<?xml version="1.0" encoding="UTF-8"?>
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<feed xmlns="http://www.w3.org/2005/Atom" xml:lang="en-US">
                        <id>https://laravel.io/index.php/forum/feed</id>
                                <link href="https://laravel.io/index.php/forum/feed" rel="self"></link>
                                <title><![CDATA[Laravel.io Forum RSS Feed]]></title>
                    
                                <subtitle>The RSS feed for the Laravel.io forum contains a list of all threads posted by community members.</subtitle>
                                                    <updated>2026-09-13T03:31:53+00:00</updated>
                        <entry>
            <title><![CDATA[Is There a Free Jira Alternative for the Agent Era?]]></title>
            <link rel="alternate" href="https://laravel.io/index.php/forum/is-there-a-free-jira-alternative-for-the-agent-era" />
            <id>https://laravel.io/index.php/30897</id>
            <author>
                <name><![CDATA[luc]]></name>
            </author>
            <summary type="html">
                <![CDATA[As AI agents become part of Laravel development, I’m starting to question whether traditional project management tools still make sense for small development teams.

For a small Laravel project, I’d ideally want a free Jira alternative that can:

Assign tasks to developers and AI agents
Keep project context in one place
Let agents work on coding, testing, or documentation tasks
Track progress without adding too much overhead
Keep developers in control of reviews and approvals

I’ve been exploring Sharkly.ai, which takes an interesting approach by combining project management with AI agents that can participate directly in the workflow.

For Laravel developers using tools like Claude Code or other coding agents, what free Jira alternatives are you using?

And do you think project management tools need to change now that AI agents can actually take responsibility for development tasks?]]>
            </summary>
                                    <updated>2026-09-13T03:31:53+00:00</updated>
        </entry>
            <entry>
            <title><![CDATA[AI Social Media Managers for Small Businesses- Worth IT ?]]></title>
            <link rel="alternate" href="https://laravel.io/index.php/forum/ai-social-media-managers-for-small-businesses-worth-it" />
            <id>https://laravel.io/index.php/30896</id>
            <author>
                <name><![CDATA[Thomas Shellby]]></name>
            </author>
            <summary type="html">
                <![CDATA[Managing social media has become one of the biggest challenges for small businesses. Customers expect brands to post consistently, respond quickly, and stay active across multiple platforms. However, many business owners don't have dedicated marketing teams. Instead, they juggle sales, operations, customer service, and marketing all at once, leaving little time to manage social media effectively.

This is one of the main reasons AI Social Media Managers have gained so much attention in recent years. Rather than replacing marketers, these AI-powered tools help automate repetitive tasks like content planning, caption writing, scheduling posts, and analyzing performance. The result is a more efficient workflow that allows business owners to spend less time on routine activities and more time growing their businesses.

One of the biggest benefits AI brings is content creation. Many businesses struggle to come up with fresh ideas every day, especially when posting across several platforms. AI can generate post ideas, write captions, recommend hashtags, and even suggest different content formats based on a business's industry. Instead of starting from scratch, marketers receive a solid draft they can personalize before publishing.

Planning content is another area where AI makes a noticeable difference. Rather than deciding what to post every morning, businesses can prepare weeks of content in advance. AI can organize a publishing calendar, recommend the best posting times, and help maintain a healthy mix of promotional, educational, and engaging content. This level of planning makes it much easier to stay consistent, which remains one of the most important factors in successful social media marketing.

Audience engagement is another challenge that small businesses often face. Customers expect quick responses to messages and comments, but replying manually throughout the day isn't always practical. AI can assist by organizing conversations, suggesting replies to common questions, and prioritizing important customer inquiries. While businesses should still respond personally when needed, AI reduces the time spent handling repetitive interactions.

Performance tracking is also becoming much more accessible with AI. Traditional social media analytics can feel overwhelming, especially for business owners without a marketing background. Instead of reviewing dozens of charts and metrics, AI summarizes campaign performance in simple language, highlights successful posts, and recommends areas for improvement. These insights help businesses make smarter marketing decisions without requiring advanced analytical skills.

Despite these advantages, AI isn't a complete replacement for human creativity. Social media is ultimately about building trust and relationships. Customers want authentic stories, real experiences, and genuine conversations with brands. AI can suggest ideas and automate repetitive work, but it cannot replace the personality and unique voice that make a business memorable.

This balance between automation and authenticity is important. Businesses that rely entirely on AI-generated content without reviewing or personalizing it often produce generic posts that fail to connect with their audience. The most successful companies use AI as a creative assistant rather than an automatic publishing tool. They review every caption, adjust messaging to match their brand, and ensure each post feels natural and relevant.

