Dev Systems

Agent-First Development Workflows in VS Code with Brigit Murtaugh

Explore VS Code's new Agents window — a familiar, focused UI that puts agent-first workflows front and center across repos, ...

Have LLMs made anyone's life substantially better?

I can't help but come to the conclusion that almost everyone's life has gotten worse as a result of AI.I'm a software engineer working for a huge company. We have access to AI tools, which is cool, and it saves me time in the sense that it is quicker to write code. Yet, despite writing code taking time, I never thought that it was a tedious usage of time. As a developer, the times that I got to actually sit down and start banging out code were some of the most fun times I've

Show HN: Raft in Rust

For quite sometime, I’ve wanted to give implementing the Raft consensus protocol a try. I first looked at MIT’s 6.5840 Distributed Systems labs as a way to do this but it is in Go and my Go skills have atrophied as well as I have been deeply investing time in Rust. The other option was PingCAPs approach (https://github.com/pingcap/talent-plan/blob/master/courses/d...) but I also wanted the ability to define my own types and RPC approach, so I decided to do

Cheers.fan #1 – Founding Infrastructure Engineers

CHEERS.FAN #1 | Founding Infrastructure EngineersEarly-stage company exploring large-scale synchronized interaction systems for entertainment, media, and shared live events.Interested in foundational infrastructure problems involving:● distributed systems ● low-latency infrastructure ● synchronization ● edge systems ● high-concurrency real-time interaction ● event-stream architectures ● coordinated participation across large populations of devicesSeeking experienced engineers with backgrounds in

SilverTorch: Index as Model — A New Retrieval Paradigm for Recommendation Systems

We’re introducing SilverTorch, a reimagining of recommendation systems that unifies all retrieval components for user generated content under a unified architecture. SilverTorch shows up to 23.7x higher throughput compared to the state-of-the-art approaches. It’s also showing 20.9x more compute cost efficiency compared to a CPU-based solution while also improving accuracy. Our research paper, “SilverTorch: A Unified Model-based System to Democratize Large-Scale Recommendation on GPUs,” accepted

Is WebSockets enough for AI chat?

WebSockets are the right protocol for production AI chat. But that fact doesn’t prevent the failure most teams hit first. An enterprise load balancer closes the idle connection at 60 seconds during a tool execution wait. Your reconnect logic fires in under a second, the agent keeps running server-side, and the client receives nothing from the gap. No tokens, no tool call results, no context.The reconnected socket has no view of what happened while it was down. Three conditions cause this routine

Show HN: Spec-Driven Development Workflow for Claude Code

Spec Driven Development approach allows to squeeze more from coding agents thanks to few strong concepts: - decomposition across two dimensions. first you generate specs in multiple steps (requirements, code analysis, design), than you split task into multiple subtasks and implement them one by one - you clear context between every step - after spec generation and after subtask implementation. this helps keep cost low and context clear and focused which boost performance - specs written to disk

Show HN: Kanban CLI (A local-first, agent-first task manager for the terminal)

Hello HN,Ever since agents have become increasingly common in development, I've been scratching my head as to how to control their randomness. Recently, I decided to emulate an issue-tracking and project-management tool for agent-driven workflows.Kanban is a Rust-based coordination layer designed to provide a feature-rich terminal interface and enforce rigorous workflows. It aims to be versatile and extendable, made to be tailored to any preferred flow. It comes with full git integration an

Distributed Data 30 Why Distributed Systems Are Hard

A practical explainer course on how modern backend systems store, move, process, and protect data. Topics include reliability ...

DS Unit 1 Part 1 | telugu | Characterization, Examples, Resource Sharing & challenges | R22

Distributed Systems | Unit 1 - Part 1 | JNTUH R22 Syllabus In this video, we start Unit 1 of Distributed Systems with clear and easy ...

