# Building Published articles for Building. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## A Speaker That Clips to City Poles and Leaves No Mark DevFeed: [A Speaker That Clips to City Poles and Leaves No Mark]() Original publisher: [Read original article]() Author: Ida Torres Published: 2026-09-16T22:30:15Z Content type: article Language: en Sources: [Yanko Design]() Topics: [systems]() Tags: [architecture](), [audio](), [audio-technology-concept-designs-public-speaker](), [building](), [concept-designs](), [design](), [public](), [sound](), [space](), [speaker](), [technology]() ### AI overview Mariami Kurtishvili's Orchid Sound System is a graduate thesis proposing stainless steel high-frequency horns that clip onto existing urban infrastructure without screws, drilling, or permanent marks. The project explores temporary communal sound in public spaces. ### Source excerpt A Speaker That Clips to City Poles and Leaves No Mark Walk down almost any street in an American city without your headphones in, and you will notice how little of that walk actually belongs to... ## Build Your Own AI Agent Harness in C#, the MafClaw Live Series DevFeed: [Build Your Own AI Agent Harness in C#, the MafClaw Live Series]() Original publisher: [Read original article]() Author: Bruno Capuano Published: 2026-09-16T21:00:00Z Content type: tutorial Language: en Sources: [.NET Blog]() Topics: [Agent Harness](), [Microsoft Agent Framework](), [AI Agent](), [C#](), [.NET]() Tags: [agent](), [agent-framework](), [agent-harness](), [ai](), [building](), [c-sharp](), [cloud](), [csharp](), [microsoft-agent-framework](), [microsoft-reactor](), [net](), [observability]() ### AI overview This article introduces a four-part live series that builds a complete C# AI agent using the Microsoft Agent Framework harness. It describes adding tools, planning, file access, approvals, memory, skills, shell commands, code execution, background agents, observability, governance, evaluations, and hosted deployment. ### Source excerpt I am building a complete C# agent live, from a single call around an IChatClient to a production-ready, observable, governed agent, using the Microsoft Agent Framework harness in a 4-part Microsoft Reactor series. The post Build Your Own AI Agent Harness in C#, the MafClaw Live Series appeared first on .NET Blog. ## Solana: Building, Proving and Earning Trust in Public DevFeed: [Solana: Building, Proving and Earning Trust in Public]() Original publisher: [Read original article]() Author: Jacob Creech Published: 2026-09-14T11:00:00Z Content type: article Language: en Sources: [Solana News Feed]() Topics: [Network](), [Critical Infrastructure](), [incident](), [networking](), [Transactions](), [Amazon Web Services]() Tags: [2026](), [aws](), [blockchain](), [blockchain-technology](), [building](), [critical-infrastructure](), [crypto](), [crypto-news](), [cryptocurrency](), [defi](), [ecosystem](), [incident](), [infrastructure](), [network](), [nfts](), [outages](), [podcasts](), [routing](), [solana](), [solana-ecosystem](), [technology](), [transactions](), [uptime](), [web3]() ### AI overview Solana describes how repeated public testing, transparent incident reporting, and corrective engineering have strengthened trust in the network. It highlights a 2026 routing failure that took nearly 29% of network stake offline while blocks and transactions continued, followed by recovery of the infrastructure provider in just over 30 minutes. The article also cites validator capacity improvements, stake-weighted quality of service, and a redesigned transaction scheduler as examples of resilience work. ### Source excerpt Solana has maintained 100% uptime since February 2024, including when a routing failure took nearly 29% of network stake offline. ## How to add WorkOS AuthKit to a Ruby on Rails app DevFeed: [How to add WorkOS AuthKit to a Ruby on Rails app]() Original publisher: [Read original article]() Author: WorkOS Published: 2026-09-14T00:00:00Z Content type: tutorial Language: en Sources: [WorkOS Blog]() Topics: [Rails](), [Authentication](), [Ruby](), [Command-line interface](), [Authorization](), [password reset]() Tags: [authentication](), [building](), [cli](), [how-to](), [password-reset](), [production](), [ruby](), [sign-in]() ### AI overview A tutorial on adding WorkOS AuthKit to a Ruby on Rails application. It explains how the CLI sets up the integration, how the sealed-cookie session layer is refreshed in a Rails before_action, and how Redirect URI, Initiate login URL, and Sign-out URI