Another interesting aspect worth discussing is cost. Hiring a dedicated social media manager or agency can be expensive for many startups and local businesses. AI-powered tools provide an affordable alternative by allowing smaller teams to manage multiple platforms efficiently. While they don't eliminate the need for marketing expertise, they significantly reduce the time required to execute daily social media tasks.

AI also supports better long-term planning. Instead of reacting to trends at the last minute, businesses can build structured content calendars, identify seasonal opportunities, and monitor audience behavior over time. This proactive approach often produces stronger results than creating content only when time allows.

As AI technology continues to improve, we're also seeing smarter personalization. Future AI social media managers may better understand audience preferences, recommend content based on customer behavior, and provide deeper insights into engagement trends. These capabilities could help even the smallest businesses compete more effectively with larger brands that have bigger marketing budgets.

For entrepreneurs considering AI Social Media App Development, there's also a growing opportunity to build specialized solutions instead of general-purpose tools. Rather than creating another scheduling platform, startups can focus on solving specific problems such as AI-powered analytics, content generation, community management, or customer engagement. Businesses increasingly value tools that address real workflow challenges rather than simply adding more features.

Ultimately, AI Social Media Managers should be viewed as productivity tools rather than replacements for marketers. They help businesses create content faster, stay organized, analyze performance, and automate repetitive tasks, but strategic thinking, creativity, and customer relationships still require human involvement.

Companies like **Triple Minds** are helping businesses and startups integrate AI into social media management by developing intelligent solutions that improve efficiency while supporting long-term digital growth.

Discussion Questions:

Have you used an AI Soc![](![]())ial Media Manager for your business?
Which tasks do you think AI handles best—content creation, scheduling, analytics, or customer engagement?
Do you believe AI will eventually manage most social media marketing, or will human creativity always remain essential?
What features would you like to see in the next generation of AI-powered social media management tools?]]>
            </summary>
                                    <updated>2026-09-13T03:31:53+00:00</updated>
        </entry>
            <entry>
            <title><![CDATA[Can MCP Make AI Agents Easier to Collaborate on Laravel Proj]]></title>
            <link rel="alternate" href="https://laravel.io/index.php/forum/can-mcp-make-ai-agents-easier-to-collaborate-on-laravel-proj" />
            <id>https://laravel.io/index.php/30895</id>
            <author>
                <name><![CDATA[Herve Kom]]></name>
            </author>
            <summary type="html">
                <![CDATA[Laravel is becoming a much more interesting environment for AI agents, especially with MCP making application context and tools accessible to agents.

But when several agents are involved, I think another problem appears: collaboration.

A platform for team collaboration on AI agents could help with:

Assigning specific tasks to different agents
Sharing Laravel project context
Coordinating development and testing work
Tracking agent progress and handoffs
Keeping developers involved for review

I’ve been exploring Sharkly.ai, which takes an interesting approach by bringing agents and human developers into a shared project workflow.

For Laravel teams experimenting with MCP and AI agents, how are you currently managing collaboration between multiple agents?

Would you use a dedicated collaboration layer alongside your existing Laravel AI tools?]]>
            </summary>
                                    <updated>2026-09-13T03:31:53+00:00</updated>
        </entry>
            <entry>
            <title><![CDATA[🎬 What's the Biggest Challenge in Launching a Vertical Dram]]></title>
            <link rel="alternate" href="https://laravel.io/index.php/forum/whats-the-biggest-challenge-in-launching-a-vertical-dram" />
            <id>https://laravel.io/index.php/30894</id>
            <author>
                <name><![CDATA[Thomas Shellby]]></name>
            </author>
            <summary type="html">
                <![CDATA[Over the past year, vertical drama platforms like ReelShort have transformed the way people consume entertainment. Short, engaging episodes designed for mobile users have created a new category of streaming, and it's easy to understand why so many startups are looking to enter this market.

At first glance, building a [ReelShort Clone](https://tripleminds.co/white-label/reelshort-clone/) platform seems straightforward. With modern development frameworks and ready-made solutions available, getting an app into users' hands is faster than ever. But after researching this space, I've realized that launching the app is probably the easiest part of the journey.

The real challenge begins after your product goes live.

Is the biggest hurdle creating original content that keeps users coming back? Is it acquiring creators and production partners? Or is it designing a monetization model that balances user experience with revenue—subscriptions, virtual coins, pay-per-episode, or advertising?

Then there's the technical side. As your audience grows, so do the demands on your infrastructure. Video streaming performance, content delivery, recommendations, analytics, payment systems, and scalability all become increasingly important. A platform that works perfectly for 1,000 users may struggle with 100,000.

Another question founders often face is whether to build everything from scratch or start with a proven solution like [Reelxia](https://reelxia.app/), a white-label ReelShort clone. Building a custom platform offers complete flexibility but usually requires a larger budget, a longer timeline, and a dedicated engineering team. On the other hand, Reelxia provides many of the core features needed to launch a short-drama platform, allowing startups to focus more on branding, content strategy, marketing, and user acquisition instead of reinventing the foundation.

