# developer tooling Published articles for developer tooling. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## What Managed Postgres Services Handle for Teams DevFeed: [What Managed Postgres Services Handle for Teams]() Original publisher: [Read original article]() Author: Databricks Staff Published: 2026-09-14T23:36:59Z Content type: article Language: en Sources: [Databricks]() Topics: [PostgreSQL](), [Database](), [Serverless](), [databricks](), [AI Development]() Tags: [data-plus-ai-foundations](), [database](), [databricks](), [developer-tooling](), [migration](), [postgres](), [postgresql](), [recovery](), [security](), [serverless]() ### AI overview The article defines managed Postgres by the operational responsibilities a provider assumes, including patching, scaling, failover, and backups. It discusses how these responsibilities can vary between providers and describes Lakebase Postgres as a serverless offering with automatic scaling, PostgreSQL compatibility, recovery, and Databricks integrations. ### Source excerpt Every Postgres vendor calls itself "managed." Few of them agree on what that word... ## What to expect at the Zephyr Project Meetup (September 15, 2026) - Amsterdam, Netherlands DevFeed: [What to expect at the Zephyr Project Meetup (September 15, 2026) - Amsterdam, Netherlands]() Original publisher: [Read original article]() Author: Susan Remmert Published: 2026-09-09T05:00:04Z Content type: news Language: en Sources: [Zephyr Project]() Topics: [Zephyr RTOS](), [Embedded Systems](), [Fuzzing/Fuzz testing](), [Open Source]() Tags: [2026](), [blog](), [c](), [c-plus-plus](), [crashes](), [developer-tooling](), [embedded](), [embedded-systems](), [event](), [events](), [firmware](), [fuzzing](), [harness](), [jetbrains](), [meetup](), [memory-corruption](), [open-source](), [simulator](), [zephyr]() ### AI overview The Zephyr Project Meetup in Amsterdam on September 15, 2026, will bring together embedded developers, contributors, students, and engineers to share practical knowledge about Zephyr RTOS. The agenda includes talks on JetBrains' work with Zephyr, fuzzing Zephyr with AFL and Renode, and making hardware development easier with Schematik. ### Source excerpt What are developers in the Netherlands building with Zephyr? On September 15, the embedded community will meet in Amsterdam to exchange practical knowledge, discuss current work, and learn more about the Zephyr RTOS. The event is open to experienced contributors, first-time users, students, engineers, and anyone curious about open source embedded development. ## Client-Side SDK Generation with VMware Cloud Foundation OpenAPI Specs DevFeed: [Client-Side SDK Generation with VMware Cloud Foundation OpenAPI Specs]() Original publisher: [Read original article]() Author: vmwareblogs Published: 2026-09-07T09:38:44Z Content type: tutorial Language: en Sources: [VMware Blogs]() Topics: [OpenAPI Specification](), [SDKs](), [.NET](), [C#](), [developer tooling](), [Java](), [Python](), [PowerShell]() Tags: [apis](), [cli](), [cloud](), [cloud-infrastructure](), [csharp](), [developer](), [developer-tooling](), [docker](), [home-page](), [java](), [net](), [openapi](), [powershell](), [programming](), [programming-language](), [python](), [rest](), [rest-api](), [sdk](), [specifications](), [vcf-9-0](), [vcf-9-1](), [vcf-sdk]() ### AI overview This guide explains how to generate a strongly typed .NET C# client SDK from VMware Cloud Foundation and vSphere OpenAPI specifications. It covers OpenAPI Generator, installation options, large specification handling, API-surface scoping, and the REST and JSON-RPC interfaces targeted by the example. ### Source excerpt Starting with VMware Cloud Foundation (VCF) 9.0, VMware officially publishes OpenAPI specifications for VCF APIs. This is a major milestone for developers, enabling you to consume VCF APIs using your programming language of choice. VMware provides first-class developer tooling such as VCF PowerCLI for PowerShell users and the VCF SDK offering Java and Python bindings. ... Continued The post Client-Side SDK Generation with VMware Cloud Foundation OpenAPI Specs appeared first on VMware Blogs. ## Solana Changelog: August 20, 2026 DevFeed: [Solana Changelog: August 20, 2026]() Original publisher: [Read original article]() Author: Solana Foundation Published: 2026-08-24T14:19:00Z Content type: release Language: en Sources: [Solana News