settings affect authentication flows and production logout. ### Source excerpt The CLI gets you signed in. This is the session layer underneath it: what the sealed cookie holds, how to refresh it inside a before_action, and the three dashboard settings that break logout in production. ## Primer on Jinja Templating DevFeed: [Primer on Jinja Templating]() Original publisher: [Read original article]() Author: Philipp Acsany Published: 2026-09-13T14:00:00Z Content type: tutorial Language: en Sources: [Real Python]() Topics: [Template](), [Python](), [web applications](), [Front end](), [Flask](), [modern web development](), [HTML](), [Django]() Tags: [building](), [code](), [content](), [django](), [features](), [framework](), [how-to](), [html](), [learn](), [learning](), [python](), [tutorial](), [web-applications]() ### AI overview A practical introduction to Jinja templating in Python. The tutorial covers installation, template creation and rendering, dynamic content, conditionals, loops, filters, macros, nesting, standalone text generation, and integration with Flask. ### Source excerpt With Jinja, you can build rich templates that power the front end of your web applications. But you can use Jinja without a web framework running in the background. Anytime you want to create text files with programmatic content, Jinja can help you out. ## The Grafana AI SDK for Go: a shared foundation for building AI applications DevFeed: [The Grafana AI SDK for Go: a shared foundation for building AI applications]() Original publisher: [Read original article]() Author: Luccas Quadros Published: 2026-09-12T11:22:06.456390Z Content type: article Language: en Sources: [Grafana Labs blog on Grafana Labs]() Topics: [vercel ai sdk](), [SDKs](), [Go Language](), [AI Development](), [Large Language Model](), [agent observability](), [Model Context Protocol](), [React]() Tags: [agent-observability](), [ai](), [analytics](), [backend](), [building](), [go](), [grafana](), [logs](), [metrics](), [monitoring](), [observability](), [sdk](), [streaming](), [tools](), [traces]() ### AI overview Grafana Labs introduces the Grafana AI SDK for Go, an open-source shared foundation for building AI applications. The SDK standardizes model calls, streaming, tool execution, structured output, multi-step agents, workflow controls, and operational features such as retries, logging, metrics, and Agent Observability. It also supports streaming Go backends to Vercel AI SDK frontend hooks. ### Source excerpt Starting an experiment with an LLM has never been easier. Keeping a growing collection of those experiments consistent is another matter. Earlier this year, as more teams began exploring AI features here at Grafana Labs, we repeatedly encountered the same pattern: a new experiment would start, move quickly, and build its own client for whichever model provider it needed. The next experiment would do the same, with a slightly different abstraction for streaming, tools, errors, or provider configuration. This was understandable, given the circumstances. Model providers were changing quickly, our teams were learning quickly, and coding agents made it possible to turn an idea into a working integration faster than ever. But that speed also made it easier for every integration to develop its own architecture. Eventually, we were maintaining a collection of solutions to what was essentially the same problem. And since most of our backend is written in Go, we built the Grafana AI SDK for Go to give our teams a shared foundation to work from. It provides common interfaces for calling models, streaming responses, executing tools, producing structured output, and running multi-step agents. It also speaks the protocol used by Vercel AI SDK frontend hooks, so a Go backend can stream directly to useChat, useCompletion, and useObject. We built it because we needed it inside Grafana Labs, but we open sourced it last month (alongside a broader collection of tools we released for building, operating, and understanding AI systems during our first Grafana Labs AI Week) because we think other teams building AI applications in Go are likely to encounter many of the same problems. We would like to build the next part together, so in this blog I'll tell you a bit more about the project, including how you can put it to use today, as well as how you can help us improve it. What teams can build with it today The SDK supports both simple model calls and larger application workflows: Generate ## Announcing ADK for Kotlin 1.0: Building Production-Ready AI Agents