Of course, there isn't a single right answer. Every startup has different goals, resources, and priorities. Some teams value complete control over every feature, while others prioritize speed to market and rapid validation.

I'm genuinely interested in hearing from developers, founders, product managers, and anyone working in the streaming industry.

If you were launching a vertical drama streaming platform today, what would be your biggest challenge?

Building the technology?
Finding compelling content?
Growing and retaining users?
Monetization?
Standing out in a competitive market?
Or something else entirely?

I'd love to hear your perspective and learn from your experiences.

If you're currently evaluating white-label solutions, I recently reviewed Reelxia and explored its features, customization capabilities, benefits, and considerations for startups looking to launch a ReelShort-style platform.]]>
            </summary>
                                    <updated>2026-09-13T03:31:53+00:00</updated>
        </entry>
            <entry>
            <title><![CDATA[What Would a Multi-Agent Collaboration Platform Look Like fo]]></title>
            <link rel="alternate" href="https://laravel.io/index.php/forum/what-would-a-multi-agent-collaboration-platform-look-like-fo" />
            <id>https://laravel.io/index.php/30893</id>
            <author>
                <name><![CDATA[luc]]></name>
            </author>
            <summary type="html">
                <![CDATA[As AI agents become more common in Laravel development, I’m wondering how teams should manage several agents working on the same project.

It’s easy to run an agent for a specific task, but coordinating multiple agents seems like a different problem.

Ideally, a platform should let teams:

Assign different tasks to different agents
Share project context between agents
Run development, testing, and documentation tasks in parallel
Track what each agent is working on
Keep developers involved for review and approval

I’ve been exploring Sharkly.ai, which takes an interesting approach by putting AI agents into a shared team workflow instead of treating them as isolated coding assistants.

For Laravel developers already experimenting with agents, MCP, or AI workflows, how are you coordinating multiple agents today?

Would a dedicated multi-agent collaboration platform be useful for your projects?]]>
            </summary>
                                    <updated>2026-09-13T03:31:53+00:00</updated>
        </entry>
            <entry>
            <title><![CDATA[Is There a Jira Alternative That Treats AI Agents as Real Te]]></title>
            <link rel="alternate" href="https://laravel.io/index.php/forum/is-there-a-jira-alternative-that-treats-ai-agents-as-real-te" />
            <id>https://laravel.io/index.php/30892</id>
            <author>
                <name><![CDATA[Herve Kom]]></name>
            </author>
            <summary type="html">
                <![CDATA[I’ve been thinking about how project management tools should evolve as AI agents become part of software development.

Most tools still treat AI as an automation layer, while the actual project workflow is built around human developers.

For a Laravel team, I’d find it useful to have a workspace where you can:

Assign tasks to developers or AI agents
Track agent work alongside human tasks
Share project context
Run multiple tasks in parallel
Keep developers responsible for reviews and decisions

That’s what caught my attention about Sharkly. It takes a more team-oriented approach where AI agents can participate directly in the project workflow rather than just being a chatbot.

Would you consider using a Jira alternative where AI agents are treated as actual teammates?]]>
            </summary>
                                    <updated>2026-09-13T03:31:53+00:00</updated>
        </entry>
            <entry>
            <title><![CDATA[Is a ReelShort Clone Worth Building?]]></title>
            <link rel="alternate" href="https://laravel.io/index.php/forum/is-a-reelshort-clone-worth-building" />
            <id>https://laravel.io/index.php/30891</id>
            <author>
                <name><![CDATA[Thomas Shellby]]></name>
            </author>
            <summary type="html">
                <![CDATA[Hi everyone,

I've been exploring the growing trend of vertical short-drama streaming platforms like ReelShort and DramaBox, and I'm curious about white-label clone solutions.

For anyone who's built or launched a short-video drama platform, I'd love to hear your thoughts.

A few questions for the community:

Is it better to build a platform from scratch or use a white-label ReelShort clone?
How customizable are these clone solutions?
What features are considered essential for a successful micro-drama streaming app?
Are subscription and coin-based monetization models actually profitable?
How important are AI-powered recommendations and user analytics?
What are the biggest challenges after launching—content, marketing, or user retention?

I'm also interested in knowing which companies provide reliable **[Reelshort Clone](https://tripleminds.co/white-label/reelshort-clone/)** development with complete source code ownership and long-term scalability.

During my research, I came across Triple Minds, which also offers custom OTT and AI-powered application development. Has anyone worked with them or compared their services with other development companies?