Feed]() Topics: [Solana](), [changelog](), [releases](), [developer tooling](), [SDK](), [Caching]() Tags: [2026](), [blockchain](), [blockchain-technology](), [cache](), [changelog](), [crypto-news](), [cryptocurrency](), [defi](), [developer-tooling](), [developers](), [network](), [newsletter](), [nfts](), [performance](), [podcasts](), [releases](), [sdk](), [solana](), [solana-ecosystem](), [technology](), [updates](), [web3]() ### AI overview The August 20, 2026 Solana changelog reports reduced slot times on mainnet and Testnet, updates to validator clients and developer SDKs, and ongoing work on transaction processing, program caching, and validator repair. ### Source excerpt Feature gates reduced mainnet slot times from 400ms to 350ms, while Agave, Firedancer, and Solana Kit shipped updates. ## ChainDrop: Inside a Self-Propagating npm Worm DevFeed: [ChainDrop: Inside a Self-Propagating npm Worm]() Original publisher: [Read original article]() Author: Unit 42 Published: 2026-08-06T22:26:39Z Content type: article Language: en Sources: [Unit 42]() Topics: [ChainDrop](), [npm](), [Malware](), [C2](), [Ethereum](), [GitHub Actions](), [GitHub](), [CI/CD](), [Security]() Tags: [blockchain](), [c2](), [chaindrop](), [ci](), [claude-code](), [developer-tooling](), [ethereum](), [github](), [github-actions](), [high-profile-threats](), [infrastructure](), [malware](), [security](), [ssh](), [supply-chain](), [tokens]() ### AI overview This article analyzes ChainDrop, a self-propagating npm worm that infected more than 400 packages and threatened developer workstations, CI pipelines, cloud environments and downstream users. It describes credential and token theft, GitHub Actions runner memory extraction, package republishing, persistence through developer and AI coding tools, blockchain-based C2 resolution, and C2 reconfiguration through an Ethereum transaction. ### Source excerpt Analysis of ChainDrop, an npm supply chain worm extracting GitHub Actions runner secrets and using Ethereum smart contracts for C2 routing. The post ChainDrop: Inside a Self-Propagating npm Worm appeared first on Unit 42. ## Developers are attached to tools because tools encode trust DevFeed: [Developers are attached to tools because tools encode trust]() Original publisher: [Read original article]() Author: Ryan Donovan Published: 2026-07-29T14:06:38Z Content type: opinion Language: en Sources: [Stack Overflow Blog]() Topics: [Developer Tools](), [AI-assisted coding]() Tags: [agentic](), [buiilding-software](), [dev-tools](), [developer-tooling](), [developers](), [ide](), [se-stackoverflow](), [se-tech](), [tools]() ### AI overview An opinion piece on how developers build trust in customizable tools and workflows, contrasting established tools such as Vim and Emacs with rapidly changing coding agents. ### Source excerpt The tools themselves are new and their capabilities are in constant flux. If your kitchen knife kept changing shape, weight, and edge, you'd have to relearn it every time; that's a hard tool to build trust in. But it also points to a flaw in how you use that tool, the process around it, and the way the tool reinforces the process. ## Model Context Protocol (MCP) vs. Agent2Agent (A2A): which protocol do you need? DevFeed: [Model Context Protocol (MCP) vs. Agent2Agent (A2A): which protocol do you need?]() Original publisher: [Read original article]() Author: Jeff Mills Published: 2026-07-22T00:00:00Z Content type: comparison Language: en Sources: [Redis Blog]() Topics: [Model Context Protocol](), [Remote Procedure Call (RPC)](), [Artificial Intelligence](), [JSON](), [Large Language Model](), [Orchestration](), [observability](), [servers](), [Grafana]() Tags: [agent](), [api](), [architecture](), [developer](), [developer-tooling](), [grafana](), [guide](), [json](), [mcp](), [model-context-protocol](), [observability](), [rpc](), [tech-de]() ### AI overview This guide compares the Model Context Protocol (MCP) with Agent2Agent (A2A), explaining that MCP connects an LLM application to tools and data while A2A connects independent agents. It describes MCP's hosts, clients, servers, tools, resources, prompts, JSON-RPC transport, streaming, production use cases, and governance limitations. ### Source excerpt Somewhere around your third agent, someone in a design review asks, "Shouldn't we be using A2A for this?" It's a fair question that most teams can't answer well, because the