Dev Systems - Building Systems That Scale

Show HN: Artie – Real-time data replication to your data warehouse, self-serve

Hey HN, cofounder of Artie here. I’ve been working on real-time database replication using CDC (Postgres/MongoDB into Snowflake, BigQuery, Redshift) with my wife for the last three years. Last time I posted here, people had to book a call with us to get access, but that’s no longer the case. You can connect your source and destination and start streaming immediately.I encountered this problem firsthand as a heavy data warehouse user at prior jobs. Our warehouse data was always lagged and an

Show HN: HelixDB – A graph database built on object storage

Hey HN, it’s been just over a year since we launched HelixDB (https://news.ycombinator.com/item?id=43975423), a project a friend and I started in college. It’s an OLTP graph database built on object-storage, with native vector search and full-text search (FTS).Why graph, vector and FTS? Graph databases provide a natural cognitive model for data, vectors allow for a semantic understanding of the entities and relationships in the graph, and FTS provides more specific filtering. Many

Show HN: I am running 3 coding agents non-stop over the last 3 days. Here is how

1. Headless modeHeadless mode allows you to use the AI as a command-line utility for automation and scripting. In Claude Code you run it with the -p flag: claude -p, in codex - exec, opencode - run.2. Ask humanThe traditional communication channel with the operator won't work in headless mode - we need to implement a dedicated tool. Here is an example of how this can be done https://github.com/sermakarevich/claude/tree/main/mcp/ask_hu...3. Tasks queue

WebSocket reconnection in AI agents: transport recovery vs. session recovery

Your AI agent is mid-task, waiting on the result of a search tool call it made 30 seconds ago. The user is watching a spinner. Then a network blip drops the connection. The application reconnects in under a second, fast enough that most monitoring wouldn't flag it. But the tool call result that came back during the gap is gone, and so are the 200 tokens the agent generated before the silence began.The reconnect succeeded - but the session didn't.This piece covers why reconnection issues are

Ask HN: Reflecting on Talk Is Cheap

Hey folks,I read the essay (https://unessays.substack.com/p/talk-is-cheap) and I started reflecting about the AI progression in my company for the last year.I work at a small sized company with 25-30 developers. Since last year the company is enforcing AI on all levels, whether it be about writing tickets, coding, architecture, documentation, business decisions or user and market research.As the essay suggests, we on a all-time low on shipping value to our customers or produc

Ask HN: Is software engineering still a good career choice for new students?

I asked 4 working engineers this exact question on my podcast: a Google Developer Advocate (Stockholm), a Senior Software Engineer/consultant (Paris), an NVIDIA Deep Learning Institute Instructor (Morocco), and an Infrastructure Engineer at IBM (Dublin).Here's what they actually said:- The Senior Software Engineer said: "LLMs are babies. If you don't understand the architecture behind everything, you won't be able to follow."- The Google advocate pushed back slightl

Show HN: Brooks-Lint – AI code reviews grounded in 12 classic engineering books

I once managed a small team and hired an intern to develop the backend services for a software system. He used AI tools to write the entire project; while it ran correctly and produced the right results, the directory structure was atrocious upon review. Typically, a FastAPI service is organized into components like routers and services, but he had created an unnecessarily deep, multi-layered structure within the service layer—logic that should have simply been split across two or three files. T

Show HN: Atlasphere – Live Infrastructure Diagrams

Hi HN. My name is Andrey. On a regular business day, I'm a software engineer working at AWS. Outside of work hours, I spend time on my hobby - writing code.I was once building a pet project that allowed customers to spin up fully synchronized blockchain nodes within just a few minutes. The backend was split into a control plane and a data plane, each with its own AWS account. Later I added two more AWS accounts. One for shared RPC nodes. One for the Analytics Service.Since I love to visuali

Show HN: Why aren't popular book trackers offline-first?

It was 9 am on the train out of London St. Pancras and I had just finished the last chapter of a book I had been reading for weeks and I tried to log it on that rain forest app (you know which one :D) & it just kept spinning due to no signal and then the Software Engineer in me thought - I just want to note that I finished a book, why does it even need the internet?Then I started building Pick Up during that weekend and designed it with an offline first architecture and then I realised I nee

Temporal made execution durable. Ably makes sessions durable.

