# Boilerplate A boilerplate code is a piece of code that can be reused without significant changes. When using a verbose language, the developer must write a lot only to accomplish minor functionality. Such code is called boilerplate. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Introducing eve DevFeed: [Introducing eve]() Original publisher: [Read original article]() Author: Rui Conti Published: 2026-06-17T04:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [AI Bots](), [Boilerplate]() Tags: [agents](), [ai-gateway](), [framework](), [next-js](), [open-source](), [production](), [skills](), [tools](), [vercel]() ### AI overview Vercel introduces eve, an open-source framework for building and operating production agents. It organizes agents as directories and provides durable execution, sandboxed compute, human approvals, subagents, evaluations, model configuration, and tool and skill wiring. ### Source excerpt Today, we are proud to introduce eve, an open-source agent framework for building, running, and scaling agents. eve is designed around the idea that building an agent should mean defining what it does without assembling all of the pieces that it needs to run in production. Instead, eve comes with production already built in: Durable execution Sandboxed compute Human-in-the-loop approvals Subagents Evals And more eve is the framework that we build and run our own agents on. Agents today are where the web was before frameworks, with everyone hand-rolling the same plumbing and nothing carrying over to the next one. Next.js ended this for the web, and eve is doing the same for agents. An agent is a directory This is an eve agent. Each file describes one component of the agent, so at a glance, the tree tells you what an agent is, what it does, where it lives, and when it acts on its own. Create an eve agent in minutes Every agent starts with its definition. The agent.ts file is where you configure the agent itself. You can define the model with one line, with provider fallbacks supported through AI Gateway, and compaction, model options, and other optional fields are there when you need them. Giving your agent a job and personality is as simple as creating an instructions.md file, which serves as the system prompt that eve puts in front of every model call. You create files for what your agent does, like post_chart.ts and revenue-definitions.md for tools and skills, and eve wires them into a working agent without any boilerplate or plumbing to manage. You can just focus on what your agent does instead of how it does it. Why we built eve We had built agents for years at Vercel, v0 among them. But once coding agents made building one something anyone could do, everyone did. We shipped hundreds of agents and internal apps, and it looked like a productivity revolution. But underneath it, every team was building and rebuilding the same plumbing before their agent could do any ## Introducing eve, an open-source agent framework DevFeed: [Introducing eve, an open-source agent framework]() Original publisher: [Read original article]() Author: Timo Lins Published: 2026-06-17T00:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [AI Chat](), [MSP MCP](), [Boilerplate]() Tags: [agents](), [announcement](), [development](), [github](), [mcp](), [open-source]() ### AI overview Vercel announces eve, an open-source framework in public preview for building and running agents. It uses a file-based agent structure and includes durable execution, sandboxed compute, approvals, subagents, and evaluations. ### Source excerpt eve is now available in public preview. eve is an open-source framework for building, running, and scaling agents. An agent is just a directory of files, and production comes built in: Durable execution Sandboxed compute Human-in-the-loop approvals Subagents Evals The smallest agent that runs is just two files, a model and a set of instructions. Add a tool, skill, channel, or schedule by adding a file. eve picks them up at build time and wires them in for you, so there's no boilerplate to register them. You can scaffold and start a new agent with a single command. It installs the dependencies, scaffolds the project, and starts a dev server, so you have an agent running locally in under a minute. Or you can let your coding agent set it up for you. Give it this prompt: And because an eve agent is an ordinary Vercel project, vercel deploy ships it to production unchanged, exactly as it ran on your machine. eve is the framework that Vercel builds and runs its own agents on. For the full tour, read the announcement or the documentation, and