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It is straightforward to configure a minimal API to produce an OpenAPI document at build time . This runs the API during build, requests the OpenAPI document from it, and saves it to disk. The slightly trickier part is to put checks in Program.cs to exclude any startup code that cannot run at build time. This is typically done because configuration key/value pairs are not available at that time. For example: if (! isBuildTime ) { connString = builder . Configuration . GetConnectionString ( "AppDB" ) ?? throw new InvalidOperationException ( "Connection string 'AppDB' is not configured." ); builder . Services . AddDbContext < AppDbContext >( options => { options . UseNpgsql ( connString ); } ); } The question is how to deduce that the API has been launched at build time, i.e. isBuildTime should be true? The official way of doing this is to check that the assembly that invoked the API is "GetDocument.Insider" : var isBuildTime = Assembly . GetEntryAssembly ()?. GetName (). Name == "GetDocument.Insider" ; GetDocument.Insider.dll is the command line tool that automatically runs during build of the API if the .csproj includes the following reference: <PackageReference Include= "Microsoft.Extensions.ApiDescription.Server" Version= "10.0.7" > ... </PackageReference> This package is a shim. It only provides build targets and props and hooks into the build of the API to run the command-line tool dotnet-getdocument . This tool in turn runs the command line tool GetDocument.Insider that we check for. This is a pretty convoluted sequence: Microsoft.Extensions.ApiDescription.Server provides targets that run during build of the API. One of those targets runs the command line tool dotnet-getdocument That in turn runs the command line tool GetDocument.Insider That in turn runs the API and fetches the /openapi/v1/json (or other configured endpoint) to get the OpenAPI document and saves it to disk. Checking in Program.cs if the API was invoked by the assembly GetDocument.Insider.dll t

The problem I often switch between Codex, OpenCode, Cline, Claude Desktop, scripts, and terminals. The annoying part is not starting a new tool. The annoying part is explaining the same workspace state again: what changed what is still pending what should not be touched what tests passed what the next agent should read before editing What I built AgentContextBus (acb) is a local-first CLI for handing off workspace context between coding agents. It saves a local handoff packet, then lets the next agent read it through: paste-ready prompts brief prompts a local dashboard JSON output explicit MCP tools First run npx @xiaoshuo1988/acb verify first-run For Chinese output: npx @xiaoshuo1988/acb verify first-run --lang zh-CN A normal handoff From the agent that has context: acb handoff --from codex --summary "Ready for the next agent" --git From the receiving side: acb receive --latest After the receiving agent summarizes the packet: acb ack --latest --by opencode What ACB intentionally does not do no hidden prompt injection no traffic interception no third-party client config mutation no cloud sync no background daemon Why local-first I want the user to be able to inspect the packet store, copy text manually, and decide exactly when context crosses from one agent to another. What I want feedback on Is the handoff packet concept clear? Is verify first-run enough to understand the tool? Is receive --latest the right receiving-side command? Which client path needs the most work? Would you trust this workflow in a real project? Repo: https://github.com/xiaoshuo1988130/acb Feedback discussion: https://github.com/xiaoshuo1988130/acb/discussions/1

Google AI Studio Mobile + Gemini Managed Agents: Build and Deploy AI Agents Without Infrastructure in 2026 TL;DR Summary Google AI Studio is now a standalone mobile app on iOS and Android — speak an idea, and a working app builds in the background Gemini Managed Agents deploy reasoning agents with one API call — code execution, Google Search, URL reading, file management, and web browsing included Agents are configured via markdown skill files (SKILL.md), not complex orchestration code — no server setup, no sandbox management State persists between sessions — files and context survive, no re-uploading Prototype on mobile , refine on desktop , share live deployment via URL — continuous workflow across devices Direct Answer Block Google has launched two new agent surfaces: AI Studio Mobile (a standalone iOS/Android app where you prototype with voice or text and see generated apps on your phone) and Gemini Managed Agents (serverless reasoning agents deployed with one API call, including code execution sandboxes, web search, browsing, and file management, all configured via markdown skill files instead of orchestration code). Introduction The gap between "I have an idea" and "I have a working AI agent" is mostly infrastructure. You need a server, a sandbox, tool integrations, state management, deployment pipelines. Google's two new releases collapse that gap from both ends: AI Studio Mobile removes the need for a desk, and Gemini Managed Agents remove the need for infrastructure. Together, they let you go from voice note to deployed agent without touching a server config. How does Google AI Studio Mobile let you build and preview apps entirely from your phone? AI Studio Mobile is a standalone app (iOS and Android) that brings Google's AI development environment to a phone. The workflow described in the AlphaSignal newsletter: Speak or type an idea — "Build me a weather dashboard with 5-day forecast and location search" App builds in the background — AI Studio's agent in