Show HN: We dropped Go for Rust in our real-time telephony AI media plane

In building Vivik, an execution-grade telephony AI engine, we faced a brutal constraint: the human conversational loop.In psychoacoustics, a delay under 250 ms feels instantaneous. At 500 ms, users notice lag. Beyond 800 ms, conversations start feeling strained, and by 1.5 seconds, the illusion of real-time interaction collapses.That creates an extremely tight latency budget for voice AI:• Network RTT: 50–200 ms • LLM inference: 200–800 ms • TTS synthesis: 100–400 ms • ASR processing: 100–300 ms

Show HN: A timeline of recent open source CVE intensity and volume

I was curious what it would look like if I plotted the intensity and volume of software supply chain CVEs over time, given what seemed like a flood of compromises lately.It looked exactly as I expected, and I expect it to get worse before it gets better.Yes, an LLM was used but because I wanted the simplest possible architecture, I steered away from using any back end at all. Instead it's just GitHub pages with a static json document as the source of data, updated daily by a GitHub action w

Cloud Native Platforms: Build

Audience: Cloud architects, platform engineers, engineering leaders making design decisionsReading time: 8 minutesSeries: Cloud Native Platforms. Build, Run, Evolve. This is Part 1 of 3.Most engineering teams can build systems.Few can scale them without rebuilding them.As platforms grow, complexity does not increase linearly. It multiplies across users, services, tenants, regions, and integrations. The systems that struggle and the systems that scale are rarely separated by which cloud they run

Cloud Native Platforms: Run

Audience: SREs (Site Reliability Engineers), platform engineers, engineering managers running production systemsReading time: 8 minutesSeries: Cloud Native Platforms. Build, Run, Evolve. This is Part 2 of 3.Most systems are designed thoughtfully.Most operations are inherited reactively.The systems that survive are not the ones built with the most care. They are the ones operated with the most discipline. Production has a way of revealing every shortcut taken during design and every assumption le

Cloud Native Platforms: Evolve

Audience: Engineering leaders, platform architects, senior developers exploring how to operationalise AI in their teamsReading time: 8 minutesSeries: Cloud Native Platforms. Build, Run, Evolve. This is Part 3 of 3.Cloud helped us scale infrastructure.AI is starting to do the same thing for the work around the code: the planning, the testing, the release communication, the incident triage, the writing that surrounds writing software.The conversation about AI in software has narrowed too quickly t

WAR, Azure Advisor, and Us (Azure Arch Diagram Builder): Three Ways to Score an Azure Architecture

Author: Arturo Quiroga, Azure AI services Engineer - Senior Partner Solutions Architect — MicrosoftA few days ago I published From Prompt to Production: Building Azure Architecture Diagrams with AI, introducing the open-source Azure Architecture Diagram Builder. One feature got more follow-up questions than any other: the Well-Architected Framework (WAF) validation. Architects from partners and customers — many of whom already use Azure Advisor and the Well-Architected Review — wanted to know ex

Cyber resilience on AWS: A reference approach for recovery from ransomware and destructive events

Cyber resilience is the ability to recover workloads to a known-good state after an adversary has affected the environment. Prevention works to keep threat actors out and detection works to find them quickly. Cyber resilience focuses on recovery: restoring a trustworthy environment when backups, credentials, or parts of the infrastructure can no longer be assumed to be safe. For organizations running critical workloads on AWS, ransomware, data extortion, and other destructive events are increasi

A new experiment brings better group meetings to Google Beam

<img src="https://storage.googleapis.com/gweb-uniblog-publish-prod/images/Screenshot_2026-05-15_at_4.21.2.max-600x600.format-webp.webp">See and hear your colleagues in true-to-life size and sound, making hybrid meetings feel more inclusive and connected.

Ask HN: What AI coding workflows have stuck for you?

There’s a lot of discussion around AI-assisted development, but I’m curious which workflows have actually remained useful beyond the initial novelty phase.

I created a 126K line Android app with AI – the workflow that worked for me

I really wanted to see how far I can go. Can I create a meaningful and complex application, big enough, but without knowing the language.I have 18+ years of experience as software developer. But I have no experience with Kotlin. And to learn Kotlin, to learn the Android libraries, it is not an easy job. I may need at year of active learning and trying things, before having the confidence to start doing something.So, I asked myself, how far can I go with AI tools? And I went far!I created https:&