Hi HN, I built this. Quick background on why it exists:When music is streamed on digital streaming platforms (think Spotify, Apple Music, Pandora), there are two separate royalty streams: one for the recording, paid through your distributor (DistroKi...
NAEOS is an open-source engineering system for AI coding agents.It provides architecture, engineering standards, policies, specifications, and validation wworkflow to help agents build software within a consistent engineering context
I'm trying to make an app to help out my local community, but with the intention of scaling it at some point and serving a much wider community. It's a complex app with a lot of moving parts, and as a junior dev with little experience in so...
In this post, you learn how AgentFlo built intelligent sales agents that convert conversations into completed purchases. We show you how AgentFlo improved revenue performance in early deployments using Amazon Bedrock AgentCore and the Strands Agents SDK. AgentFlo, the agentic commerce service by Salesflo, helps merchants deploy always-on AI sales, support, and ordering agents across channels like WhatsApp. These agents understand intent, connect to commerce systems, recommend products, create ca
Many discussions about Microsoft Foundry Agent Service eventually arrive at the same question: should this workload be implemented as a Prompt Agent or a Hosted Agent? While the documentation explains both options well, the architectural decision usu...
Clario, part of Thermo Fisher Scientific, uses Amazon Bedrock to automate PHI (Protected Health Information) and PII (Personally Identifiable Information) detection across thousands of DICOM (Digital Imaging and Communications in Medicine) image slices in clinical trials. Each image slice may carry PII or PHI hidden in metadata tags, in custom vendor fields, or burned directly into the pixels. Across imaging sites, central labs, sponsors, and CROs (Contract Research Organizations), every one of
AI agents built on Amazon Bedrock AgentCore let clinical trial teams make fast, accurate enrollment decisions while keeping clinicians in control through human-in-the-loop oversight. According to the Tufts Center for the Study of Drug Development, 80 percent of clinical trials miss their enrollment timelines, and each day of delay costs an estimated $500,000. Today, eligibility decisions rely on manual chart review across fragmented sources — EHR notes, lab results, imaging reports, and medicati
I built a Human + multi-Agent shared memory system I use daily for my coding workflow. It helps reduce Agent drift by formalizing Human decisions and storing coordination logs. We're calling it Agent Mesh.You can try it out yourself via the GitHub link or pip install my-agent-mesh. Simply point your AI Agent to Agent Mesh and ask it to review the README and adoption docs. Your Agent will automatically review it, prompt you for any input needed, add your input to a decision log, and give you
Hi everyone!! I made my own personal static website inspired by my friend's Carrd. I ended up implementing a browser-native post-quantum PGP-like system: signed and encrypted messages are carried directly in URL hash fragments, so the user does not need any accounts, specialized software, or key uploads. Once installed as a PWA, verification and decryption can run fully offline; the only thing that needs to reach the device is the URL itself. Clicking a link with a signed message automatica
As AI applications scale from reactive bots to autonomous agents, their reliability is bound to the speed and accuracy of the data layer beneath them. The integrity crisis nobody is talking about There’s a quiet assumption baked into most AI architectures today regarding data layer consistency, and it’s costing companies more than they realize. The assumption is that the data your AI agent reads is the current state of reality. In a world of distributed systems, cross-region replication, and aut
This is an interesting use case that gets talked about much less, and potentially one that is more useful than software development. Especially now that everyone is relying heavily on AI and even forgetting things they used to know.<p>Have you explored this yourself or found any existing workflows for mastering technologies, concepts, theory, basically everything that we have traditionally learned manually, from university onward?
When Bosch Mobility Platform Solutions set out to unify vehicle tracking across India’s fragmented spot logistics market, they faced a daunting reality: dozens of telematics providers, incompatible data formats, and thousands of concurrent tracking requests — all needing real-time resolution. The result was L.OS, a serverless platform on AWS that standardizes this chaos into a single visibility layer. In this post, we’ll show you how Bosch Mobility Platform Solutions (MPS) uses AWS services to s
In May, I introduced the open-source Azure Architecture Diagram Builder as a way to move from a natural-language prompt to an Azure architecture diagram, cost estimate, Well-Architected assessment, and deployment guidance. In July, I shared how the project had become agent-ready through Model Context Protocol (MCP).Those posts described what the tool could do. The more interesting story came next: what happened when people actually used it.As adoption grew, the central product question changed.
I’m 18, and I’ve recently solved my 823rd problem on LeetCode with a 430+ day streak. After a year of doing this every single day, I can confidently tell you: LeetCode is a dry platform for micro-optimization, and it has almost nothing to do with real software education. It shouldn't, but it's a problem.The biggest flaw is the learning loop. When you encounter a new architectural or algorithmic concept, you are forced to break your flow. You have to leave the platform, read abstract do
One of the very first problems I hit when I started to do agentic programming was the context problem, and that my agent always started again from the beginning. Being a bit naive and not really knowing what I was doing, I started off writing a mcp tool (because those are cool, right?) to solve the problem.MD files are primitive, I thought. This memory stuff should really be a database, I thought. So I tried a couple of free memory tools, but nothing was really doing anything for my particular i
I've seen a few discussions over the years about how niche languages like Lisp, Forth, Prolog, etc. would be great to use, but even for personal projects the lack of available packages makes them hard to use. However, with an LLM you can have it replicate whatever package you'd like from a more popular language. You can even port software to your favorite niche architecture. If you really want to run your homelab off a PA-RISC machine you just give an agent SSH access and tell it to
Hi all,This is a project I’ve been working on for the last 10 or so weeks. Tesserae is a self-hosted dashboard server for e-ink panels.It allows you to build dashboards in two ways. A card-based editor that lets you tessellate different widgets side by side in resizable cells. Or a canvas editor which lets you drag and drop elements on a free-form canvas. You can also drive the canvas editor via MCP for some highly detailed dashboards.I fell down this rabbit hole after impulse buying a 13.3” Spe
I've been working on mr_tech, a from-scratch 3D engine in Go built around a question I wanted to answer:Can a 3D game be reverse-engineered, without infringing copyright, understood as source code, and transformed into a sufficiently general Intermediate Representation (IR) that allows it to execute on a runtime for which it was never designed?The idea is to treat a game as source code, not as its runtime — the way a compiler treats its source files.Instead of reproducing the original game
Hey everyone,In early 2026, I started working on Lark, with the goal of creating a realtime database with the same fundamental premise of Firebase RTDB: syncing a JSON tree with persistence to thousands of concurrent users. Today, Lark is releasing as open-source software under an AGPLv3 license.I've been building on Firebase RTDB since the earliest days, and I still think it's one of the most magical ways to build realtime apps for the web and mobile. However, I've always been bo
<img src="https://storage.googleapis.com/gweb-uniblog-publish-prod/images/Sheets_canvas-blog-header-2784x.max-600x600.format-webp.webp">Sheets canvas turns data into interactive dashboards, custom study trackers, seating charts, and more, all with a simple prompt.