You Accumulate Technical Debt When You Skip Code Review. Here's What You Accumulate When You Skip the Human. There's a concept in software engineering called Technical Debt. You skip the right abstraction, move fast, ship. Someday you pay it back in refactoring hours. I've been thinking about a different kind of debt. One that doesn't show up in your codebase. Human Debt: When you build with AI as your only collaborator, you remove the one thing that makes you feel obligated to show up. Not accountability in the corporate sense — the simpler thing. Someone is reading your work. You don't want to waste their time. That's not a productivity hack. It's closer to a structural property of how humans behave when observed. The Research Didn't Start With AI In 2015, Gail Matthews ran a study on 267 professionals tracking goal completion. One group wrote their goals. Another group wrote their goals and sent weekly progress reports to a real person. The second group completed 76% more of their goals . Not 10% more. Not "statistically significant at p<0.05." Seventy-six percent. The mechanism is what Gouldner called reciprocity norm in 1960 (doi: 10.2307/2092623): when someone gives you their attention, you owe them something back. Not contractually. Biologically. You don't want to disappoint someone who showed up for you. Harkin et al. confirmed this across 138 studies, 19,951 participants — the effect holds across cultures, domains, and formats. None of this was discovered because of AI. It was hiding in plain sight for 65 years. AI Has No Concept of Day 14 Here's what changed. For most of the history of side projects, your "collaborator" was a rubber duck or Stack Overflow. Those tools don't simulate accountability. Nobody was surprised. Then came AI pair programming. Which is genuinely useful. But it introduced a specific failure mode: you now have a collaborator that responds, scaffolds, and generates — but doesn't notice when you stopped. AI has no concept of Day 14. It

I often record my screen for clients to show what I’ve built or how something works. But almost always I end up writing detailed comments and explanations anyway, because they just blink and miss things in the video. So I thought it’d be cool to add freeze-frames with annotations right inside the video, to pause their attention and explain what's happening at that exact moment. I tried doing this in video editors, but it takes way too much time, so I hated the process. But the videos with freeze-frames actually worked great for my clients. I got way fewer questions from them. That’s why I decided to build a tool to add freeze-frames and annotations quickly and easily. I wanted it to feel as simple and natural as drawing in Excalidraw. Let me know if you find this useful, or if it feels unnecessary. You can try it here: https://framepin.com . There is a quick demo to save you time. No registration, everything works locally in the browser. submitted by /u/aksuta [link] [留言]

So for about 10 years I've been wanting this every time I'm on a scam website or news article that has no comment section or locked reddit thread. I've seen a couple similar attempts, but most of them focus on personal notes or having drawing features and things I'm not really interested in. This is just about letting users, customers and the general public communicate about URLs and sub-urls the websites themselves don't provide or won't provide the public the ability to comment on. In the extension you can see how many comments are on a URL and your notifications if anyone replied to you. There are some rules like everyone is only allowed one top level comment to reduce spam or potential bots. You can replay as many times as you want. You can also edit your top level comment, which will show last when it was edited. Here is the main list of reasons I created it: Warn people on scam websites when they go there they can just read the comments Comment on locked social media posts, x profiles, youtube videos, reddit threads etc.. Comment on news articles that have no comment section Comment on top of social media that would otherwise require an invasive account to comment. Almost all social media also has a url these days. This also works with any string so technically you can comment on anything including, addresses, businesses, cities. If you paste in a URL it will normalize it so you won't accidentally create a duplicate forum. On the PublicNotes.xyz homepage you can just create a forum based on anything. Feedback and bug notes welcome. Website: https://publicnotes.xyz Chrome extension: https://chromewebstore.google.com/detail/public-notes/keaopkaplnpjhccneageakejbbbeoncp?pli=1 submitted by /u/PandorasBucket [link] [留言]

I've been working on a side project called WEBDEVPACK - a collection of free web-based tools for developers, designers, and generally anyone working online. The idea is simple: lightweight tools that help us solve everyday problems. Check it out at webdevpack.com submitted by /u/ivopetkov [link] [留言]