you can follow development in the open over at github.com/vercel/eve. Read more ## Works on my machine: how we use AI to reproduce reported bugs DevFeed: [Works on my machine: how we use AI to reproduce reported bugs]() Original publisher: [Read original article]() Author: Neel Shah Published: 2026-06-08T09:00:00Z Content type: article Language: en Sources: [Sentry Blog]() Topics: [Claude](), [SDKs](), [bug](), [Artificial Intelligence](), [Development](), [GitHub](), [Open Source](), [Python](), [Django](), [Boilerplate](), [Concurrency](), [legacy]() Tags: [ai](), [bugs](), [claude](), [concurrency](), [django](), [frameworks](), [github](), [legacy](), [open-source](), [python](), [sdks]() ### AI overview Sentry's SDK teams use a Claude skill to automate parts of reproducing reported bugs, including setting up boilerplate environments and playgrounds with the required parameters. The approach is intended to reduce triage time across the team's large SDK ecosystem. ### Source excerpt How Sentry's SDK team built a Claude skill to auto-reproduce bug reports, reducing triage time across 159 packages. ## Kotlin 2.4 Brings Swift-Style Collection Syntax \[\] DevFeed: [Kotlin 2.4 Brings Swift-Style Collection Syntax \[\]]() Original publisher: [Read original article]() Author: Nav Singh Published: 2026-06-04T16:32:23Z Content type: article Language: en Sources: [Stories by Nav Singh 🇨🇦 on Medium]() Topics: [Kotlin](), [Boilerplate](), [Code](), [Compiler]() Tags: [build](), [collection](), [compiler](), [experimental](), [kotlin](), [kotlin-2](), [kotlin-standard-library](), [new-features](), [syntax]() ### AI overview This article explains Kotlin 2.4's experimental collection literals, which allow collections to be initialized with bracket syntax instead of functions such as listOf() or mutableListOf(). It also covers enabling the feature with the compiler option and discusses explicit declarations and type inference. ### Source excerpt Image generated using Perplexity In Kotlin 2.4, collection literals are introduced, making collection initialization more concise and readable. To define collections, we no longer need to use functions like listOf() or mutableListOf(). This reduces boilerplate and makes intent clearer at a glance, especially when working with simple, static data. It's currently an experimental feature. We need to opt in, and the syntax or behavior may evolve in future releases. Add the Xcollection-literals compiler option to the build file kotlin { jvmToolchain(21) compilerOptions { freeCompilerArgs.add("-Xcollection-literals") } }Code samples Bracket syntax [] + explicit declaration // Mutable list with explicit type declaration // val plFNames: MutableList = mutableListOf("Joe", "Alice") // Mutable list with brackets syntax val plFNames: MutableList = ["Joe", "Alice"] println(plFNames) // ["Joe", "Alice" ] Bracket syntax [] + type inference As per docs:Compiler defaults to List if it lacks sufficient information to infer the collection type.But it seems like Array as we can see in the screenshot 📸 👇 val plFNames = ["Joe", "Alice"] println(plFNames) // ["Joe", "Alice" ]Screenshot type inference -- typeReferences What's new in Kotlin 2.4.0 | Kotlin Kotlin 2.4 Brings Swift-Style Collection Syntax [] was originally published in ProAndroidDev on Medium, where people are continuing the conversation by highlighting and responding to this story. ## How AI-Assisted Development Uses Reviewed Design Documents and Extensive Testing DevFeed: [How AI-Assisted Development Uses Reviewed Design Documents and Extensive Testing]() Original publisher: [Read original article]() Author: Brian Jenney Published: 2026-05-30T17:42:50Z Content type: article Language: en Sources: [Brian Jenney]() Topics: [Artificial Intelligence](), [Code](), [Testing](), [Documentation](), [Kubernetes](), [Terraform](), [Mocking](), [Boilerplate](), [GitHub API](), [Figma]() Tags: [ai](), [api](), [boilerplate](), [code](), [documentation](), [figma](), [github](), [kubernetes](), [mocking](), [terraform](), [testing]() ### AI overview The author describes an AI-assisted development workflow in which reviewed, versioned design documents provide context for coding agents. Agents handle implementation and testing boilerplate, while developers decide expected behavior and test coverage. The author connects this process with frequent deployments and confidence in changes. ### Source excerpt AI writes basically all of my code now. ## Introducing @supabase/server DevFeed: [Introducing @supabase/server]() Original publisher: [Read original article]() Author: Tomás Pozo; Kalleby