Looking forward to hearing your experiences, recommendations, and lessons learned.]]>
            </summary>
                                    <updated>2026-09-13T03:31:53+00:00</updated>
        </entry>
            <entry>
            <title><![CDATA[TypeScript Everywhere: Practical Full Stack Migration Guide]]></title>
            <link rel="alternate" href="https://laravel.io/index.php/forum/typescript-everywhere-practical-full-stack-migration-guide" />
            <id>https://laravel.io/index.php/30890</id>
            <author>
                <name><![CDATA[Hidden Brains]]></name>
            </author>
            <summary type="html">
                <![CDATA[I spent about four months last year migrating a mid-size Laravel + Vue app to a TypeScript-first stack, and I want to save someone else the headache I gave myself in week one: I tried to convert everything at once. Don't do that.

**Key stance:** you don't migrate a codebase to TypeScript. You migrate the boundaries first, then let the middle catch up whenever it wants to.

Here's what actually worked.

## Start with your API contract, not your components

The biggest win came before I touched a single `.vue` file. I generated TypeScript types straight from our Laravel API responses using a package that reads route definitions and Eloquent resources, and suddenly the frontend knew exactly what shape the backend was sending. Half our "why is this undefined" bugs were just frontend code guessing at API shapes. Once the types existed, the guessing stopped.

If you're on Laravel, look at spatie/laravel-typescript-transformer or similar tools before you write a single interface by hand. Hand-written types drift from reality within a sprint. Generated ones don't.

## Convert leaf components before core ones

I made the mistake of starting with our biggest, most central component (a 900-line order form, genuinely a mess) because it felt like the "important" one to fix. Wrong move. It touched everything, so every conversion attempt cascaded into fifteen other files.

Instead, flip it: convert the small, dumb, leaf-level components first. Buttons, cards, form inputs. Nothing depends on them, so there's no cascade. You build TypeScript muscle memory on low-stakes files, and by the time you reach the scary 900-line form, you've already got your patterns figured out.

## `allowJs` is your friend, not a crutch

Set `"allowJs": true` in your tsconfig and let JS and TS files sit side by side for as long as it takes. We ran mixed for about ten weeks. That's fine. The alternative, a hard cutover weekend, sounds efficient and is actually how you end up debugging production at 11pm.

## The part nobody warns you about: your build config

Vite handles TS out of the box, no drama there. Where we lost two full days was Laravel Mix, which was still hanging around one legacy module. If you're still on Mix anywhere in your app, migrate that piece to Vite first. Fighting Mix and TypeScript at the same time is not a fight worth having.

## Where I landed

Full migration took longer than the estimate (they always do), but the payoff showed up fast: refactors that used to take an afternoon of careful reading now take twenty minutes, because the compiler tells me what I broke before a user does.

Curious what tooling others here are using for the Laravel-to-TS type bridge. Anyone tried the Inertia + TS combo at scale?

If your team doesn't have the bandwidth to run a migration like this alongside regular feature work, it's worth bringing in extra hands rather than stalling the roadmap for months. We looked at a few options and ended up leaning on outside help for the crunch weeks. If you're in the same boat, you can [hire dedicated full stack developers](https://www.hiddenbrains.com/hire-fullstack-developers.html) to keep the migration moving without pulling your core team off their sprint.]]>
            </summary>
                                    <updated>2026-09-13T03:31:53+00:00</updated>
        </entry>
            <entry>
            <title><![CDATA[When Does It Make Sense to Replace Postman for Laravel API T]]></title>
            <link rel="alternate" href="https://laravel.io/index.php/forum/when-does-it-make-sense-to-replace-postman-for-laravel-api-t" />
            <id>https://laravel.io/index.php/30889</id>
            <author>
                <name><![CDATA[luc]]></name>
            </author>
            <summary type="html">
                <![CDATA[Postman has been part of my Laravel API workflow for a long time, but lately I’ve been looking for something that fits better with CLI and CI/CD workflows.

For Laravel API projects, I usually want to:

Run API tests from the command line
Manage multiple environments
Reuse the same tests in CI/CD
Keep API documentation updated
Share API workflows between developers and QA

That’s what led me to look at Apidog as a possible Postman alternative.

What I find interesting is that it combines API design, testing, documentation, and CLI automation instead of keeping those workflows separate.

For those building Laravel APIs:

Are you still using Postman?

Have you moved to another tool for API testing?

And how are you handling API tests in your CI/CD pipeline?]]>
            </summary>
                                    <updated>2026-09-13T03:31:53+00:00</updated>
        </entry>
            <entry>
            <title><![CDATA[What Terminal-Based API Testing Tool Do You Use for Laravel?]]></title>
            <link rel="alternate" href="https://laravel.io/index.php/forum/what-terminal-based-api-testing-tool-do-you-use-for-laravel" />
            <id>https://laravel.io/index.php/30856</id>
            <author>
                <name><![CDATA[luc]]></name>
            </author>
            <summary type="html">
                <![CDATA[Most of the Laravel projects I work on expose REST APIs, and I've been trying to move more of my API testing into the terminal instead of relying on a GUI.