I'm working on a self-hosted search service called Hister with the goal to reduce dependence on online search engines. Hister is a full text indexer for websites and local files which automatically saves all the visited pages rendered by your browser. It provides a flexible web (and terminal) search interface & query language to explore saved content with ease or quickly fall back to traditional search engines. I've been using it for a few months and as my local index is growing I can avoid opening google/duckduckgo/kagi - and even websites listed in results - more and more frequently. The initial reception is overwhelmingly positive with already more than 30 contributors and hundreds of contributions - perhaps you can find it useful as well. (Or at least have some constructive criticism =]) The code is AGPLv3 licensed, available at https://github.com/asciimoo/hister , read-only demo: https://demo.hister.org/ , website: https://hister.org/ submitted by /u/asciimoo [link] [留言]

Hello! I am Axel and I’ve been building Kanto, a small forum platform for niche communities. The main idea is that communities can allow normal posting or optional anonymous posting which is fully secure and private, while still requiring accounts behind the scenes. Users can create communities, start threads, reply, and browse communities around specific interests! :) I’m trying to keep it simple and privacy-friendly: no ads, no selling user data, and a cleaner experience than huge social platforms, not like the big american social media companies that sell your data. https://kanto.forum submitted by /u/axeeeeeel- [link] [留言]

This is a submission for the Hermes Agent Challenge: Write About Hermes Agent Hermes Agent...

https://preview.redd.it/rbt6z0s1k84h1.jpg?width=1200&format=pjpg&auto=webp&s=87b4980b47fb45994978a1a719b5fbf3180c0860 – 6+ years of shooting, stitching, retouching, design and coding – Built solo. 0 funding, 0 sponsors, 0 ads. – Free for everyone – 80 places online 170 HD 360° panoramas (still only around 30% of what I've shot so far) – Map mode for browsing places across Tasmania, immersive journeys for larger full-screen 360° tours https://tas360.au submitted by /u/vla_dis [link] [留言]

https://lifeappbybabs.netlify.app I want to see if it's worth investing in and buying a domain name submitted by /u/Miserable_Spirit3319 [link] [留言]

A $0 multi-model decision agent: three LLMs debate, Hermes judges, and it learns who to trust.

TL;DR : Built a RAG pipeline, allows you to upload docs and connect via API/MCP to service. need feedback if you find it useful or confusing: https://rig-rag.vercel.app I got into the whole AI, embeddings, etc workflow for another project of mine and while pretty fascinating how this all ties together, I thought that it is perhaps also useful to others who don’t want to rebuild the whole pipeline from scratch every time. (also, competition seems pretty costly). It is pretty simple: Make account, make memory space, upload your stuff, configure how you want it retrieved, setup scoped API key, connect your AI to the hosted MCP → done. RigRAG lets you: upload / index documents search them via a simple HTTP API or MCP optionally configure retrieval settings like top-k, candidate count, chunking, etc. Currently entirely free to use since I would want to gather feedback first if it's worth pursuing further before I spend too much time into it. I’d really appreciate feedback on it, if something is unclear to setup, should be improved etc. I’m not trying to do a big launch yet so this is more of a “please try it, and tell me what sucks or if its good” thing. Here the link again: https://rig-rag.vercel.app And for the MCP: https://rig-rag.vercel.app/api/mcp submitted by /u/Odysseyan [link] [留言]

submitted by /u/Last_Success5724 [link] [留言]

Production incidents almost never break in one place. The alert fires in one tool. The broken deploy is in Netlify. The suspicious change is in GitHub. The stack trace is in Sentry. The human context is in Slack. The runbook is in Notion. The "is this actually paging someone?" answer is in PagerDuty. A normal chatbot can sound helpful in that situation. It can say things like "you should check your recent deployments" and "look for related errors in Sentry." But that is not triage. That is a polished to-do list. I wanted something more useful: an agent that could go get the evidence, connect the dots across sources, show its work, and give an operator-grade answer grounded in real system data. The design constraint from the start was simple: no evidence, no answer. That became ReefWatch , a Coral-powered production triage agent built to investigate instead of improvise. It discovers the tools connected to a workspace at runtime, queries them as evidence, correlates records across systems, and produces a compact answer only when the facts support one. Coral became the backbone because it turns the messiest part of agent tooling into something the model can actually reason about: SQL . What This Guide Builds By the end of this route, you will have a blueprint for an agent that can: discover connected Coral sources at runtime query production systems through read-only SQL correlate evidence across code, deploys, errors, alerts, chats, and runbooks stream every query and row count into an inspectable UI run the same investigation workflow from a CLI when you want a scriptable path generate an incident report only when the evidence supports one stay focused with policy layers instead of a giant prompt blob In one sentence: ReefWatch is a Coral-powered investigation workspace that lets an agent discover connected tools at runtime, query them with read-only SQL, stream the evidence trail, and generate an incident report only when the facts actually support one. Why Coral B

submitted by /u/Kriem [link] [留言]