Santos; Katerina Skroumpelou; Matt Johnston Published: 2026-05-06T07:00:00Z Content type: article Language: en Sources: [Supabase Blog]() Topics: [Supabase](), [Authentication](), [JSON Web Tokens](), [Boilerplate](), [Workers](), [Bun](), [Hono]() Tags: [auth](), [authentication](), [cloudflare-workers](), [code](), [post](), [security](), [workers]() ### AI overview Supabase introduces @supabase/server in public beta, a package that provides authentication verification, Supabase client setup, request context, CORS handling, and common server-side helpers across Edge Functions, Vercel Functions, Cloudflare Workers, Hono, and Bun. It supplies user-scoped and admin clients, verified identity, and JWT claims while reducing repeated setup code. ### Source excerpt Stateless auth, RLS-scoped clients, and CORS on the server, without the boilerplate. ## Kubernetes v1.36: Declarative Validation Graduates to GA DevFeed: [Kubernetes v1.36: Declarative Validation Graduates to GA]() Original publisher: [Read original article]() Author: Yongrui Lin Published: 2026-05-05T18:35:00Z Content type: article Language: en Sources: [Kubernetes Blog]() Topics: [Kubernetes](), [API](), [Code](), [Go Language](), [Boilerplate](), [OpenAPI Specification](), [migration](), [Tooling]() Tags: [api](), [apis](), [code](), [contributors](), [developers](), [ecosystem](), [errors](), [feature](), [framework](), [go](), [kubernetes](), [migration](), [openapi](), [release](), [tooling](), [v1](), [validation]() ### AI overview Kubernetes v1.36 makes declarative validation for Kubernetes native types generally available. The article explains how marker tags and generated Go validation functions replace extensive handwritten validation code, improving maintainability, consistency, API discoverability, and integration with OpenAPI and ecosystem tooling. ### Source excerpt In Kubernetes v1.36, Declarative Validation for Kubernetes native types has reached General Availability (GA). For users, this means more reliable, predictable, and better-documented APIs. By moving to a declarative model, the project also unlocks the future ability to publish validation rules via OpenAPI and integrate with ecosystem tools like Kubebuilder. For contributors and ecosystem developers, this replaces thousands of lines of handwritten validation code with a unified, maintainable framework. This post covers why this migration was necessary, how the declarative validation framework works, and what new capabilities come with this GA release. The Motivation: Escaping the "Handwritten" Technical Debt For years, the validation of Kubernetes native APIs relied almost entirely on handwritten Go code. If a field needed to be bounded by a minimum value, or if two fields needed to be mutually exclusive, developers had to write explicit Go functions to enforce those constraints. As the Kubernetes API surface expanded, this approach led to several systemic issues: Technical Debt: The project accumulated roughly 18,000 lines of boilerplate validation code. This code was difficult to maintain, error-prone, and required intense scrutiny during code reviews. Inconsistency: Without a centralized framework, validation rules were sometimes applied inconsistently across different resources. Opaque APIs: Handwritten validation logic was difficult to discover or analyze programmatically. This meant clients and tooling couldn't predictably know validation rules without consulting the source code or encountering errors at runtime. The solution proposed by SIG API Machinery was Declarative Validation: using Interface Definition Language (IDL) tags (specifically +k8s: marker tags) directly within types.go files to define validation rules. Enter validation-gen At the core of the declarative validation feature is a new code generator called validation-gen. Just as Kubernetes uses ge ## Learn how to use scorecards for standards compliance DevFeed: [Learn how to use scorecards for standards compliance]() Original publisher: [Read original article]() Author: Jenny Salem Published: 2026-05-04T10:35:38Z Content type: article Language: en Sources: [Developer Experience & Platform Engineering Blog | Port]() Topics: [internal developer portal](), [Platform Engineering](), [ci](), [CI/CD](), [Boilerplate](), [dora metrics](), [Application Security]() Tags: [ci](), [compliance](), [dora-metrics](), [engineering](), [how-to](), [internal-developer-portal](), [learn](), [platform-engineering](), [workflows]() ### AI overview This article explains how internal developer portals can use scorecards to define, measure, monitor, and enforce engineering