The goal is simple: use the same workflow locally and in CI/CD.

I'm looking for a terminal-based API testing tool that can:

*Run API tests from the command line
*Support multiple environments
*Work with OpenAPI-based APIs
*Integrate with GitHub Actions
*Return reliable exit codes for automation

So far I've tried curl, HTTPie, Hurl, Newman, and Apidog CLI.

I've been leaning toward Apidog CLI because I can run the same API test scenarios while developing a Laravel application and then reuse those tests in GitHub Actions without maintaining separate workflows.

For those building API-first Laravel applications:

*What terminal-based API testing tool do you use?
*Have you completely replaced Postman, or do you use both?
*Which tool has been the easiest to integrate into your CI/CD pipeline?]]>
            </summary>
                                    <updated>2026-09-13T03:31:53+00:00</updated>
        </entry>
            <entry>
            <title><![CDATA[How Can Fixer Simplify Currency Conversion?]]></title>
            <link rel="alternate" href="https://laravel.io/index.php/forum/how-can-fixer-simplify-currency-conversion" />
            <id>https://laravel.io/index.php/30886</id>
            <author>
                <name><![CDATA[William hazad]]></name>
            </author>
            <summary type="html">
                <![CDATA[Fixer is a currency exchange API designed to help developers access reliable exchange rate and currency conversion data. It can be integrated into websites, mobile applications, ecommerce platforms, financial dashboards, and other digital products that work with multiple currencies.

With structured currency data available through an API, developers can automate exchange rate retrieval and reduce the need for manually maintained currency information. This can be useful for displaying converted prices, supporting international transactions, creating currency converters, and managing financial calculations across different markets.

Fixer also provides a practical option for businesses and developers looking to build applications that require currency-related data without creating their own exchange rate infrastructure from scratch.

**Get started with Fixer:** https://fixer.io/]]>
            </summary>
                                    <updated>2026-09-13T03:31:53+00:00</updated>
        </entry>
            <entry>
            <title><![CDATA[Why Isn't My Website Ranking for Arabic Keywords?]]></title>
            <link rel="alternate" href="https://laravel.io/index.php/forum/why-isnt-my-website-ranking-for-arabic-keywords" />
            <id>https://laravel.io/index.php/30885</id>
            <author>
                <name><![CDATA[Thomas Shellby]]></name>
            </author>
            <summary type="html">
                <![CDATA[Hi everyone,

I'm trying to figure out why a website that performs well for English searches struggles to gain visibility for Arabic keywords. We've already added Arabic content, but the rankings and organic traffic haven't improved as expected.

I'd love to hear from anyone with experience in multilingual or regional SEO.

A few questions:

Is translating existing content enough, or should Arabic content be written specifically for native speakers?
How much does localized keyword research influence rankings?
Do technical factors like RTL formatting, hreflang implementation, and Arabic-friendly URLs make a noticeable difference?
Are region-specific backlinks important for improving Arabic keyword rankings?
Does Google interpret search intent differently across GCC countries?

If you've managed Arabic SEO campaigns, what changes had the biggest impact on rankings?

I'm particularly interested in understanding what businesses in Dubai are doing differently to compete in Arabic search results and whether investing in a dedicated [arabic SEO services in Dubai](https://burjcode.ae/marketing/arabic-seo-services-dubai/) is worth it.

Looking forward to hearing your experiences and recommendations.

While researching agencies that specialize in Arabic SEO, I came across Burj Code. If anyone has worked with them or knows about their approach, I'd be interested in hearing your feedback.]]>
            </summary>
                                    <updated>2026-09-13T03:31:53+00:00</updated>
        </entry>
            <entry>
            <title><![CDATA[How should Laravel applications handle AI agents that need h]]></title>
            <link rel="alternate" href="https://laravel.io/index.php/forum/how-should-laravel-applications-handle-ai-agents-that-need-h" />
            <id>https://laravel.io/index.php/30884</id>
            <author>
                <name><![CDATA[luc]]></name>
            </author>
            <summary type="html">
                <![CDATA[I've been experimenting with AI-driven workflows in Laravel, and one question keeps coming up: what should happen when an AI agent reaches a step where it shouldn't make the decision on its own?

For example, imagine a queued workflow where an agent:

Receives a task
Analyzes the data
Executes several actions
Reaches a decision requiring human approval
Pauses the workflow
Resumes after the human provides feedback

Laravel already gives us useful building blocks for this with queues, jobs, events, notifications, and scheduled tasks.

The interesting part is combining those pieces with an agent that can maintain its state and continue the workflow after a human intervention.

