Dev Systems - Building Systems That Scale

Introducing AI Transport v0.5.0: durable execution with Steps

AI Transport v0.5.0 is now available. It adds first-class support for running an agent turn inside a durable execution framework, such as Temporal or Vercel's Workflow Development Kit (WDK), while every client watching the conversation still sees one clean, resumable stream.The last release, v0.4.0, let an agent hydrate its history from your own database. This one is about what happens when the process running the agent isn't around for the whole turn.Two kinds of durabilityA durable execution f

Specification-driven composition for flexible data workflows

Specification-driven composition addresses a common scalability bottleneck in data pipelines. Data pipelines often start as simple scripts, but as they grow, you duplicate transformation logic and small changes cascade across multiple workflows. Copying and modifying data transformation logic across scripts leads to workflows that become difficult to manage at scale. Tracking what each pipeline does becomes harder because workflow intent is embedded in code. This lack of visibility complicates g

Show HN: CodeRadius, map and govern multi repo architectures

Hi HN,I deal with tens of repositories daily, in a company with thousands. Having a clear picture of real-time architecture relies on discipline and the goodwill of engineers to keep the (fragmented) documentation up to date. With coding agents, this problem grows at the speed of light.LLMs are good at explaining parts of code, but are very bad at extracting precise and reliable architecture mapping of big codebases, not to say when dealing with multiple repos of a microservices fleet (read: di

Show HN: I hated how much my 12-year-old played Roblox, so we built our own FPS

I'm a father of two, 7 and 12. They are obsessed with Roblox, especially Rivals.Like a lot of parents, we did not love it. We tried the usual things: block it, limit it, set timers." It became a daily battle, a lose-lose situation.So I flipped the problem.Instead of fighting what they loved, I decided to lean into it, but with a twist.Why just play an FPS when you could build one together?My kids became the PMs. Claude and I became their engineer.I was shocked by how fast we moved. We

We're rolling out AlphaEvolve widely to solve Google Cloud customers' hardest problems.

<img src="https://storage.googleapis.com/gweb-uniblog-publish-prod/images/1-Blog_hero_pic.max-600x600.format-webp.webp">Finding the most efficient algorithm — whether designing a microchip, routing a logistics network or accelerating medical research — can be challenging, with many possib…

Why AI agents need a durable session layer - and why HTTP isn't enough

HTTP works fine for a chatbot that responds in seconds. Add token streaming, and it mostly still works. But once an agent starts doing things that take real time, reasoning across multiple tool calls, spawning sub-agents, running for minutes instead of milliseconds, the UX starts to falter.The connection drops while the agent is mid-thought. The user switches tabs, comes back five minutes later, and the session is gone. The agent finishes its work, but the client has already moved on. The user w

Golden Paths Are a Product. Treat Them Like One.

Audience: Cloud architects, platform engineers, engineering leadersIn my earlier Cloud Native Platforms articles, I focused on how teams build, run, and evolve modern engineering foundations. This article focuses on what keeps those capabilities useful after launch.Most teams do not lose adoption because the first release was poor. They lose adoption because the path was launched like a project and left to survive like a product.The pattern is familiar. A capability ships with good intent, reaso

S&P Global’s innovative disaster recovery strategy using Amazon FSx for NetApp ONTAP snapshots

This post is co-written by Nishanth Charlakola from S&P Global. Organizations have a requirement to build high availability and disaster recovery (HA/DR) solutions for their complex SQL Server infrastructure to maintain data availability and integrity. With the rapid pace of cloud adoption, businesses across different industries have realized the value of a successful proof of concept (POC) for any technical project that migrates existing environments to the cloud. For companies of any size,

Optimizing GitHub Copilot Cost in the Usage-Based Billing Era

GitHub Copilot has become a core part of the modern developer workflow. We use it to complete code, explain unfamiliar repositories, write tests, refactor legacy applications, review pull requests, generate documentation, and automate repetitive engineering work.But as GitHub Copilot moves further into usage-based billing, teams and users are asking a very practical question:How do we keep getting value from GitHub Copilot without letting costs become unpredictable?The answer is not to blindly s