standards. It presents a repeatable framework with examples covering production readiness, application security, cost, pull request review times, DORA metrics, documentation, and continuous integration. ### Source excerpt Use scorecards for standards compliance with repeatable frameworks and examples to enforce consistency across engineering teams. ## From Zero to Product: A Guide for Building a SaaS with Laravel DevFeed: [From Zero to Product: A Guide for Building a SaaS with Laravel]() Original publisher: [Read original article]() Author: Wendell Adriel Published: 2026-05-01T12:15:00Z Content type: tutorial Language: en Sources: [Laravel Blog]() Topics: [Software as a service](), [App](), [Deployment](), [Boilerplate]() Tags: [app](), [authentication](), [building](), [database](), [deployment](), [feature-flags](), [framework](), [guide](), [how-to](), [laravel](), [product](), [production](), [routing](), [saas](), [testing]() ### AI overview A tutorial that outlines a production-ready Laravel SaaS blueprint using a TeamPulse example, covering sign-in, plans, feature access, and safe shipping. ### Source excerpt Build a production-ready SaaS the Artisan way with Laravel: Starter Kits, Socialite, Cashier, Pennant, and Laravel Cloud. ## Agentic coding at ClickHouse DevFeed: [Agentic coding at ClickHouse]() Original publisher: [Read original article]() Author: Alexey Milovidov Published: 2026-04-01T00:00:00Z Content type: article Language: en Sources: [ClickHouse Blog]() Topics: [AI-assisted coding](), [Language models](), [Boilerplate](), [C++](), [cursor]() Tags: [agentic-coding](), [agents](), [ai](), [c-plus-plus](), [claude-code](), [clickhouse](), [cursor](), [javascript](), [python](), [vibe-coding]() ### AI overview A ClickHouse perspective on using coding agents pragmatically: they can help with boilerplate and internal tools, but may perform poorly in a large C++ codebase. ### Source excerpt How to remain competitive in the AI era of software engineering ## How to Sell a SaaS Boilerplate or Starter Kit DevFeed: [How to Sell a SaaS Boilerplate or Starter Kit]() Original publisher: [Read original article]() Author: Aarthi Poonia Published: 2026-03-26T00:00:00Z Content type: tutorial Language: en Sources: [Dodo Payments Blog]() Topics: [Boilerplate](), [Software as a service](), [dev-tools](), [Documentation](), [GitHub]() Tags: [building](), [code](), [developer-tools](), [documentation](), [github](), [how-to](), [payment](), [payments](), [pricing](), [saas]() ### AI overview A practical guide to selling SaaS boilerplates and starter kits as digital assets. It covers licensing, code delivery, intellectual-property protection, pricing tiers, payment automation, documentation, updates, and support for audiences such as indie hackers and agencies. ### Source excerpt Learn the best strategies for monetizing your developer tools, from choosing a license model to automating delivery via GitHub. ## The Best Payment Provider for SaaS Starter Kits DevFeed: [The Best Payment Provider for SaaS Starter Kits]() Original publisher: [Read original article]() Author: Ayush Agarwal Published: 2026-03-25T00:00:00Z Content type: comparison Language: en Sources: [Dodo Payments Blog]() Topics: [Software as a service](), [stripe](), [Boilerplate](), [Development]() Tags: [api-keys](), [comparison](), [developer-tools](), [merchant-of-record](), [payment](), [payments](), [saas](), [stripe]() ### AI overview A comparison of payment approaches for SaaS starter kits. The article argues that a Merchant of Record can reduce founders' responsibility for VAT, GST, US sales tax, and chargeback liability compared with a typical Stripe integration, and discusses replacing Stripe with Dodo Payments. ### Source excerpt Comparison of payment providers for SaaS boilerplates and starter kits. Why a Merchant of Record beats Stripe for ShipFast, supastarter, Makerkit, and other SaaS starters. ## How to Replace Stripe in Your SaaS Boilerplate DevFeed: [How to Replace Stripe in Your SaaS Boilerplate]() Original publisher: [Read original article]() Author: Ayush Agarwal Published: 2026-03-25T00:00:00Z Content type: tutorial Language: en Sources: [Dodo Payments Blog]() Topics: [Software as a service](), [Boilerplate](), [stripe]() Tags: [compliance](), [developer-tools](), [eu](), [guide](), [how-to](), [merchant-of-record](), [payments](), [saas](), [uk](), [vat]() ### AI overview A developer guide explains how to replace Stripe with Dodo Payments in SaaS boilerplates such as ShipFast, supastarter, and Makerkit. It focuses on Merchant of Record responsibilities, global tax