When Temporal launched, a lot of people had the same reaction: "We have queues and retries. We don't need this." (Temporal's own blog addressed this directly.) That reaction made sense. Queues solve queue problems and they do it well.What Temporal gave you was something different: a named execution context that survives a server restart and picks up from its last checkpoint. Not a better queue. A different abstraction entirely. If you built with it, you couldn't imagine going back. If you hadn't

Temporal made execution durable. Ably makes sessions durable.

Introducing the Snowflake and AWS Custom Lens for the AWS Well-Architected Framework

Running Snowflake on AWS means navigating two distinct sets of best practices simultaneously: AWS Well-Architected guidance for infrastructure, and Snowflake Well-Architected Framework guidance for compute, data organization, and governance. Without a unified review framework, security controls go unmapped to Snowflake configurations. Production readiness timelines stretch as teams reconcile guidance from two separate review processes, and compliance posture becomes difficult to demonstrate when

A universal test suite for Ably SDKs

At Ably we've been able to make a transformational change in how we build SDKs as a result of what's now possible with LLMs. In this post I explain how.The problemAbly's service is accessed by clients using a range of client libraries, or SDKs. The core Ably Pubsub product is supported by SDKs for a comprehensive range of languages and platforms, both for end-user clients (iOS, Android, Browser, React Native, etc) and servers (Go, Python, Java, .NET, PHP, etc). Each SDK implements the same funct

Ask HN: What is your (AI) dev tech stack / workflow?

Hello, happy Friday!I am looking to do some in-person "developer boot-up" workshops, and seek your suggestions for "modern tooling".The background of the participants range from motivated newbie ("I heard you can make your own app with AI!") to existing software developers who want to get up to speed on modern development for the purposes of building stuff, and getting jobs where AI tools are being used.For those who have been doing software development & "

A wild idea: Abstract reality using ontology

# A Wild Idea: Abstract Reality with Ontology## Background Large language models (LLMs) debuted with GPT-3 back in June 2020. After roughly five to six years of development, I believe the technology is still in its infancy, with massive room for improvement. A major priority is building powerful models that run on fewer resources, especially capable models that can operate smoothly on CPUs.More crucially, the engineering ecosystem around LLMs is also at an early stage. Many unresolved challenges

Show HN: Command Center, the AI coding env for people who care about quality

Hi HN! We’re Jimmy and Ray. Jimmy is a Thiel Fellow with a Ph. D. from MIT who has worked on programming tools for 15 years; Ray became VP of Sales at a $2B company when he was 19 and has built side-businesses vibe-coding.Last year, we set to answer the question “If AI can write code 100x faster, then why aren’t you shipping 100x faster?” What we learned shocked us — even fairly nontechnical people and solo founders told us they were spending more than half of their development time reading the

Show HN: Lich, start a dev stack per coding agent in parallel

Hey HN, Lich is a worktree aware local dev stack orchestrator. Simply put, it allows you to run multiple copies of your development stack from different worktrees with different code in parallel without going insane. I built Lich because I’ve found myself increasingly using multiple parallel coding agents for development work. I wanted my coding agents to each have independent copies of my development stack to be able to test and validate their own work well. I found that trying to do this total

Show HN: Alternative to WebXR, TypeScript SDK for multi-user VR app development

Hi HN, I am building Adamas VR, a TypeScript SDK and runtime for building multi-user VR projects.The motivation for this project is that the traditional game-engine based VR development workflow often requires developers to rebuild the common VR infrastructure. To reduce the overhead of VR development, I wrapped the common VR subsystems, such as avatar, locomotion, and multiplayer, directly into the runtime environment, so that developers can only focus on the application logic instead of rebuil

Ask HN: How do you run your agent swarm?

I passed through some evolution, from todo list with /clear + "take next task" prompt to cleaning most of the skills/plugins/claudemd, using centralized beads db, developing ask_human mcp on sqllite and creating lightweight python orchestrator with ui: https://github.com/sermakarevich/fleet.My use cases are:- centralized interface for spawning unrelated single tasks in parallel- coding with spec driven development approach: https://github.co

Automate medical record digitization with Amazon Bedrock Data Automation and AWS HealthLake

Healthcare providers manage millions of paper medical records that remain disconnected from modern clinical systems. Clinicians make decisions without full patient histories, organizations spend millions on manual data entry, and critical information stays trapped in formats that modern applications can’t read. The technical challenge is clear: how do you transform unstructured, scanned documents into standardized, interoperable health data at scale, without building custom machine learning (ML)