two big agent protocols keep getting lumped together when they solve differen... ## How to migrate feature flags without breaking production DevFeed: [How to migrate feature flags without breaking production]() Original publisher: [Read original article]() Author: Anthony Rindone; Ryan Lucht; Natasha Silva Published: 2026-06-23T00:00:00Z Content type: tutorial Language: en Sources: [Datadog | The Monitor blog]() Topics: [migration](), [SDKs]() Tags: [developer-tooling](), [devops](), [feature-flags](), [how-to](), [migration](), [production](), [safety](), [software-delivery](), [sync](), [validation]() ### AI overview A guide to safely migrating feature flags by auditing legacy flags, checking evaluation parity, synchronizing configuration, and validating cutover safety. ### Source excerpt Feature flag migrations have a reputation for stalling. Learn how to structure the process in a few steps: audit legacy flags, validate evaluation parity with shadow mode, and cut over with confidence. ## Open House 2026 Day 1: Real-time data without lock-in and what teams can build next DevFeed: [Open House 2026 Day 1: Real-time data without lock-in and what teams can build next]() Original publisher: [Read original article]() Author: ClickHouse Published: 2026-05-27T00:00:00Z Content type: news Language: en Sources: [ClickHouse Blog]() Topics: [AI, ML & Data Engineering](), [AI Bots](), [developer tooling]() Tags: [agents](), [ai](), [ai-agents](), [announcement](), [clickhouse](), [cloud](), [developer-tooling](), [monitoring](), [observability](), [postgres](), [replication](), [resilience](), [workflows]() ### AI overview A Day 1 recap of ClickHouse Open House 2026 announces ClickHouse Cloud updates, ClickHouse Postgres public beta, faster distributed queries, Langfuse V4 performance work, ClickHouse Agents, observability improvements, and lakehouse interoperability. ### Source excerpt A full recap of Day 1 at Open House 2026, covering every major announcement across ClickHouse Cloud, Postgres, distributed queries, ClickPipes, ClickHouse Agents, Langfuse V4, ClickStack, and the House Mates partner program. ## MCP Server Pricing Models: How to Charge for Model Context Protocol DevFeed: [MCP Server Pricing Models: How to Charge for Model Context Protocol]() Original publisher: [Read original article]() Author: Ayush Agarwal Published: 2026-05-20T00:00:00Z Content type: article Language: en Sources: [Dodo Payments Blog]() Topics: [MCP Server](), [Model Context Protocol](), [AI Infrastructure](), [Software as a service]() Tags: [ai](), [ai-infrastructure](), [api](), [developer-tooling](), [mcp](), [mcp-server](), [model-context-protocol](), [pricing](), [saas](), [tool]() ### AI overview This article examines pricing models for MCP servers, including subscription plans with quotas, per-call usage pricing, per-session pricing, and hybrid approaches. It explains how operators can meter tool invocations, resource reads, prompt templates, and server connections, with the pricing model aligned to customer consumption and delivery costs. ### Source excerpt Pricing patterns for MCP servers. Subscription, per call, per session, hybrid. What works for tool servers, data connectors, and AI infrastructure. ## Claude Code and Margin Pass Through: Pricing Lessons for AI Products DevFeed: [Claude Code and Margin Pass Through: Pricing Lessons for AI Products]() Original publisher: [Read original article]() Author: Ayush Agarwal Published: 2026-05-19T00:00:00Z Content type: opinion Language: en Sources: [Dodo Payments Blog]() Topics: [Claude Code](), [Artificial Intelligence](), [Frontier Model](), [Software as a service](), [developer tooling]() Tags: [agent](), [ai](), [business](), [claude](), [claude-code](), [cost](), [developer-tooling](), [economics](), [margin](), [pricing](), [saas]() ### AI overview The article examines pass-through pricing for AI products, using Claude Code as an example. It explains how charging customers at or near underlying model costs differs from applying a larger markup, and discusses when each approach may fit products with different levels of added value. ### Source excerpt How Claude Code and similar AI products handle pass through pricing of model costs. When pass through works, when it doesn't, and what to charge instead. ## What's Easy Now? What's Hard Now? DevFeed: [What's Easy Now? What's Hard Now?]