compliance, environment variables, and subscription lifecycles. ### Source excerpt A developer's guide to migrating from Stripe to Dodo Payments in popular SaaS boilerplates like ShipFast, supastarter, and Makerkit to handle global taxes and compliance automatically. ## Inertia.js v3 Is Now in Beta DevFeed: [Inertia.js v3 Is Now in Beta]() Original publisher: [Read original article]() Author: Pascal Baljet Published: 2026-03-05T16:54:27Z Content type: release Language: en Sources: [Laravel Blog]() Topics: [Vite](), [Server-side rendering](), [Boilerplate](), [migration](), [Node.js](), [API]() Tags: [development](), [http](), [migration](), [node-js](), [release](), [updates]() ### AI overview Inertia.js v3 has entered beta with a Vite plugin that automates page resolution and SSR, a built-in XHR client replacing Axios, and support for optimistic updates, standalone HTTP requests, and layout props. ### Source excerpt Inertia.js v3 beta is out. No more Axios, a new Vite plugin handles SSR automatically, and optimistic updates are now built in. Upgrade guide included. ## Reusable Prompts: The Future of Starter Templates DevFeed: [Reusable Prompts: The Future of Starter Templates]() Original publisher: [Read original article]() Author: Andre Landgraf Published: 2026-01-08T16:26:24Z Content type: article Language: en Sources: [Blog -- Neon Docs]() Topics: [AI-assisted coding](), [Boilerplate](), [cursor](), [Drizzle](), [vercel ai sdk]() Tags: [agent-skills](), [ai](), [ai-agents](), [ai-assisted-coding](), [ai-coding](), [anthropic](), [claude-code](), [cursor](), [drizzle](), [mcp](), [product](), [tailwind](), [vercel](), [vibe-coding]() ### AI overview The article argues that reusable prompts, skills, MCP integrations, and plugins can replace traditional starter-template boilerplate for AI-assisted development. ### Source excerpt Looking back at 2025, AI changed coding for good. Early in the year, skepticism around AI-assisted coding was still high and capabilities were limited. Now it's clear that vibe coding has gone mainstream, and AI-assisted coding is the future of software engineering. That said, we... ## Inside JetBrains--the company reshaping how the world writes code DevFeed: [Inside JetBrains--the company reshaping how the world writes code]() Original publisher: [Read original article]() Published: 2025-11-25T00:00:00Z Content type: article Language: en Sources: [OpenAI News]() Topics: [AI-assisted coding](), [AI Chat](), [Boilerplate]() Tags: [agent](), [ai](), [chatgpt](), [codex](), [coding](), [developers](), [gpt](), [junie](), [openai](), [review]() ### AI overview JetBrains describes integrating OpenAI models, including GPT-5 and Codex, into its development workflows and coding products. The article emphasizes hybrid workflows in which AI handles drafts and repetitive tasks while engineers retain responsibility for design, review, readability, safety, and maintainability. ### Source excerpt JetBrains is integrating GPT-5 across its coding tools, helping millions of developers design, reason, and build software faster. ## Automated Package-Publication Incident IndonesianFoods in the NPM Ecosystem Linked to Crypto Reward-Farming Scam DevFeed: [Automated Package-Publication Incident IndonesianFoods in the NPM Ecosystem Linked to Crypto Reward-Farming Scam]() Original publisher: [Read original article]() Author: Stephen Thoemmes Published: 2025-11-13T05:00:00Z Content type: article Language: en Sources: [Blog RSS Feed | Snyk]() Topics: [incident](), [Boilerplate]() Tags: [automation](), [awareness](), [blog](), [code-security](), [container-security](), [cryptocurrency](), [developer](), [ecosystem](), [incident](), [next-js](), [npm-packages](), [open-source-security](), [publication](), [scam](), [security](), [snyk-code](), [snyk-container](), [snyk-iac](), [snyk-open-source](), [supply-chain-security]() ### AI overview The article examines a large-scale surge of similarly structured NPM package publications linked to a dormant automation script associated with a cryptocurrency reward-farming scheme. It reports no verified active exploit and says the packages currently pose minimal risk, while emphasizing dependency hygiene and registry safeguards. ### Source excerpt In November 2025, a large-scale surge of package publications on the NPM registry with similar structures and naming patterns was discovered. Understand the details of the incident. ## Introducing Compose Unstyled boilerplates DevFeed: [Introducing Compose Unstyled boilerplates]() Original publisher: [Read original article]() Author: Alex Styl Published: 2025-10-23T00:00:00Z Content