in Kotlin, Android, and Beyond DevFeed: [Announcing ADK for Kotlin 1.0: Building Production-Ready AI Agents in Kotlin, Android, and Beyond]() Original publisher: [Read original article]() Author: Guillaume Laforge Published: 2026-09-12T11:04:33.891311Z Content type: release Language: en Sources: [Google Developers Blog]() Topics: [Artificial Intelligence](), [Kotlin](), [AI Development](), [Android](), [Kotlin Multiplatform](), [multiplatform](), [Orchestration](), [Google](), [Persistence](), [Agent Skill](), [LiteRT](), [Cloud]() Tags: [agent-skill](), [agents](), [ai](), [ai-agent](), [ai-agents](), [android](), [building](), [database](), [development-kit](), [firebase](), [incident](), [kotlin](), [multiplatform](), [orchestration](), [persistence](), [production]() ### AI overview Google announces the 1.0 general availability release of the Agent Development Kit (ADK) for Kotlin, a production-ready toolkit for building multi-agent applications with Kotlin, Java, and Android. Built on Kotlin Multiplatform, it provides feature parity with the ADK 1.0 Core and adds Android-first extensions for on-device agents with LiteRT-LM and ML Kit, hybrid cloud workflows through Firebase AI Logic, and state persistence with Room and AppSearch. The release also includes type-safe, compile-time function calling through KSP and declarative agent skills. ### Source excerpt Google has officially released version 1.0 of the Agent Development Kit (ADK) for Kotlin, achieving full feature parity with the Python and Java ADK cores to enable idiomatic, multi-agent AI development. Built on Kotlin Multiplatform (KMP), the framework leverages Kotlin Symbol Processing (KSP) for zero-reflection, type-safe function calling, alongside advanced orchestration capabilities like human-in-the-loop workflows and context compaction. Additionally, the release introduces a robust suite of Android-first extensions, allowing mobile developers to integrate local models via LiteRT-LM, cloud reasoning through Firebase AI, session persistence using Room, and semantic memory powered by AppSearch. ## How to set up Postmark email templates for Webflow form submissions DevFeed: [How to set up Postmark email templates for Webflow form submissions]() Original publisher: [Read original article]() Author: Ismail Ajagbe Published: 2026-09-12T00:00:00Z Content type: tutorial Language: en Sources: [Webflow Blog]() Topics: [webflow](), [Forms](), [Cloud](), [Next.js](), [API](), [App](), [Server]() Tags: [api](), [app](), [building](), [cloud](), [developer](), [forms](), [guide](), [guides](), [how-to](), [learn](), [next-js](), [server](), [webflow]() ### AI overview A practical guide to moving email copy out of a Webflow Cloud app and into Postmark templates. It explains the prerequisites and focuses on keeping Webflow form field names aligned with Postmark template placeholders so the Route Handler sends data instead of hard-coded email text. ### Source excerpt Learn how to send Webflow form submissions through Postmark templates. ## The Reflexes Machine turns a reaction game into an interactive experience DevFeed: [The Reflexes Machine turns a reaction game into an interactive experience]() Original publisher: [Read original article]() Author: Arduino Team Published: 2026-09-09T12:37:27Z Content type: article Language: en Sources: [Arduino Blog]() Topics: [Arduino](), [UNO Q](), [Computer vision](), [webcam](), [real-time](), [Hardware]() Tags: [architecture](), [arduino](), [building](), [camera](), [computer-vision](), [hardware](), [i2c](), [led](), [modulino-nodes](), [project](), [reaction-game](), [real-time](), [reflex-game](), [reflexes-machine](), [sensors](), [uno-q]() ### AI overview An Arduino community member built Reflexes Machine, an arcade-style reaction game using an Arduino UNO Q board, Modulino nodes, a USB camera, illuminated buttons, LED Matrix displays, and sound effects. The camera detects a player's face and automatically starts the countdown. ### Source excerpt What happens when you combine a little imagination with a powerful dual-brain board and a handful of building-block sensors? In the case of Arduino community member LucaDilo, you get a reaction game that doesn't simply wait for someone to press a button... it actually notices when you walk up and invites you to play. Reflexes [...] The post The Reflexes Machine turns a reaction game into an interactive experience appeared first on Arduino Blog. ## Call for volunteers: Fundraising Working Group DevFeed: [Call for volunteers: Fundraising Working