical AI](https://changelog.com/practicalai) is the best fit on this list for applied machine learning and MLOps. ### Which podcast fits web developers best? [Syntax](https://syntax.fm/) is the clearest match for web developers because it stays focused on the JavaScript and web ecosystem. ### How long do most developer podcast episodes run? It depends on the show. You’ll see everything from Syntax’s 15-minute Hasty Treats to 50- to 70-minute deep dives like [Software Engineering Daily](https://softwareengineeringdaily.com/). ### Are podcasts or text feeds better for staying current? They do different jobs. Podcasts help you understand why decisions get made, while text feeds help you scan fast. 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