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Podcast Archives - Software Engineering Daily

Podcast Archives - Software Engineering Daily

Podcast Archives - Software Engineering Daily 100 Episodes Oct 13, 2026

Software Engineering Daily features technical interviews about software topics. Each episode dives into a specific area of software engineering, from architecture to deployment. The podcast aims to provide in-depth discussions with industry experts.

Episodes

SED News: Jev, Meta’s Muse, and the AI Slowdown Paradox
SED News: Jev, Meta’s Muse, and the AI Slowdown Paradox Oct 13, 2026 49:01 SED News is a monthly podcast from Software Engineering Daily where hosts Gregor Vand and Sean Falconer break down the biggest stories shaping software engineering, Silicon Valley, and the broader tech industry. In this episode, Gregor and Sean cover a wave of new product drops, including Jev from TypeSafe AI, a model that returns scored, type-safe structured responses for machine-to-machine t
Steve Jobs in Exile
Steve Jobs in Exile Oct 8, 2026 2:02:15 The popular story of Steve Jobs is that he co-founded Apple, was pushed out, wandered through a failed venture called NeXT, then returned to save the company and usher in the iPod and iPhone. That version is memorable, widely repeated, and, in an important sense, wrong. His years at NeXT are usually treated as a footnote, when they were among the most consequential of his life and career. Geof
Security in the Age of Instant Exploits
Security in the Age of Instant Exploits Oct 6, 2026 49:53 In the world of software security, there was historically a comfortable lag between the moment a vulnerability became public and the moment attackers could exploit it. This lag was often measured in months, but AI models can now read a vulnerability report and generate a working exploit almost instantly. They can scan the entire internet for exposed secrets at a scale no human team could match, a
The State of Browser Testing
The State of Browser Testing Oct 1, 2026 52:29 Automated browser testing is a foundational technology that many web developers rely on. Modern tooling lets a single test drive Chrome, Firefox, and Safari the same way, a triumph of software engineering built on years of standardization work. That standardization emerged from the interplay between open source projects, browser vendors, and standards bodies like the W3C. David Burns is a long
Cory Doctorow on AI, Work, and Power
Cory Doctorow on AI, Work, and Power Sep 29, 2026 59:48 Cory Doctorow is a science fiction author, journalist, and technology activist, and a special advisor to the Electronic Frontier Foundation. He is the author of dozens of books, including the nonfiction Enshittification: Why Everything Suddenly Got Worse and What to Do About It and the novel Picks and Shovels. His work spans tech policy books like The Internet Con and Chokepoint Capitalism, the s
Chroma and Agentic Retrieval
Chroma and Agentic Retrieval Sep 24, 2026 52:20 Data retrieval is a fundamental challenge in AI systems, and the approaches for solving it are still evolving. Vector search was an early answer to the retrieval problem, but the rise of agentic systems has raised the stakes considerably. Agents issue queries at machine speed, decompose complex questions into parallel searches, and require retrieval infrastructure that can keep pace without becom
Scaling Time-Series Workloads on Postgres
Scaling Time-Series Workloads on Postgres Sep 22, 2026 48:23 Many real-world processes produce data as a continuous stream rather than as isolated records. Sensor readings, financial markets, and application telemetry all generate data this way. This kind of time-series data has a distinctive shape. It’s written far more often than it is updated, it accumulates continuously, and it is usually queried across ranges of time. Time-series databases are b
Scaling Agent Workloads at Vercel
Scaling Agent Workloads at Vercel Sep 17, 2026 51:25 Most AI agent setups today are built around a single session, where one user interacts with one agent at a time. However, that model breaks down when an agent has to serve a business, where thousands of requests can arrive at once and each session needs to be isolated, durable, and recoverable. Getting agents to run reliably at that scale has meant a lot of hand-rolled infrastructure beneath the
Inside Google’s Database Infrastructure for the AI Era
Inside Google’s Database Infrastructure for the AI Era Sep 15, 2026 1:18:26 Historically, databases were responsible for storing data and returning exact results in response to queries. However, AI is now bending that contract in a new direction. Applications increasingly expect structured and unstructured data to come together. This is pushing databases into territory that looks more like search, where relevance and ranking matter and results are no longer strictly exac
A Rust Framework to Simplify Distributed Systems
A Rust Framework to Simplify Distributed Systems Sep 10, 2026 50:31 A Rust Framework to Simplify Distributed Systems Building software that runs across many machines is notoriously difficult. Developers have to grapple with problems such as race conditions, partial failures, and message ordering. Notably, one category of distributed software has largely escaped these burdens. A distributed database can spread a single query across thousands of machines, handli
SED News: The NVIDIA-Hugging Face Deal, China’s Proxy Economy, the Open Weight Surge
SED News: The NVIDIA-Hugging Face Deal, China’s Proxy Economy, the Open Weight Surge Sep 8, 2026 52:06 SED News is a monthly podcast from Software Engineering Daily where hosts Gregor Vand and Sean Falconer break down the biggest stories shaping software engineering, Silicon Valley, and the broader tech industry. In this end-of-summer episode, Gregor and Sean turn to a busy season of mergers and acquisitions, including NVIDIA‘s reported $12.9 billion acquisition of Hugging Face, Dynatrace
Moving Beyond RAG with Precomputed Context
Moving Beyond RAG with Precomputed Context Sep 3, 2026 55:48 Retrieval has become one of the central problems in building useful AI systems. The standard approach to grounding a model in one’s own data has been retrieval augmented generation, or RAG, where an agent searches a vector database for relevant information at query time. That pattern works, but it has limitations, such as retrieving information that’s not truly relevant, repeating the

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