Hiring an AI Development Company? Ask These 7 Questions First Most AI projects fail long before deployment. Not because the model is bad. Because teams skip the hard engineering questions. If you're evaluating an AI development company, ask these 7 questions first: 1. How is data secured? AI systems process sensitive business information. Ask: Where is data stored? Is encryption enabled at rest and in transit? Who has access to prompts, logs, and embeddings? Are enterprise security standards followed? Security should be designed in from day one. 2. What observability exists? You can't improve what you can't monitor. A production AI system should include: Request tracing Prompt/version tracking Latency monitoring Cost visibility Error reporting If nobody can explain what happened after a bad output — that's a problem. 3. How do you handle model drift? AI performance changes over time. Questions to ask: How are outputs evaluated? Is feedback collected? How are prompts/versioning managed? What happens when accuracy drops? Production systems need iteration loops. 4. What happens during failure? No system is perfect. Ask: Is there fallback logic? Human review? Retry handling? Graceful degradation? Failure handling matters more than demos. 5. How is access controlled? Enterprise AI systems require permissions. Examples: Role-based access API authentication Audit logs Team-level controls Not everyone should access everything. 6. What compliance assumptions exist? Especially important for regulated industries. Ask whether the system considers: GDPR SOC2 HIPAA Financial or internal compliance rules Compliance cannot be an afterthought. 7. Who owns the infrastructure? Clarify ownership before signing anything. Ask: Who owns the source code? Cloud infrastructure? Models and prompts? Data pipelines? You should avoid vendor lock-in. AI success is rarely about flashy demos. It's about secure infrastructure, reliability, observability, and long-term maintainability. What question

been maintaining a privacy first clipboard manager chrome extension for a while. recently shipped a snippets feature where you type /keyword in any text field and it expands to whatever you saved i use it for: - my product pitch so i dont rewrite it every time - boilerplate comments on github or pr reviews - pasting my product link into discussions - common replies i send over and over it supports two types - rich text with formatting for things like emails, and code with syntax highlighting if you need it. the expansion works through a content script on all websites. comes with a management page where you can search filter by type or language and edit your snippets. everything is saved locally only on your device, currently these are not synced, let's see if user needs the sync facility for these or not. NOTE: currently figuring out how to make this feature work on Google Docs and MS Word submitted by /u/nhrtrix [link] [留言]

This is a submission for the GitHub Finish-Up-A-Thon Challenge What I Built I revisited my personal website and decided to turn it into a more complete and polished portfolio. The project originally started as a simple personal website hosted on GitHub Pages. While it was functional, many planned features and improvements were never completed. For this challenge, I am working on improving the mobile experience, adding dark mode support, enhancing the Projects section, improving SEO, fixing existing issues, and making the website more interactive and professional. My goal is to transform an unfinished personal website into a modern portfolio that better represents my work, skills, and projects. Demo Live Website https://ehsankahrizi.github.io/ GitHub Repository https://github.com/Ehsankahrizi/Ehsankahrizi.github.io Current Status This project is currently being improved as part of the GitHub Finish-Up-A-Thon Challenge. Planned improvements include: Better mobile responsiveness Dark mode support Enhanced Projects section Improved SEO More interactive user experience Better website performance Additional pages and content Fixing existing usability issues The Comeback Story When I returned to this project, I realized that many ideas I originally had for the website were still unfinished. Although the website was online, it still had several limitations: The mobile experience needed improvement. Dark mode was not available. The Projects section was incomplete. The contact functionality needed attention. SEO optimization was missing. The website relied on a mostly single-page structure. User interactions were limited. Performance could be improved. Instead of starting a new project, I decided to revisit this existing one and finally complete the improvements that had been postponed. This challenge provided the perfect opportunity to continue development, clean up the codebase, improve the user experience, and turn the website into something I can confidently share with ot