Show HN: Autoops – Multi-region data and service mesh operated by a Makefile

Hi HN, Stefan here. autoops is an infrastructure automation framework I have been using at my previous company and is now opensourced. It has been the base layer running various products and projects, and also for quickly standing up client infra.It works with Debian-based systems (apt) and sets up a WireGuard mesh with peer discovery and built-in DNS (Wesher), a distributed S3-compatible object store (Garage), and a reverse proxy and load balancer (Traefik). It supports service autodiscovery (T

Show HN: Foundation – A Tale of Tokens and Psychosis

I called my first experience with AI psychosis, master - https://github.com/nmxmxh/master-ovasabi.During the beginning of the coding agent expansion, compute was somewhat free to get with the right methods. I decided to finally build the backend project I'd always wanted to build.I settled on Go for the language. I'd always liked Go because it was easy for me to read whilst also always being in the top ranges for performance.I realise I'd tried to build a codeb

Show HN: Bytesalt – AI that finds bugs Playwright tests miss

Hey! I built Bytesalt and excited to share it here.Every engineering team I've been part of has had the same problem. Playwright (or similar) scripts pass, yet critical bugs showed up when real users used our software. I don't think this is because Playwright is inherently bad - it is doing its job perfectly well - testing exactly what we told it to test.The problem is - real world bugs happen because we didn't think to test a particular path - think a support widget covering the

The C4 Model for Documenting Architecture - Software Architecture

The C4 Model for Documenting Architecture - part of Software Architecture. How real systems are structured - tiers, layers, and the ...

Choosing an Architecture: A Decision Framework - Software Architecture

Choosing an Architecture: A Decision Framework - part of Software Architecture. How real systems are structured - tiers, layers, ...

Introducing AI Transport v0.4.0

AI Transport v0.4.0 includes changes to optionally support database hydration.Some applications may wish to store AI conversation history in an external store, such as a database. AI Transport's support for database hydration allows applications to reconcile that stored history with the live activity in the AI session.When using database hydration, your application persists messages for completed runs to the database. This allows developers to build additional functionality, such as search or an

Show HN: Enola-A deterministic architecture graph for developers and AI agents

Together with a friend, we were developing a golf application. Our codebase grew rapidly and became split between multiple repositories: the iOS app, Android app, backend, front-end, and extra tooling. Both of us also work in larger scale-ups, and we saw the same problem: understanding large distributed codebases becomes progressively harder. Yay for microservices.It takes time to understand and answer questions like: - What calls this function? - What is the impact of changing this interface? -

Launch HN: Manufact (YC S25) – MCP Cloud

Hi HN, we are Pietro and Luigi, cofounders of Manufact (https://manufact.com), a cloud for MCP apps and servers. We used to be called mcp-use, and still build open source SDKs for MCP under that name: https://github.com/mcp-use/mcp-use. We did a Show HN about that last year: https://news.ycombinator.com/item?id=44747229.Today we want to tell you about our cloud product, Manufact, which is to mcp-use as Vercel is to Next.js. Manufact is an MCP vertical

Meta’s AI Storage Blueprint at Scale

Over the past several years, model capabilities and training dataset sizes have experienced exponential growth. During the past year or so, the time between new-frontier-model releases has gone down from months to weeks. Reliable and fast access to storage is important to both the speed and computational cost of this AI innovation. If AI is the brain, storage is the memory: Capability and speed are highly dependent on the size of memory and speed of retrieval. Yet while AI compute performance h

Show HN: Shikhu – Understand the code your agents write

Agents write code really well, but it can get hard to understand what they've written and why. Shikhu is a CLI tool and Agent Skill that facilitates learning your code through self-quizzing, transcript analysis, and validation flows.I'm Arjun, I'm currently a developer advocate at Pinecone, and I use agents to code a lot!I enjoy using agents to code, but I've been feeling like I've lost some conceptual learning and understanding that comes with writing the code yourself.

We Reduced Development Time by 50%, Users Didn't Notice

We spent months optimizing engineering speed. Deployments improved. Users barely noticed. What moved engagement instead was fixing one confusing workflow. What's something your team optimized that users never cared about?