() Original publisher: [Read original article]() Author: Marc Brooker Published: 2026-05-18T00:00:00Z Content type: opinion Language: en Sources: [Marc Brooker's Blog](), [Marc Brooker's Blog]() Topics: [AI-assisted coding](), [Artificial Intelligence](), [AI Development](), [Large Language Model](), [developer tooling](), [Software Engineering]() Tags: [ai](), [coding-agents](), [developer-tooling](), [llm](), [software-development](), [software-engineering]() ### AI overview The article examines what coding agents are good and bad at as AI changes software development. It argues that coding agents can rapidly build meaningful, correct software at very low cost and can outperform humans on some tasks, while remaining less capable in others. It explains this behavior through feedback loops: agents combine an LLM's useful but flawed standalone behavior with iterative feedback, enabling capabilities beyond the LLM alone. ### Source excerpt What's Easy Now? What's Hard Now? Take it easy. This is the fourth in a series about how AI is changing software development, after It's time to be right., What about juniors?, and My heuristics are wrong. What now?. It stands alone, but if you found this interesting you may also find those interesting. I've been spending a lot of time thinking about the shape of the capabilities of coding agents. What they're good at now, what they're going to be good at. What they're bad at now, how much of that is inherent and how much is transient. This is worth thinking about, because it's the most important question shaping the future of software, and of software engineering. I don't pretend to have an answer, but am coming to a conclusion that may be deeply counter-intuitive. Coding agents are becoming very good indeed, and can build meaningful and correct software very quickly and at transformatively low cost. They have super-human abilities on some coding tasks. Of course, computer systems have had super human abilities for at least 85 years1. I think we're going to find, as we have over those nine decades, that this new technology we're building is vastly super-human in some areas2, and not nearly as capable as humans in others. Which raises the important question of how, and why. Feedback is powerful Early on in my EE education, one of my professors drew a simple circuit on the board that's been stuck in my mind ever since. It looked like this3: Apply a voltage on the left, and on the right you get the square root of that voltage4. The two components are an opamp and an analog multiplier IC (e.g. the deeply obsolete MC1495). This simple circuit encapsulates possibly the most important idea in electrical engineering: feedback is uniquely powerful. Maybe unreasonably powerful. It's the idea that makes nearly every electronic device work, it keeps planes in the sky, and stops your oven from burning your dinner. Components inside feedback loops can be made to behave significa ## Tinybird vs. ClickHouse®: What's the difference? DevFeed: [Tinybird vs. ClickHouse®: What's the difference?]() Original publisher: [Read original article]() Author: Gonzalo Gómez Published: 2026-04-17T00:00:00Z Content type: comparison Language: en Sources: [Tinybird]() Topics: [clickhouse](), [developer tooling](), [SDKs](), [real-time]() Tags: [analytics](), [clickhouse](), [developer](), [developer-tooling](), [open-source](), [real-time](), [sdks](), [the-data-base]() ### AI overview The article compares ClickHouse with Tinybird, describing ClickHouse as an open source columnar database and Tinybird as a data platform built on ClickHouse with developer tooling, SDKs, and infrastructure abstractions for building real-time analytics APIs. ### Source excerpt ClickHouse® is an open source columnar database. Tinybird is a data platform built on ClickHouse® with developer tooling, SDKs, and infrastructure abstractions for building real-time analytics APIs. ## Applications of AI at OpenAI DevFeed: [Applications of AI at OpenAI]() Original publisher: [Read original article]() Published: 2026-04-10T00:00:00Z Content type: article Language: en Sources: [OpenAI News]() Topics: [AI, ML & Data Engineering](), [Developer Tools](), [AI Chat](), [debugging]() Tags: [ai](), [apis](), [applications](), [automation](), [chatgpt](), [codex](), [debugging](), [developer-tooling](), [development](), [openai](), [openai-academy]() ### AI overview An overview of how OpenAI products and APIs support real-world AI use, including