Group]() Original publisher: [Read original article]() Author: Priya Pahwa Published: 2026-09-08T19:27:14Z Content type: article Language: en Sources: [The Django weblog]() Topics: [Django]() Tags: [building](), [business](), [community](), [development](), [django](), [ecosystem](), [events](), [executive](), [framework](), [infrastructure](), [leadership](), [open-source](), [partnerships](), [python](), [sales](), [support]() ### AI overview The Django Software Foundation is recruiting volunteers for a Fundraising Working Group as it pursues a 2026 fundraising goal of $500,000 and prepares to hire its first Executive Director. The group will help develop sponsorships, partnerships, donor relationships, and new fundraising initiatives for the Django project. ### Source excerpt The Django Software Foundation is looking for people to join the Fundraising Working Group. This is a particularly interesting time to get involved. The DSF has raised its 2026 fundraising goal to $500,000. That funding is what allows us to continue supporting the Django Fellows, Django Girls, community events, Djangonaut Space, infrastructure, and the many other things that keep the Django ecosystem going. It also gives the DSF the room to do something new: hire its first Executive Director. You can read more about the DSF's fundraising goals for 2026 in this post. Getting there will take more than asking people to donate. We need to think about how we build relationships with companies that depend on Django, how we make sponsorships meaningful, how we find new ways for organisations to support the project, and how we communicate the value of investing in Django. That is where the Fundraising Working Group comes in. The DSF is hiring an Executive Director who will bring dedicated, day-to-day leadership to the Foundation, including sponsorship development and partner relationships. The Fundraising Working Group will have an opportunity to work closely with the person in this role as we build out our fundraising efforts. Who are we looking for? We'd love to have people who have done this before. If you have experience with fundraising, sponsorships, partnerships, business development, sales, donor relationships, or building relationships with companies, there is plenty of scope to put that experience to work. We need people who can help identify opportunities, open doors, develop ideas, and turn them into actual fundraising initiatives. But you don't need to be a fundraising expert to join. Maybe you've never worked on fundraising before, but you know how companies make decisions about supporting open source. Maybe you have ideas for how Django could engage organisations that rely on it. Maybe you are good at building relationships, telling a compelling story, organi ## Building a Risk-Based Secure Network Analytics Detection with Splunk Detection Editor (Alpha) DevFeed: [Building a Risk-Based Secure Network Analytics Detection with Splunk Detection Editor (Alpha)]() Original publisher: [Read original article]() Author: Aditya Sankar Published: 2026-09-07T15:00:32Z Content type: article Language: en Sources: [Security @ Cisco Blogs]() Topics: [Network](), [incident]() Tags: [black-hat](), [building](), [cybersecurity](), [data](), [dns](), [documentation](), [firewall](), [network-operations-center](), [noc](), [security](), [security-operations-center](), [soc](), [splunk-cloud](), [splunk-enterprise-security]() ### AI overview This article explains how to use Splunk Detection Editor (Alpha) to develop a Cisco Secure Network Analytics detection and add its alarms as risk events in Splunk Enterprise Security. It covers SPL development and testing, sample data, risk scoring, CIM fields, and investigation drilldowns, with risk-based alerting used to correlate behavior over time. ### Source excerpt At Black Hat USA, we used Splunk Detection Editor Alpha to turn Cisco SNA alarms into risk events with context, drilldowns & analyst-ready investigation paths. ## For the builders: canvas, CMS, and quality-of-life improvements from Webflow Conf 2026 DevFeed: [For the builders: canvas, CMS, and quality-of-life improvements from Webflow Conf 2026]() Original publisher: [Read original article]() Author: Webflow Team Published: 2026-09-02T00:00:00Z Content type: article Language: en Sources: [Webflow Blog]() Topics: [Canvas](), [Content Management System](), [Artificial Intelligence]() Tags: [ai](), [building](), [code](), [design](), [dev](), [developers](), [inside-webflow](), [platform](), [post](), [web](), [webflow](), [workflow](), [zoom]() ### AI