Moving Beyond RAG with Precomputed Context

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1. 

   22 Sep 2026 · 48 min

   Scaling Time-Series Workloads on Postgres

   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 built specifically for this kind of workload. TimescaleDB is an open source database from Tiger Data that adds time-series capabilities to PostgreSQL. It’s implemented as a Postgres extension, so it…

2. 

   17 Sep 2026 · 51 min

   Scaling Agent Workloads at Vercel

   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 agent itself. eve is an open source, cloud-native agent framework from Vercel that removes much of the agent scaling burden. In the eve framework, an agent is defined declaratively through…

3. 

   15 Sep 2026 · 1 hr 18 min

   Inside Google’s Database Infrastructure for the AI Era

   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 exact. Agents are also beginning to write their own queries and even propose their own schemas, which raises new questions about how data should be structured, governed, and trusted. Sailesh…

4. 

   10 Sep 2026 · 51 min

   A Rust Framework to Simplify Distributed Systems

   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, handling the coordination, failure recovery, and ordering internally. This raises a natural question of why general-purpose distributed programming can’t feel the same way. This is a highly practical problem…

5. 

   8 Sep 2026 · 52 min

   SED News: The NVIDIA-Hugging Face Deal, China’s Proxy Economy, the Open Weight Surge

   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 ‘s near-billion-dollar deal for AI observability platform Arize , and Temporal ‘s rumored raise at a $12 billion valuation. They also cover a run of large funding rounds, from AI security startup…

6. 

   1 Sep 2026 · 53 min

   The Death of Online Anonymity

   Age verification is reshaping how people access the internet. An ever-growing patchwork of laws can now require government IDs, facial age estimation, or behavioral inference before you can enter digital spaces. Discord, app stores, social media platforms, and AI chatbots are all being pulled into these requirements. Almost always, these measures are enacted under the banner of protecting children. However, beneath that goal lies a set of hard questions about privacy, anonymity, security, and the line between what a private platform may choose to do and what a government may compel. John…

7. 

   27 Aug 2026 · 57 min

   TypeScript 7 and What Comes Next

   TypeScript is a programming language that builds on JavaScript by adding a system of types. Those types let developers describe the shape of their data and catch mistakes before code ever runs, while also powering the autocompletion and editor tooling that many developers now rely on every day. It was first released in 2012, and has since become one of the most widely used tools in web development. TypeScript recently underwent one of the most significant changes in its history with the release of version 7. Daniel Rosenwasser is the Principal Product Manager of TypeScript at Microsoft ,…

8. 

   25 Aug 2026 · 55 min

   The Gap Between AI Spending and AI Value

   It is widely reported that a gap has emerged between enterprise spending on AI and the durable value captured from that spend. Individual employees have enthusiastically adopted coding assistants and chatbots, yet those gains do not seem to be transforming businesses at an organizational level. One of the most important questions in the tech industry today is understanding why AI is not yet delivering returns that match the investment, and what separates the small number of enterprises succeeding from the many that are not. Scale AI is known for supplying the human-labeled data behind many…

9. 

   20 Aug 2026 · 1 hr 13 min

   AI and the New Global Security Landscape

   The conversation about AI often focuses on software, automation, and the race between attackers and defenders in code. However, some of the most consequential risks lie further afield, in domains where a mistake is measured in human lives. Advanced models can now offer step-by-step guidance toward chemical and biological weapons, and militaries are already folding AI into targeting and battlefield assessments. These are no longer speculative fears confined to the AI doomer crowd. They are documented in red team disclosures, government legislation, and events unfolding on real battlefields.…

10. 

    18 Aug 2026 · 48 min

    How LLMs Are Reshaping Recommendation Systems

    News feeds and recommendation systems have long relied on deep learning architectures that score each candidate item independently. As LLMs have matured, they have opened up a fundamentally different approach, where a system can reason about content the way it reasons about language. However, that power comes with a fresh set of engineering challenges around cost, scale, and evaluation. LinkedIn recently rebuilt its news feed to treat content recommendation as a sequence modeling problem. The general approach is to predict what a user will want next, much like an LLM predicts the next token…