ChatGPT for general-purpose work and Codex for AI-assisted software development. ### Source excerpt Explore how OpenAI products like ChatGPT, Codex, and APIs bring AI into real-world use for work, development, and everyday tasks. ## The 5 Principles of Snyk's Developer Experience DevFeed: [The 5 Principles of Snyk's Developer Experience]() Original publisher: [Read original article]() Author: Mayank Khera; Brendan Hann Published: 2026-03-26T04:00:00Z Content type: article Language: en Sources: [Blog RSS Feed | Snyk]() Topics: [Developer experience](), [Security](), [developer tooling](), [Pull Request](), [Code review](), [Command-line interface](), [ide](), [CI/CD](), [Git](), [ai-coding](), [agent observability](), [internal developer portal]() Tags: [ai](), [ai-coding](), [americas](), [application-security](), [awareness](), [blog](), [ci-cd](), [cli](), [code-security](), [developer](), [developer-experience](), [developer-tooling](), [devops](), [devsecops](), [engineering](), [executive](), [git](), [ide](), [interest](), [pull-request](), [review](), [scm](), [security](), [snyk-code](), [snyk-platform](), [tech](), [vulnerability-insights]() ### AI overview Snyk presents five principles for developer experience, emphasizing seamless integration into existing workflows such as IDEs, terminals, Git, pull requests, AI coding assistants, and CI/CD. The article argues that surfacing security findings directly where developers work reduces context switching and helps teams ship secure code faster. ### Source excerpt Discover the 5 principles behind Snyk's developer experience. Learn how seamless workflows, actionable fixes, and AI-driven security help developers ship secure code faster without disrupting productivity. ## Cloud Coding Agents at HubSpot DevFeed: [Cloud Coding Agents at HubSpot]() Original publisher: [Read original article]() Author: Stephan Lensky Published: 2026-01-23T15:59:04Z Content type: article Language: en Sources: [HubSpot]() Topics: [hubspot](), [AI-assisted coding](), [Claude Code](), [Self-hosted](), [GitHub](), [pull-requests](), [developer tooling](), [Code review]() Tags: [ai](), [claude-code](), [code-review](), [coding-agents](), [developer-tooling](), [engineering](), [github](), [hubspot](), [self-hosting]() ### AI overview This article explains how HubSpot built and deployed a self-hosted platform for cloud coding agents, integrating them with internal developer tooling, infrastructure, and GitHub. It describes their use of autonomous agents for planning, implementation, and code review, including more than 7,000 merged AI-generated pull requests and over 50,000 human-authored pull requests reviewed by agents. ### Source excerpt This post is the second in a series about empowering product, UX, and engineering teams with AI, especially in the context of writing code. Read the first post about scaling AI adoption here! ## Run GitHub Actions Workflows Locally with Self-Hosted Runners DevFeed: [Run GitHub Actions Workflows Locally with Self-Hosted Runners]() Original publisher: [Read original article]() Author: Ivan Morgillo Published: 2025-08-26T13:34:43Z Content type: tutorial Language: en Sources: [Ivan Morgillo]() Topics: [GitHub Actions](), [Self-hosted](), [ci](), [Mobile](), [Android]() Tags: [android](), [ci](), [ci-cd](), [developer-tooling](), [github](), [github-actions](), [how-to](), [local-ci](), [mobile](), [self-hosted](), [self-hosted-runner](), [workflows]() ### AI overview A tutorial on running GitHub Actions workflows locally with self-hosted runners to reduce cloud queue wait times and CI costs for Android and mobile projects. ### Source excerpt How to run GitHub Actions workflows locally using self-hosted runners, cutting cloud queue wait times and CI costs for Android and mobile projects. ## Building Laravel's Future. The Artisan of the Day Is Tom Crary. DevFeed: [Building Laravel's Future. The Artisan of the Day Is Tom Crary.]