type: release Language: en Sources: [Composables - Concise, no-fluff video tutorials for Android developers]() Topics: [Compose](), [compose-multiplatform](), [Template](), [Android](), [multiplatform](), [Boilerplate]() Tags: [android](), [building](), [compose](), [compose-multiplatform](), [design](), [docs](), [getting-started](), [gradle](), [multiplatform](), [tokens]() ### AI overview The article announces official Compose Unstyled Boilerplates for Android and Compose Multiplatform apps. The templates are designed to provide minimal project setups with custom theming, themable components, Lucide Icons, multiplatform support, and other included configuration and development features. ### Source excerpt Start building apps with Compose Unstyled in seconds. ## Vibe Coding: Best Practices for Prompting DevFeed: [Vibe Coding: Best Practices for Prompting]() Original publisher: [Read original article]() Author: Prashant Sridharan Published: 2025-08-16T07:00:00Z Content type: tutorial Language: en Sources: [Supabase Blog]() Topics: [Prompt Engineering](), [Vibe coding](), [ai-coding](), [cursor](), [Claude Code](), [Code](), [React](), [Supabase](), [Tailwind CSS](), [API](), [Boilerplate]() Tags: [ai-assistants](), [ai-coding](), [ai-tools](), [api](), [best-practices](), [claude-code](), [code](), [cursor](), [react](), [tailwind](), [vibe-coding]() ### AI overview This tutorial explains how to prompt AI coding assistants effectively for vibe coding. It covers providing technical and application context, structuring prompts in layers, refining results iteratively, and maintaining continuity across coding sessions to produce coherent, deployable applications. ### Source excerpt Master the art of communicating with AI coding assistants through effective prompting strategies, iterative refinement, and systematic approaches that turn ideas into deployable applications. ## Ready, steady, goa: our API setup DevFeed: [Ready, steady, goa: our API setup]() Original publisher: [Read original article]() Author: Shlok Shah Published: 2025-08-11T10:51:01Z Content type: article Language: en Sources: [The incident.io Blog]() Topics: [API](), [Go Language](), [OpenAPI Specification](), [Boilerplate](), [Back end]() Tags: [api](), [backend](), [blog](), [engineering](), [examples](), [go](), [incident](), [incident-channel](), [incident-management](), [incident-response](), [openapi](), [outage](), [post-mortem](), [slack-incident]() ### AI overview This article explains incident.io's design-first API setup for making endpoint creation fast, reliable, and scalable. It describes the company's use of Goa on top of Go, contrasts the approach with an older manually maintained setup, and discusses shared types, generated clients, and OpenAPI documentation. ### Source excerpt Writing API's is essentially for any engineering team. Find out how we make the whole process so easy and abstract out the nonsense to help our engineers move that much faster ## Laravel Starter Kits: A New Beginning for Your Next Project DevFeed: [Laravel Starter Kits: A New Beginning for Your Next Project]() Original publisher: [Read original article]() Author: Chris Sev Published: 2025-03-19T21:40:00Z Content type: release Language: en Sources: [Laravel Blog]() Topics: [Boilerplate](), [Web Development](), [passwords](), [Dark Mode](), [MFA]() Tags: [authentication](), [dark-mode](), [jetstream](), [laravel](), [react](), [tailwind](), [vue]() ### AI overview Laravel has replaced its Jetstream and Breeze starter kits with standalone Livewire, React, and Vue applications. The kits include common application foundations such as authentication, profile management, dark mode, layout options, and Tailwind CSS integration. ### Source excerpt We've overhauled our starter kits, replacing Jetstream and Breeze with three distinct, purpose-built starter kits in Livewire, React, and Vue. These new kits allow you to focus on building your app instead of creating boilerplate code from scratch. ## Introducing The AWS AI Stack DevFeed: [Introducing The AWS AI Stack]() Original publisher: [Read original article]() Author: Serverless Team Published: 2024-09-11T00:00:00Z Content type: release Language: en Sources: [Serverless Blog]() Topics: [Artificial Intelligence](), [Amazon Web Services](), [Amazon Bedrock](), [Large Language Model](), [AWS Lambda](), [Boilerplate](), [Claude](), [React](), [Serverless](), [Back end](), [Front end](), [llama3]() Tags: [ai](), [aws](), [aws-lambda](), [back-end](), [bedrock](), [ci-cd](), [claude](), [cloud-computing](), [faas](), [front-end](), [function-as-a-service](), [infrastructure-as-code](), [llama3](), [llms](), [news](), [react](), [serverless](), [serverless-architecture](), [serverless-framework]() ### AI