Natural language search to domain query search with AI & AWS Bedrock
Learn how to build a natural language search feature using AI and Amazon Bedrock. Translate user intent into secure, structured SQL or GraphQL queries without training custom LLMs.

Learn how to build a natural language search feature using AI and Amazon Bedrock. Translate user intent into secure, structured SQL or GraphQL queries without training custom LLMs.

A monthly reading roundup - no chasing every model, no top-50 lists, no marketing. One thread running through it all: the best model on the planet can be switched off on a Friday afternoon, so the real asset is what you build around it. You lease the model, but the process is yours.

Depending on the team and project, developers may work from well-defined requirements or help shape solutions from the ground up. In developer tooling, the latter tends to happen particularly often. We spoke with Karol Skóra about what surprised him most after moving from backend development into tooling and why communication may be just as important as technical expertise.

Diffusion models became de facto standard in image generation. While remarkably powerful, they rely on a multi-step process of iterative denoising, which takes time. Text generation is also processed in a sequential manner, however the text can be streamed and visualized token by token, giving a natural, real-time feeling, similar to how humans read or write a text. With images, we must wait for the final denoising step to complete before a usable result appears. This makes optimizing diffusion models for speed and efficiency a critical challenge.

Most developers build software for a specific customer. Tomasz Godzik works in a very different environment. As one of the engineers behind Scala open-source projects such as Metals and the Scala 3 compiler, his users can be anyone - from developers inside large organizations to contributors on the other side of the world. We talked about open source, development tooling, AI, and the kind of mindset required to solve problems that often have no documented solution.

Canton Network is becoming increasingly popular in the fintech space. Here is what you need to know as an engineer willing to integrate and build on this distibuted ledger.

JEP-538 introduces the third preview of the PEM API. This API provides native support for decoding and encoding cryptographic objects in the Privacy-Enhanced-Mail (PEM) format, which is kind of an industry standard.

Interview with Krzysztof Romanowski, Head of Development Productivity at VirtusLab Software engineering loves process, structure, best practices, and architectural purity. Tooling engineering often lives somewhere else entirely - in edge cases, uncomfortable tradeoffs, and systems that only work because somebody deeply understands how they break. We sat down with Krzysztof Romanowski to talk about why tooling engineers often think very differently from the rest of the industry.

A slightly unsettling realization hit us at VirtusLab not long ago - our collective list of starred GitHub repositories had quietly ballooned into something that could generously be called "a problem." Instead of pretending it wasn't happening, we decided to lean into it: every two weeks, we pick a trending open-source project, pull the hood off, and tell you what we find underneath. We focus on fresh, relatively unknown repos - not the usual suspects that everybody and their tech newsletter already covered (because let's be honest, you don't need us for that).

Interview with Jerzy Muller, Scala Evangelist & Dev Tooling Expert at VirtusLab Sometimes Google returns zero results. That’s usually where tooling engineers begin their work. In large-scale engineering organizations, their job is to make impossible systems work together and keep thousands of developers unblocked when everything starts breaking at scale. We sat down with Jerzy Müller, Scala Evangelist and Dev Tooling Expert at VirtusLab, to talk about what this work actually looks like behind the scenes.

Explore key insights from the Scala Survey 2026, including Scala 3 adoption rates, popular libraries, tooling preferences, and industry trends shaping the future of the Scala ecosystem.

Tomek Lelek and I wrote Vibe Engineering because we kept seeing the same mistake everywhere: teams confusing the speed of generation with the speed of delivery. Vibe coding, that intuition-first, prompt-driven mode where you accept what the AI gives you without deep verification, is genuinely valuable. It's the digital sketchpad. It's how you turn a foggy idea into a working interface in an afternoon. I use it. You probably should too.