() Original publisher: [Read original article]() Author: Ana Tavares Published: 2025-08-17T15:22:17Z Content type: article Language: en Sources: [Laravel Blog]() Topics: [Laravel](), [PHP](), [Deployment](), [developer tooling](), [Monitoring](), [Cloud](), [releases]() Tags: [business](), [cloud](), [community](), [deployment](), [developer](), [developer-tooling](), [global](), [laravel](), [monitoring](), [php](), [releases]() ### AI overview Laravel President and COO Tom Crary describes his transition from accounting and technology leadership to Laravel, including his experience scaling PHP-powered web properties and supporting developer communities. The article outlines Laravel's $57 million funding round and future plans for Laravel Cloud, a reimagined Forge, Laravel Nightwatch, and broader ecosystem growth. ### Source excerpt Laravel's President and COO shares his story on Laravel's funding, how to build a global team, and the company's future. ## Announcing the Trillion Dollar Security Initiative DevFeed: [Announcing the Trillion Dollar Security Initiative]() Original publisher: [Read original article]() Author: Ethereum Foundation Published: 2025-05-14T00:00:00Z Content type: release Language: en Sources: [Ethereum Foundation Blog]() Topics: [Ethereum](), [Blockchain](), [Security](), [developer tooling]() Tags: [attacks](), [blockchain](), [developer-tooling](), [ethereum](), [protocol](), [security]() ### AI overview The Ethereum Foundation announces the Trillion Dollar Security initiative, an ecosystem-wide effort to improve Ethereum's security across its technology stack. The initiative will map security strengths and attack vectors, implement improvements, and communicate security standards more effectively. ### Source excerpt Ethereum is the most secure blockchain ecosystem. This is the result of 10 years of progress and iteration across every level of Ethereum's technology stack, from wallet UX to developer tooling to consensus protocol security. But being the most secure platform in the crypto ecosystem isn't enough. Ethereum's ambition... ## Announcing Firebase Genkit 1.0 for Node.js DevFeed: [Announcing Firebase Genkit 1.0 for Node.js]() Original publisher: [Read original article]() Author: Chris Gill; Peter Friese Published: 2025-02-12T04:00:00Z Content type: release Language: en Sources: [Firebase Blog]() Topics: [Genkit](), [Artificial Intelligence](), [Node.js](), [Tooling](), [Open Source](), [Retrieval Augmented Generation (RAG)](), [JSON]() Tags: [ai](), [ai-development](), [deepseek](), [developer-tooling](), [firebase](), [gemini](), [gemma](), [genkit](), [json](), [launch](), [llama](), [node-js](), [ollama](), [rag]() ### AI overview Firebase announces Genkit 1.0 for Node.js as production-ready after its preview at Google I/O 2024. The open-source framework supports AI-powered features, agents, automations, model integrations, structured generation, function calling, vector search, and local developer tooling. ### Source excerpt Production-ready AI for your apps ## The Atlassian method: The power of developer joy DevFeed: [The Atlassian method: The power of developer joy]() Original publisher: [Read original article]() Author: Alia Fite Published: 2024-08-13T00:00:00Z Content type: article Language: en Sources: [Figma Blog]() Topics: [atlassian](), [Developer experience](), [developer tooling](), [DevOps]() Tags: [atlassian](), [cognitive-load](), [company](), [developer](), [developer-experience](), [developer-tooling](), [developers](), [development](), [devops](), [processes](), [productivity](), [systems](), [tooling](), [work](), [workflow]() ### AI overview Atlassian presents developer joy as a company-wide philosophy focused on reducing friction, improving tooling and systems, and helping developers spend more time on core development work. The article describes the productivity and satisfaction problems that motivated this approach, along with a cross-functional champions program to identify and address sources of frustration. ### Source excerpt Learn how Atlassian made cultivating "developer joy" their north star metric for success. ## First look at Declarative Gradle DevFeed: [First look at Declarative Gradle]() Original publisher: [Read original article]() Author: Sterling Greene Published: 2024-07-24T04:00:00Z Content type: article Language: en Sources: [The Gradle Blog]() Topics: [Gradle](), [configuration](), [developer tooling](), [Groovy](), [Kotlin]() Tags: [beginners](), [blog-post](), [community](), [configuration](), [developer-tooling](), [dsl](), [eap](), [experimental](), [gradle](), [groovy](), [improvements](), [kotlin](), [preview]() ### AI overview This article introduces the first early access preview of Declarative Gradle, an experimental project aimed at providing a clearer, developer-first declarative build language for Gradle. It describes the Declarative Configuration Language, its