I've also been exploring this concept from the project-management side with Sharkly, where AI agents can work alongside human teammates and hand tasks back to humans when they need input.

https://sharkly.ai/

For Laravel developers building AI agents, how are you currently handling state, retries, approvals, and human-in-the-loop steps in long-running agent workflows?]]>
            </summary>
                                    <updated>2026-09-13T03:31:53+00:00</updated>
        </entry>
            <entry>
            <title><![CDATA[Good Coding Challenges]]></title>
            <link rel="alternate" href="https://laravel.io/index.php/forum/good-coding-challenges" />
            <id>https://laravel.io/index.php/30883</id>
            <author>
                <name><![CDATA[Thomas Shellby]]></name>
            </author>
            <summary type="html">
                <![CDATA[Every developer faces problems that look easy at first but turn into hours of debugging, research, and experimentation. Sometimes it’s a frustrating bug, sometimes it’s understanding a new framework, improving application performance, fixing an unexpected edge case, or simply figuring out why something refuses to work.

But these challenges often become the experiences that help us grow the most.

So, let’s discuss:

What’s one coding challenge you’ve faced that genuinely improved your development skills?

What were you working on, and what made the problem difficult? How did you approach it? Did you rely on documentation, Stack Overflow, GitHub, AI tools, your teammates, or good old-fashioned trial and error?

More importantly, what did you learn from the experience?

Whether you’re a beginner who recently solved your first major bug or an experienced developer who has dealt with complex production issues, your experience could help someone else facing a similar problem.

Share your story, solution, or lesson in the comments. Let’s make this a useful discussion for developers to learn from each other.

This is the kind of practical knowledge and developer conversation we love building around at Burj Code.]]>
            </summary>
                                    <updated>2026-09-13T03:31:53+00:00</updated>
        </entry>
            <entry>
            <title><![CDATA[I built an open-source native macOS app to manage Laravel de]]></title>
            <link rel="alternate" href="https://laravel.io/index.php/forum/i-built-an-open-source-native-macos-app-to-manage-laravel-de" />
            <id>https://laravel.io/index.php/30881</id>
            <author>
                <name><![CDATA[Luca Becchetti]]></name>
            </author>
            <summary type="html">
                <![CDATA[I work on multiple Laravel projects every day, and I got tired of keeping several terminal tabs open just to run artisbetan serve, queues, Horizon, Vite, Reverb, Sail, and everything else.

So I started building LaraDeck.

It automatically detects Laravel projects and lets you start, stop, and monitor their development services from a native macOS interface.

It’s still very early and completely open source.

I’m looking for Laravel developers on macOS who are willing to try it, break things, and tell me what sucks.

👉 https://laradeck.brokenice.it]]>
            </summary>
                                    <updated>2026-09-13T03:31:53+00:00</updated>
        </entry>
            <entry>
            <title><![CDATA[AI Agents as Teammates in Laravel Projects]]></title>
            <link rel="alternate" href="https://laravel.io/index.php/forum/ai-agents-as-teammates-in-laravel-projects" />
            <id>https://laravel.io/index.php/30880</id>
            <author>
                <name><![CDATA[luc]]></name>
            </author>
            <summary type="html">
                <![CDATA[AI agents are becoming part of Laravel development, but I’m curious how teams are managing them alongside human developers.

I’ve been exploring **Sharkly**, a project management platform where AI agents can be part of the same workflow as human teammates.

Instead of treating agents as separate tools, they can participate directly in tasks and projects.

Would you see value in having AI agents work alongside your Laravel team?]]>
            </summary>
                                    <updated>2026-09-13T03:31:53+00:00</updated>
        </entry>
            <entry>
            <title><![CDATA[How to Ensure Your Laravel APIs Follow OpenAPI Standards?]]></title>
            <link rel="alternate" href="https://laravel.io/index.php/forum/how-to-ensure-your-laravel-apis-follow-openapi-standards" />
            <id>https://laravel.io/index.php/30878</id>
            <author>
                <name><![CDATA[luc]]></name>
            </author>
            <summary type="html">
                <![CDATA[For Laravel APIs, it’s easy for the implementation and OpenAPI definition to drift apart as the project grows.

I’ve been looking at ways to catch this earlier instead of relying only on code reviews and manual testing.

One approach I found interesting is **Apidog’s Endpoint Compliance Check**, which can validate endpoints against defined API standards.

Combined with API testing and documentation checks, it gives teams a way to catch inconsistencies before they reach production.

For Laravel developers, how do you currently keep your API implementation and OpenAPI documentation in sync?]]>
            </summary>
                                    <updated>2026-09-13T03:31:53+00:00</updated>
        </entry>
            <entry>
            <title><![CDATA[API Governance Tool for Laravel: Keeping OpenAPI, Tests and]]></title>
            <link rel="alternate" href="https://laravel.io/index.php/forum/api-governance-tool-for-laravel-keeping-openapi-tests-and" />
            <id>https://laravel.io/index.php/30875</id>
            <author>
                <name><![CDATA[luc]]></name>
            </author>
            <summary type="html">
                <![CDATA[I've been working with Laravel APIs and one problem keeps coming up as projects get larger: keeping the API implementation, tests and documentation consistent.

