Dev Systems
10 Years of Meta’s Commitment to Python
This year marks Meta’s 10th consecutive year as a sponsor of the Python Software Foundation (PSF), the charitable organization dedicated to advancing, supporting, and protecting the open-source Python programming language and the community that sustains it. Python is one of the world’s most influential programming languages, and we use it across our engineering stack, from thebackend of our apps and products like Instagram and Threads to cutting-edge AI research. We recognize the vit
AI chat stream resumption: when Redis is enough, and when you need durable sessions
There's a well-worn path to resumable AI chat streams: find the Vercel SDK docs, implement Redis-backed replay, and ship it. For many products, that's the right call.The challenge arises when the product goes further than that. AI customer support tools that handle complex queries over 30-plus seconds. Agents that keep working while the user switches from their laptop to their phone. Products deployed to enterprise customers whose networks terminate long-lived Server-Sent Events (SSE) connection
Caching in Distributed Systems Part 1
Caching In Distributed Systems Part : 1 Now, let's understand what caching is. Whenever your application needs data, it usually ...
Lessons learned from scaling to 1 million Lambda functions
In this post, we share our journey and the lessons learned from building and running a fully serverless, multi-account software as a service (SaaS) platform at scale. We’ll explore why true scale-to-zero is critical, how we handle quota management, why engaging AWS service teams early saved us from outages, and which unexpected practices emerged once we scaled from thousands to over a million functions. At ProGlove, we build smart wearable barcode scanning solutions that connect frontline worker
Preventing data exfiltration in machine learning environments with Amazon SageMaker AI
If you’re building machine learning solutions with sensitive data, you face a persistent challenge: preventing data exfiltration while enabling data scientists to work productively. iBusiness, an AI-driven fintech organization, needed its data scientists to work with sensitive data to fine-tune and improve machine learning models. As the data science team scaled, traditional air-gapped environments and monitored virtual desktops proved unsustainable, leading to high costs and operational complex
Dual-token authentication for Nakama game servers with Amazon Cognito on AWS
When your game server needs both a managed identity provider and its own session system, players face a broken experience if authentication forces a redirect or stalls gameplay. Dual-token authentication for Nakama game servers with Amazon Cognito solves this by connecting two independent session systems, each with its own token lifecycle, without interrupting the player. This post shows you how. Amazon Cognito handles player identity and Nakama manages game sessions. Cognito issues a JWT, a ser
Gemini can now take notes in Google Meet for Google AI Pro and Ultra subscribers.
<img src="https://storage.googleapis.com/gweb-uniblog-publish-prod/images/TNFM-header-light.max-600x600.format-webp.webp">Google Meet's "Take notes for me" feature is available to Google AI Pro and Ultra subscribers in select languages.
GenPage: Towards End-to-End Generative Homepage Construction at Netflix
Authors: Lequn Wang, Jiangwei Pan, and Linas BaltrunasFigure 1. Autoregressive homepage generation. GenPage builds a Netflix homepage one row or entity at a time, each one conditioned on what’s already on the page and the user’s context.IntroductionThe Netflix homepage is the first thing users see when they open the app and the primary way they discover content to enjoy. Almost every part of it is personalized, including which rows appear, which entities show up within those rows, and how everyt
Show HN: Write SaaS apps where users control where their data is stored
Hello HN,I would like to share with you linkedrecords.com - an open source backend as a service I'm working on since some time now. You can think of it as an firebase/convex alternative with an interesting twist.In 2018 I needed to write large software requirements/architecture documents in Google Docs. While I was annoyed by the limitations of Google Docs back then (no captions on figures, no automatic heading numbering, slow when docs are bigger,...) I was still fascinated by th
Show HN: PostgreSQL backup tool Databasus moved to PG 17 native physical backups
An earlier version of Databasus shipped a backup agent: a binary that ran on the database host to stream WAL and create physical backups locally. That first implementation turned out to be a mistake, and we removed it. Physical backups now run remotely from the Databasus host, as described above.Why the agent was the wrong approach:• It was a naive implementation that only copied WAL on top of full backups, which led to a long RTO• Users had to configure both Databasus and a separate agent, when
Show HN: Proxy Block-CAGE, a new sparse block attention
Hi, I'm a PhD student in Bioinformatics/Computational Biology with a software engineering background,I'm trying to pivot toward AI/ML research. I'm familiar with the practical side of AI as in using, Scikit learn, R, Pytorch, ONNX Runtime etc...I was thinking if LLMs could be used as a research assistant to create better AIML algorithms. So I asked ChatGPT to help find better way to solved one of the most computationally intensive problems in Transformer architecture ba
Show HN: Visual Workspace for Agents Based on Unix
Hey HN,Thijs here! I'm the founder of Prototyper and today we're launching the first visual canvas built for agents.Couple of interesting lessons from building the product that I think are worth sharing:For the agents, everything is a file. In Prototyper, everything from plans, to apps, and diagrams, can be read as a file.We found that a filesystem is the most natural way for an agent to navigate: it discovers new content and functionality just by traversing the tree.We kept this layer
Ask HN: Is Multi-core a thing of the past?