relationship to Kotlin syntax, the .gradle.dcl file format, and the restrictions that exclude imperative constructs such as loops, conditionals, and functions. The preview is intended for feedback and is not ready for production use. ### Source excerpt Introduction In our update in November 2023, we announced a new experimental project called Declarative Gradle. That post introduced our ideas for a developer-first software definition and how we planned to fulfill our vision for a declarative build language for Gradle. Since then, we've been working hard to create the first early access preview (EAP) of Declarative Gradle. This blog post provides an update on the project's progress and outlines how you can try it out, provide feedback, and influence our next steps. What is Declarative Gradle? Part of our vision for Gradle Build Tool is to deliver an elegant and extensible declarative build language that allows developers to describe any kind of software in a clear and understandable way. Gradle's build language is already extensible in the most fundamental ways, which results in a high degree of flexibility, but it's not always fully declarative, clear, and understandable. We believe that Declarative Gradle will offer a fundamental advancement in the Gradle user experience for software developers thanks to a developer-first software definition, a declarative DSL, and improvements in developer tooling made possible by these. Note that Declarative Gradle is still in an experimental stage and is not ready for production use. We are providing an early access preview to gather initial feedback from the community. Declarative Configuration Language Gradle's existing Kotlin and Groovy DSLs give users access to a full programming language and ecosystem. This makes build scripts very powerful, but it can also make it harder for beginners to understand them and for vendors to provide tooling on top of Gradle. With Declarative Gradle, we're introducing a new configuration language. In addition to .gradle and .gradle.kts build files, Gradle will also recognize .gradle.dcl, where DCL stands for "Declarative Configuration Language". This language falls into the family of declarative configuration languages, meaning it is non-pro ## Introducing Firebase Genkit DevFeed: [Introducing Firebase Genkit]() Original publisher: [Read original article]() Author: Chris Gill; Peter Friese Published: 2024-05-14T04:00:00Z Content type: release Language: en Sources: [Firebase Blog]() Topics: [Artificial Intelligence](), [Firebase](), [Framework](), [Node.js](), [JavaScript](), [Tooling](), [Cloud](), [Ollama](), [Firestore](), [PostgreSQL](), [Serverless]() Tags: [agents](), [ai](), [backend](), [build](), [cloud](), [developer-tooling](), [firebase](), [firestore](), [genkit](), [javascript](), [launch](), [node-js](), [ollama](), [postgresql](), [release](), [serverless](), [typescript]() ### AI overview Firebase introduces Genkit in beta, an open-source framework for JavaScript and TypeScript developers building Node.js backends with AI-powered features. It supports integrations with models, data sources, cloud services, and agents, with local tooling and deployment options for Firebase and Google Cloud. ### Source excerpt Build and deploy AI features with ease ## Everything you need to know about Dev Mode DevFeed: [Everything you need to know about Dev Mode]() Original publisher: [Read original article]() Author: Figma Published: 2024-01-31T00:00:00Z Content type: article Language: en Sources: [Figma Blog]() Topics: [Figma](), [developer tooling](), [Front end](), [React](), [Web]() Tags: [building](), [code](), [design](), [design-systems](), [dev](), [developer-tooling](), [developers](), [development](), [figma](), [product-development](), [ui](), [workflows]() ### AI overview Figma introduces Dev Mode as a dedicated space for developers, moving the feature out of beta. The article describes how Dev Mode supports product development from idea to code, improves collaboration between developers and designers, and addresses developer workflows, toolchains, design systems, components, content layouts, and asset export. ### Source excerpt We built Dev Mode to make product development more efficient, from idea to code. Today, Dev Mode moves out of beta. Learn more about our product philosophy, how we're improving the experience for developers and designers, and what's next. [Next page]()