overview The AWS AI Stack is introduced as a full-stack, serverless boilerplate for building AI applications on AWS. It uses Bedrock LLMs including Claude 3.5 Sonnet and Llama3.1, with a React front end, AWS Lambda back end, and built-in CI/CD. ### Source excerpt Full-stack, serverless, boilerplate for AI applications on AWS, featuring Bedrock LLMs like Claude 3.5 Sonnet and Llama3.1, a React front-end, AWS Lambda back-end, built-in CI/CD and more. ## Introducing the Turso Per-User Starter DevFeed: [Introducing the Turso Per-User Starter]() Original publisher: [Read original article]() Author: Jamie Barton Published: 2024-08-28T00:00:00Z Content type: article Language: en Sources: [Turso Blog]() Topics: [Turso](), [Multi-tenancy](), [Per-user Database](), [Boilerplate](), [libSQL](), [Next.js](), [SQLite](), [Drizzle](), [Software as a service](), [GitHub](), [Discord](), [Demo]() Tags: [discord](), [drizzle](), [github](), [libsql](), [multi-tenancy](), [next-js](), [orm](), [saas](), [sqlite](), [turso](), [tutorial]() ### AI overview Turso introduces a Per-User Starter boilerplate for building scalable multi-tenant SaaS applications with Next.js, Clerk, Drizzle, and Turso. It uses Turso's multi-database schemas to support database-per-user or database-per-tenant architectures, with libSQL enabling consistent local, cloud, edge, and infrastructure deployments. ### Source excerpt Power Multi-Tenant Applications with Next.js, Clerk, Drizzle, and Turso ## Kotlin 1.9.20: Streamlining Source Sets in Multiplatform Project DevFeed: [Kotlin 1.9.20: Streamlining Source Sets in Multiplatform Project]() Original publisher: [Read original article]() Author: Jigar Brahmbhatt Published: 2024-03-26T13:57:17Z Content type: release Language: en Sources: [Touchlab]() Topics: [Kotlin Multiplatform](), [Kotlin](), [Gradle](), [Boilerplate](), [configuration](), [Code]() Tags: [apple](), [coding](), [community](), [configuration](), [development](), [efficiency](), [engineering](), [gradle](), [gradle-plugin](), [inclusive](), [kmp](), [kotlin](), [kotlin-multiplatform](), [kotlinmultiplatform](), [multiplatform](), [readability](), [software]() ### AI overview Kotlin 1.9.20 makes Kotlin Multiplatform stable and introduces a default source set hierarchy template through the Kotlin Gradle Plugin. The update simplifies iOS target configuration, custom source sets, dependency setup, and IDE code completion while reducing boilerplate. ### Source excerpt The release of Kotlin 1.9.20 marked a significant milestone for Kotlin Multiplatform enthusiasts, as this update moved Kotlin Multiplatform to Stable. Kotlin 1.9.20 introduces several notable features and enhancements. Among these updates, the new source set hierarchy template by the Kotlin Gradle Plugin stands out to me for its ability to simplify configuration complexities. It was launched as experimental in Kotlin 1.8.20 and has been made default in Kotlin 1.9.20. Simplified iOS Target Configuration In the common Kotlin Multiplatform project set-up, you would have seen specific source set setup for two or three iOS targets like for X64, Arm64. Instead of the common and confusing 'ios()' target, one must always declare specific targets like 'iosArm64()' as required. Once one of the iOS targets is declared, the default template would automatically create iosMain source set. So no more val iosMain by creating boilerplate required. Before 1.9.20 After 1.9.20 kotlin { ios() iosSimulatorArm64() sourceSets { val commonMain by getting val iosMain by creating { dependsOn(commonMain) } val iosX64Main by getting { dependsOn(iosMain) } val iosArm64Main by getting { dependsOn(iosMain) } val iosSimulatorArm64Main by getting { dependsOn(iosMain) } } } kotlin { iosX64() iosArm64() iosSimulatorArm64() // The iosMain source set is now created automatically // You can directly use the reference now iosMain.dependencies { implementation("...") } } If you've an old KMP project and still have reference of darwinMain, you can simply rename it to appleMain now as that encapsulates all other apple targets. Checkout the full hierarchy template! Streamlined Custom Source Sets Managing custom source sets in Kotlin Multiplatform projects is now more straightforward with Kotlin 1.9.20. The update simplifies the process of setting up dependencies between source sets, reducing the need for extensive boilerplate code and enhancing overall readability. For example, let's assume that you already h [Next page]()