overview Webflow's 2026 Builder Keynote introduces Source by Webflow and highlights workflow improvements for designers and developers, including CMS components, breakpoint canvas updates, and visual editing for AI code components. ### Source excerpt A roundup of what's new for designers and developers building in Webflow, including components in the CMS, breakpoint canvas, and visual editing for AI code components. ## Building patterns unlocked by scale to zero DevFeed: [Building patterns unlocked by scale to zero]() Original publisher: [Read original article]() Author: Carlota Soto Published: 2026-09-01T12:00:00Z Content type: article Language: en Sources: [Blog -- Neon Docs]() Topics: [Databases](), [autoscaling](), [ci]() Tags: [autoscaling](), [building](), [ci](), [compute](), [database](), [postgres](), [product](), [scale]() ### AI overview The article explains how autoscaling and scale to zero reduce idle Postgres compute costs. It presents ephemeral database branches for previews, tests, and individual development work as patterns enabled by suspending inactive compute. ### Source excerpt Most hosted Postgres pricing works like this: you pick an instance size, the vendor assumes the instance will run for about 730 hours a month, and you pay for those hours. Lakebase Postgres addresses that waste with autoscaling and scale to zero. ## The good ol' days of building Java DevFeed: [The good ol' days of building Java]() Original publisher: [Read original article]() Published: 2026-09-01T07:40:00Z Content type: article Language: en Sources: [Stack Overflow Blog]() Topics: [Programming](), [cross-platform]() Tags: [building](), [cross-platform](), [history](), [java](), [podcast](), [se-stackoverflow](), [se-tech](), [windows](), [youtube]() ### AI overview An interview about the early development of Java, including its cross-platform ABI, competition with Windows NT, and the initial role of applets. ### Source excerpt Ryan sits down with Tim Lindholm, an early contributor to the Java language at Sun Microsystems, to chat about what it was like building one of the most popular programming languages ever at its inception, why it was strategically important for the Java team to create a cross-platform ABI to compete with Windows NT, and how applets were initially just an interesting demo. ## fx is now available in the AI SDK harness layer DevFeed: [fx is now available in the AI SDK harness layer]() Original publisher: [Read original article]() Author: Felix Arntz Published: 2026-08-31T06:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [vercel ai sdk](), [SDKs](), [Vercel](), [AI-assisted coding](), [API](), [Protocol (disambiguation)]() Tags: [agent](), [agents](), [ai](), [api](), [building](), [claude](), [claude-code](), [codex](), [coding-agents](), [cursor](), [integration](), [open-source](), [opencode](), [sdk](), [vercel]() ### AI overview Vercel's AI SDK harness layer now supports fx, a lightweight open-source coding agent. Developers can run fx in their applications through the HarnessAgent interface using the official @ai-sdk/harness-fx adapter, which connects through the Agent Client Protocol via @ai-sdk/harness-acp. ### Source excerpt The AI SDK harness layer now supports fx, Vercel's lightweight, open-source coding agent. The harness layer provides one API for running coding agents in your application, so you can add fx without building a separate integration. Configure HarnessAgent with the official @ai-sdk/harness-fx adapter: The @ai-sdk/harness-fx adapter connects to fx over the Agent Client Protocol (ACP) using @ai-sdk/harness-acp. fx joins Claude Code, Cline, Codex, Cursor, Deep Agents, Grok Build, OpenCode, and Pi in the list of supported harnesses. Read the fx harness documentation to get started. Read more ## From Project Description to Funding Opportunity DevFeed: [From Project Description to Funding Opportunity]() Original publisher: [Read original article]() Author: Gabriel Preda Published: 2026-08-31T05:03:07Z Content type: tutorial Language: en Sources: [Google Developer Experts - Medium]() Topics: [Artificial Intelligence](), [Google AI](), [Streamlit](), [Cloud](), [PostgreSQL](), [postgresql clusters]() Tags: [adk](), [ai](), [building](), [cloud](), [developer](), [gemini](), [google](), [google-adk](), [google-cloud-sql](), [pgvector](), [postgresql](), [search](), [streamlit]() ### AI overview This article describes GrantMatch AI, a Streamlit application that matches project descriptions with potentially relevant grant and funding