Modern CPUs e.g XEON 6 have 144 cores, 144 threads - which to me seems a heavy misalignment between the hardware engineers making the CPUs & the software engineers using the CPUs.on the software side - in distributed systems - most systems when containerized assume they're gonna be utilizing one CPU core in a horizontally distributed manner i.e many pods etc. the other pods could be on different machines.then the language platforms e.g JVM, Golang, JS are going the route of green thread
How durable sessions unify human-to-human and human-to-agent messages
AI chats are often a rather solitary experience: just you and ChatGPT, sitting there together, solving a problem. But so many of the tasks that we perform day to day are ones that benefit from, or often even require, collaboration with other people such as colleagues, family members, or friends.So, if AI agents are helpful, and other people are helpful, then how can we provide a space for multiple people to collaborate with each other and with AI agents?This is a question to which the flagship A
Is AI making your teams better, or just busier?
AI adoption programs tend to end in the same place. Tools are accessible, usage is up, and there's a dedicated Slack channel for wins. Six months later, nothing about how the team works has fundamentally changed. People are doing the same things – just slightly faster. And it’s easy for programs to stall when you’re measuring the wrong thing. Adoption (whether people have access and whether they're using the tools) is visible and easy to report. It tells you nothing about whether the team i
One person, one vote: building live voting with message annotations
Live polls are a staple of conferences, streams, and all-hands: a question goes up on the big screen, everyone votes from their phone, and the bars race each other in realtime.There's a lot of different ways you could implement this.The most obvious way is a CRUD app backed by a server that votes are POSTed to, and the server keeps a running count. But this is the Ably blog, so we're obviously going to use Ably Pub/Sub to build something which does not need each vote to go via your server. That
Privacy-Aware Infrastructure in the AI-Native Era: An Asset Classification Case Study
Privacy controls — systems that enforce retention, access, allowed-purpose, downstream-sharing, or anonymization policies — require a reliable understanding of data to function. Before such a control can operate effectively, it must know exactly what it is looking at. This can be complex, as demonstrated by a field simply named “age“: In one context, it might describe a person and require strict protections, while in another, it could be a cache time-to-live (TTL) numerical value in
Show HN: eBook to audiobook narration with realistic AI voices
For a while I've wanted to try out the new AI voices for long-form narration, but everything I found required a subscription that didn't justify my limited usage. I came across the open Kokoro model [0] and the voices are very good -- good enough to listen to for hours without the fatigue I got from legacy, robotic TTS voices. The model is 82m parameters and designed to run fast, but I still struggled to get reasonable times from CPU inference on my 12-core laptop. I thought a cloud-ba
A 30 Year OG Application Developer Available
https://www.youtube.com/watch?v=DACtpW9Q-hcThat link is the #1 Architectural Interior Design software used by the top firms in the world. What you are looking at is the result of pure architectural discipline. To handle massive global budgets, complex subcontractor workflows, and real-time synchronization with massive enterprise CAD suites, I engineered a closed-loop, self-aware data object model. The data objects carry their own application logic and database schemas. It is a zer
Show HN: TLA+ Process Studio
Disclaimer: This was made with LLMs.I made this tool to help understand large business processes that can be modelled as a single state machine.The core loop of this is to enable to walk stakeholders through discussing each step, adding comments, and reiterating with an LLM of their choice to generate the TLA+ syntax on the left.Users can click through the green state nodes to see how things work visually.You can see some sample state machines in the dropdown in the top left.The power would come