Laravel makes it easy to build and test APIs, but there are still several things that can drift over time:

OpenAPI definitions becoming outdated
Missing endpoint documentation
Inconsistent response structures
Breaking changes going unnoticed
Authentication requirements changing
Exposed API secrets
Different teams following different API conventions

I've been testing Apidog as an API Governance Tool to see how much of this can be handled before an API reaches production.

What I found interesting is that it combines API design, testing and governance, with features such as:

Endpoint Compliance Check for enforcing API standards
API Documentation Completeness Check for finding incomplete documentation
Secret Scanner for detecting exposed credentials
RBAC for managing team access
Audit Logs for tracking changes

For a Laravel API, I'm thinking about a workflow like:

Laravel → OpenAPI → Apidog governance checks → API tests → CI/CD → production

This seems particularly useful when several developers are working on the same API and simply relying on code review isn't enough to keep everything consistent.

I'm curious how other Laravel developers handle this.

Do you rely on PHPUnit/Pest + OpenAPI tooling, custom CI rules, or a dedicated API governance tool?

And how do you currently detect when your Laravel implementation and OpenAPI documentation start drifting apart?]]>
            </summary>
                                    <updated>2026-09-13T03:31:53+00:00</updated>
        </entry>
            <entry>
            <title><![CDATA[Top 10 On-Premises API Testing Platforms Like Postman for La]]></title>
            <link rel="alternate" href="https://laravel.io/index.php/forum/top-10-on-premises-api-testing-platforms-like-postman-for-la" />
            <id>https://laravel.io/index.php/30877</id>
            <author>
                <name><![CDATA[luc]]></name>
            </author>
            <summary type="html">
                <![CDATA[Laravel makes API development and testing relatively straightforward. But when a Laravel application is used inside an enterprise environment, the question isn't only how to test an endpoint.

It's also about where API data, credentials, environments, and testing workflows are managed.

For teams working with private infrastructure, sensitive data, or strict security requirements, an on-premises API testing platform like Postman can be worth considering.

Here are 10 options and approaches I'd look at.

1. Apidog

Best overall for enterprise Laravel API development

Apidog would be my first option for teams looking for an on-premises API testing platform like Postman.

It goes beyond request testing by combining:

API design
API testing
Automated testing
Documentation
Mocking
Collaboration
Environment management
Enterprise access control

Apidog also provides on-premises and self-hosting options, which makes it interesting for Laravel applications that need to remain inside private infrastructure.

A possible Laravel workflow would be:

Laravel API → OpenAPI → Apidog → API testing → CI/CD → production

Best for: teams that want API testing and the broader API lifecycle in one platform.

2. Bruno

Best for Git-native Laravel teams

Bruno's local-first approach can work particularly well for Laravel developers who already keep API definitions and development workflows in Git.

Best for: teams that want API collections managed alongside their code.

3. Hoppscotch

Best open-source self-hosted option

Hoppscotch provides a browser-based API client with a self-hosting option.

Best for: teams looking for an open-source API testing environment.

4. Insomnia

Best for local desktop API development

Insomnia provides a desktop workflow for REST, GraphQL and other API development tasks.

Best for: developers who prefer a dedicated desktop API client.

5. Katalon

Best for broader QA automation

Katalon can be useful when API testing needs to be part of a larger web, mobile, and API automation strategy.

Best for: QA teams managing several testing types.

6. SoapUI

Best for REST and SOAP

SoapUI remains useful when a Laravel application needs to interact with legacy SOAP services as well as REST APIs.

Best for: mixed REST/SOAP environments.

7. SwaggerHub

Best for OpenAPI-focused teams

SwaggerHub can be useful when OpenAPI specifications are central to API design, documentation, and collaboration.

Laravel teams using OpenAPI as their API contract may find this workflow useful.

Best for: OpenAPI-centric teams.

8. Kong

Best for API gateway environments

Kong isn't a direct Postman replacement, but it becomes relevant when API testing is part of a larger API gateway architecture.

Best for: teams that need runtime API management alongside testing.

9. Laravel + PHPUnit/Pest + CI/CD

Best for teams that prefer native Laravel testing

Laravel already provides strong testing capabilities through PHPUnit and Pest.

A team can combine those tests with OpenAPI validation and CI/CD to build a completely internal API testing workflow.

Best for: Laravel teams that prefer code-first testing.

10. Custom Self-Hosted API Testing Stack

Best for specialized enterprise requirements

Some organizations combine OpenAPI, automated tests, CI/CD, security scanning, and custom tooling.