opportunities. It explains how hybrid keyword and embedding search, Gemini, ADK, Cloud SQL, PostgreSQL, pgvector, and Streamlit are used to connect related concepts despite different wording. ### Source excerpt Building GrantMatch AI with hybrid keyword and embedding search using Gemini, ADK, Cloud SQL, PostgreSQL, pgvector, and Streamlit Continue reading on Google Developer Experts " ## Building a mini Homelab that fits in my carry-on DevFeed: [Building a mini Homelab that fits in my carry-on]() Original publisher: [Read original article]() Author: jeff@jeffgeerling.com (Jeff Geerling) Published: 2026-08-28T15:00:00Z Content type: opinion Language: en Sources: [Jeff Geerling]() Topics: [Homelab](), [networking](), [Ubiquiti](), [Local-First](), [Hardware](), [SOC]() Tags: [5g](), [arm](), [battery](), [building](), [cloud](), [ethernet](), [fees](), [hardware](), [homelab](), [linux](), [local-first](), [networking](), [opnsense](), [portable](), [ubiquiti](), [unifi](), [video](), [vpn](), [youtube]() ### AI overview The author describes building a portable homelab that fits in carry-on luggage for a trip to Chicago. It supports 1-10 Gbps networking, battery operation, multiple WAN connections, and 12 wired Ethernet connections. The article also shares first impressions of Ubiquiti UniFi, highlighting its local-first operation, optional cloud integration, lack of core licensing fees, and easy web-based management, while criticizing its proprietary ecosystem and limited hardware control. ### Source excerpt I'm traveling to Chicago for VCF Midwest next month. I'll be demoing NTP time history on vintage Macs, with my own GPS-derived NTP service hosted on an Xserve G5, synced via NTP or a strange AppleTalk timing extension from the 1990s. So I built a little 'portable homelab' (pictured above) that supports 1-10 Gbps networking, can run off a small battery for at least an hour, switches between multiple WANs (so I can get my own 5G Internet connection, in case I need it), and gives me 12 wired Ethernet connections. ## Supporting Thailand's next generation of AI startups DevFeed: [Supporting Thailand's next generation of AI startups]() Original publisher: [Read original article]() Published: 2026-08-28T02:00:00Z Content type: news Language: en Sources: [OpenAI News]() Topics: [Artificial Intelligence](), [OpenAI](), [Deployment](), [ChatGPT](), [codex]() Tags: [ai](), [building](), [business](), [company](), [deployment](), [launch](), [prototypes](), [startups]() ### AI overview OpenAI and Thailand's Ministry of Higher Education, Science, Research and Innovation are launching an eight-week accelerator for ten AI startups in health, wellness, and education. The program aims to help founders turn promising prototypes into reliable products ready for real-world use and growth through mentoring, testing, user feedback, safeguards, and business-model development. ### Source excerpt OpenAI and Thailand's MHESI launch an eight-week accelerator helping 10 health, wellness, and education startups turn AI prototypes into trusted products. ## How loveholidays is making everyone a builder with Codex DevFeed: [How loveholidays is making everyone a builder with Codex]() Original publisher: [Read original article]() Published: 2026-08-26T00:00:00Z Content type: article Language: en Sources: [OpenAI News]() Topics: [codex](), [OpenAI](), [AI Development](), [Code](), [Software Engineering](), [Deployment](), [Front end]() Tags: [ai](), [building](), [code](), [codex](), [deployment](), [frontend](), [openai](), [software-development]() ### AI overview loveholidays uses OpenAI Codex to broaden software development beyond engineering, enabling product, design, and commercial teams to contribute code, infrastructure changes, experiments, and deployments. The article highlights growth in AI-assisted code changes and deployment frequency, alongside improvements to its Data Platform and the creation of Search Playground. ### Source excerpt Discover how loveholidays uses OpenAI Codex to make software development accessible across the business, helping teams turn ideas into products faster. ## Build a Multi-Agent GTM Intelligence System DevFeed: [Build a Multi-Agent GTM Intelligence System]() Original publisher: [Read original article]() Author: Avi Chawla Published: 2026-08-25T20:26:56Z Content type: tutorial Language: en Sources: [Daily Dose of Data Science]() Topics: [Code](), [API]() Tags: [agent](), [api](), [building](), [code](), [multi-agent](), [pipelines](), [research]() ### AI overview A hands-on tutorial for building a multi-agent go-to-market intelligence pipeline with Seltz. It explains how combining structured people and company-news records can help identify timely re-engagement opportunities. ### Source excerpt ...explained with code. ## I spent $20,000 on Devin in a month. Here's what I learned | Ryan Carson (solo founder) DevFeed: [I spent $20,000 on Devin in a month. Here's what I learned | Ryan Carson (solo founder)]() Original publisher: [Read original article]() Author: Claire Vo Published: 2026-08-24T12:04:02Z Content type: opinion Language: en Sources: [Lenny's Newsletter]() Topics: [coding](), [Claude Code](), [codex](), [Claude](), [Monitoring](), [OpenClaw](), [OpenAI]() Tags: [agents](), [building](), [claude](), [claude-code](), [codex](), [cursor](), [monitoring](), [openclaw]() ### AI overview A podcast episode featuring solo founder Ryan Carson discusses how he uses concurrent Devin agents and other AI tools for engineering, customer success, operations, and product work. The episode also covers monitoring accounts, managing pull-request workflows, choosing between Codex, Devin, and Claude Code, and using Claude Design with Codex. ### Source excerpt Watch now | 🎙 Solo founder Ryan Carson runs 15 concurrent Devin agents to handle engineering, customer success, and investor updates, and he uses a handwritten list to keep it all straight ## Advancing price-performance for developers with GPT-5.6 in Kiro DevFeed: [Advancing price-performance for developers with GPT-5.6 in Kiro]() Original publisher: [Read original article]() Published: 2026-08-24T12:00:00Z Content type: news Language: en Sources: [OpenAI News]() Topics: [Kiro](), [AI Development](), [Artificial Intelligence](), [OpenAI](), [Amazon Web Services](), [coding](), [Software Engineering]() Tags: [ai](), [ai-coding](), [aws](), [building](), [code](), [coding](), [developers](), [development](), [engineering](), [gpt](), [kiro](), [openai](), [product](), [software-development](), [spec-driven-development](), [testing]() ### AI overview GPT-5.6 is now available in Kiro, bringing OpenAI's latest flagship model series to development workflows for planning, coding, review, and testing. The article highlights structured, spec-driven development, complex multi-step coding, property-based testing, and reported cost reductions on Terminal-Bench 2.1. ### Source excerpt GPT-5.6 is now available in Kiro, helping developers plan, build, review, and test software with better price-performance. ## From signals to systemic risk: Building Risk AI DevFeed: [From signals to systemic risk: Building Risk AI]() Original publisher: [Read original article]() Author: Jaclyn Verga Published: 2026-08-20T00:00:00Z Content type: article Language: en Sources: [Datadog | The Monitor blog]() Topics: [AI Bots]() Tags: [agentic](), [agents](), [ai](), [ai-agents](), [ai-security](), [building](), [devsecops](), [engineering](), [reasoning](), [security](), [vulnerabilities]() ### AI overview Datadog describes a risk-detection pipeline and AI agents that correlate security signals to identify and prioritize systemic risk. Deterministic detection is combined with AI-assisted investigation, with security practitioners validating findings and retaining ownership of next steps. ### Source excerpt Datadog's Risk Engineering team built a Systemic Risk Detection Pipeline and Risk AI Agents to identify, contextualize, and prioritize systemic risks. ## Replit expands access to software creation with GPT-5.6 Luna DevFeed: [Replit expands access to software creation with GPT-5.6 Luna]() Original publisher: [Read original article]() Published: 2026-08-19T07:00:00Z Content type: article Language: en Sources: [OpenAI News]() Topics: [Repl.it](), [OpenAI](), [AI Development](), [coding](), [software-development]() Tags: [agent](), [applications](), [building](), [cost](), [development](), [gpt](), [inference](), [model](), [models](), [openai](), [performance](), [products](), [scale](), [software](), [software-development](), [startup](), [workflows]() ### AI overview Replit is introducing Free Mode, powered by GPT-5.6 Luna, to let users explore ideas and create working software without token costs. The article explains how improved model price performance and OpenAI price cuts support access at scale, while Replit Agent preserves project context and can route advanced tasks to GPT-5.6 Sol. ### Source excerpt Replit introduces Free Mode, powered by GPT-5.6 Luna, so anyone can turn ideas into working software without worrying about token costs. [Next page]()