This provides maximum control but also means the team is responsible for maintaining the entire stack.

Best for: organizations with highly specialized infrastructure requirements.

Quick Comparison
Tool / approach	Self-hosted	API testing	OpenAPI	Automation	Best for
Apidog	Yes	Yes	Yes	Yes	Enterprise Laravel
Bruno	Local-first	Yes	Yes	Yes	Git workflows
Hoppscotch	Yes	Yes	Yes	Yes	Open-source
Insomnia	Local	Yes	Yes	Yes	Desktop testing
Katalon	Enterprise	Yes	Yes	Yes	QA automation
SoapUI	Yes	Yes	Yes	Yes	REST/SOAP
SwaggerHub	Enterprise	Yes	Yes	Yes	OpenAPI
Kong	Enterprise	Yes	Yes	Yes	API gateway
PHPUnit/Pest	Yes	Yes	Depends	Yes	Laravel-native testing
Custom stack	Yes	Yes	Depends	Yes	Specialized teams
What I'd Look At Before Choosing

For a Laravel API, I'd evaluate more than the request builder.

Infrastructure control: Where are API definitions, environments and test data stored?

Security: How are credentials and sensitive API information handled?

OpenAPI support: Can the API contract be shared between development, documentation and testing?

Automation: Can tests run in CI/CD?

Collaboration: Can developers and QA engineers work on the same API projects?

Deployment: Can the platform run inside the organization's own infrastructure?

My Pick

If you're just testing a local Laravel endpoint, PHPUnit, Pest, curl, or a lightweight API client may be all you need.

But if you're looking for an on-premises API testing platform like Postman for an enterprise Laravel environment, I'd put Apidog at the top because it combines API testing with design, documentation, mocking, collaboration, and enterprise deployment options.

The interesting question isn't simply:

"What's the best Postman alternative?"

It's:

"How much control do we need over our API testing infrastructure?"

For some Laravel projects, the answer will be a local test suite.

For others, a self-hosted API platform may make more sense.

What are you using today for Laravel API testing when cloud-based tooling isn't an option?]]>
            </summary>
                                    <updated>2026-09-13T03:31:53+00:00</updated>
        </entry>
            <entry>
            <title><![CDATA[Laravel After Deploy book is out]]></title>
            <link rel="alternate" href="https://laravel.io/index.php/forum/laravel-after-deploy-book-is-out" />
            <id>https://laravel.io/index.php/30876</id>
            <author>
                <name><![CDATA[milon]]></name>
            </author>
            <summary type="html">
                <![CDATA[Eleven years ago I wrote my first book, on Laravel. It did well: two editions, and the copies sold quickly. The years since have not been a straight line. I left Bangladesh, spent five years in Europe, and have now been in Canada for a little over three and a half years, working at companies of every size.

Whenever a colleague found that first book on my LinkedIn profile, they asked if they could read it. They could not. It was written in Bengali, against Laravel 5, for beginners, and it has been out of date for a long time.

The first book was for people just starting. This one is for mid-to-senior engineers. Building a Laravel application is the easy part. The hard part starts after deploy, which is also where most books and tutorials stop. This book starts there.

There are 46 chapters. Almost every one opens with a real production incident, then explains why it happened and how you recover from it. I was there for each of them, on my own team or a sister team, and I worked on the recovery. Company names are changed. I folded the incidents into a handful of fictional companies and kept those names consistent, so a system you meet in one chapter is still that system later in the book. Not every incident happened on a Laravel app. The examples are Laravel. The problems are not. If you can read PHP, you can take the patterns home.

The book is **Laravel After Deploy: Architecture, Performance, and Operations at Scale**. 46 chapters, 736 pages, eight parts. The first two parts are the foundation the rest of the book assumes. After that, most parts stand on their own.

The free sample has the front matter and three full chapters: Chapter 9 on schema evolution, Chapter 16 on rate limiting, and Chapter 25 on datetime and timezones.

I learned from the first book that this is not how you make money. The time that went into this one would have paid better as consulting. I took a lot from this community, and this is what I can put back. Kindle, PDF, and EPUB are $12.99. The paperback is $44.99, because printing 736 pages is expensive. I thought about giving it away. In my experience, a free book does not get read. So the digital price is a floor, not a target. The first 100 PDF or EPUB purchases get 15% off with the code `LAUNCH15` at checkout.

Site (sample is on the page): [https://laravel-after-deploy.milon.im](https://laravel-after-deploy.milon.im) 

Amazon: [https://mybook.to/laravel-after-deploy](https://mybook.to/laravel-after-deploy) 

PDF and EPUB: [https://store.milon.im/laravel-after-deploy](https://store.milon.im/laravel-after-deploy)]]>
            </summary>
                                    <updated>2026-09-13T03:31:53+00:00</updated>
        </entry>
    </feed>
