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**Are you ready to take your PHP development skills to the next level for AI automation? Neuron v2, the foundation of AI workflow development in PHP, is here to revolutionize your workflow and boost your productivity.**
1. **Upgrade guide**
– Learn about the latest changes and how they impact your PHP application upgrading to Neuron v2.
– Bookmark the Upgrade guide on the documentation to understand the latest changes and how they impact your implementation.
– **What Changes in Neuron V2**
– Simplifies the workflow by eliminating the Edge class and introduces an event-driven architecture that supports complex agentic systems.
– Streamlining real-time streaming with multi-agent systems by enabling seamless human-in-the-loop without complexity.
– Enhances human-in-the-loop functionality with seamless interruption handling and providing external data for resuming workflows.
– **Human-in-the-Loop Without Complexity**
– Provides a seamless user experience by pausing execution, requesting human input, and resuming with minimal complexity.
– **Performance at the Foundation**
– Optimizes performance by automatically chunking data, file access using generators, and the strong type system.
– Improves developer experience with the Neuron CLI tool
Since the beginning of my journey building Neuron I challenged myself with a simple question: “Is PHP ready for agentic application development?”
For months, developers have been asking whether they need to switch to Python to build production-grade AI systems, or if they can leverage their existing PHP expertise. More and more discussions have been posted in the forum about coordinating multiple agents or how to implement complex scenarios.
Neuron v2 provides a definitive answer. This release fundamentally changes how PHP developers can approach complex AI workflows, introducing an event-driven architecture that makes building sophisticated agentic systems both practical and performant.
If you are curious about the beginning of this journey you can read the article of the first launch:
https://inspector.dev/introduction-to-neuron-ai-create-full-featured-ai-agents-in-php/
Upgrade guide
Before moving forward you can bookmark the Upgrade guide on the documentation to learn more about the latest changes, and how they impact your application upgrading your implementations to V2: https://docs.neuron-ai.dev/overview/readme/upgrade-guide
What Changes in Neuron V2
Aside from removing “AI” from the name, the core advancement in v2 centers around a complete rearchitecture of the Workflow system. In v1 Workflow was marked as experimental. The previous implementation relied on a combination of nodes and edges to define the path workflow must follow to navigate through nodes. V2 introduces an event-driven model that uses only nodes as entities that handle incoming events and emit other events.
namespace App\Neuron;
use NeuronAI\Workflow\Node;
use NeuronAI\Workflow\StartEvent;
use NeuronAI\Workflow\WorkflowState;
class InitialOne extends Node
{
public function __invoke(StartEvent $event, WorkflowState $state): FirstEvent
{
$state->set('node_one_executed', true);
return new FirstEvent('First complete');
}
}
This shift eliminates the Edge class entirely and opens up possibilities that weren’t feasible with the graph-like workflows. Nodes now trigger and respond to events, creating dynamic execution paths based on runtime conditions rather than predetermined sequences. It’s very easy now to create and maintain workflows with loops and braches. Here is an example:
https://docs.neuron-ai.dev/workflow/loops-and-branches
Real-Time Streaming in multi-agent systems
The most immediate impact developers can notice is streaming capability. V2 workflows can stream intermediate results to clients in real-time, transforming user experience from “loading…” states to live progress updates even in multi-agent systems.
$workflow = new Workflow();
$workflow->addNodes([
new NodeOne(),
new NodeTwo(),
new NodeForSecond(),
]);
// Draw the workflow graph
echo $workflow->export()."\n\n\n";
$handler = $workflow->start();
foreach ($handler->streamEvents() as $event) {
if ($event instanceof ProgressEvent) {
echo "\n- {$event->message} \n";
}
}
$finalState = $handler->getResult();
// It should print "Second complete"
echo $finalState->get('final_second_message');
Check out this example: https://github.com/inspector-apm/neuron-ai/blob/2.x/examples/workflow/workflow-stream.php
This streaming architecture means users see planning complete, watch research queries execute, and observe content generation happen step by step. For applications where users need to understand what the AI system is doing, this visibility builds confidence in the process.
Human-in-the-Loop Without Complexity
One of the most practical features v2 reinforced is seamless human intervention. Workflows can pause execution, request human input, and resume exactly where they stopped. This capability makes AI systems viable for sensitive business processes where human oversight is required.
$persistence = new FilePersistence(__DIR__);
$workflow = Workflow::make(new WorkflowState(), $persistence, 'test_workflow')
->addNodes([
new NodeOne(),
new InterruptableNode(),
new NodeForSecond(),
]);
// Draw the workflow graph
echo $workflow->export()."\n\n\n";
// Run the workflow and catch the interruption
try {
$finalState = $workflow->start()->getResult();
} catch (WorkflowInterrupt $interrupt) {
// Verify interrupt was saved
$savedInterrupt = $persistence->load('test_workflow');
echo "Workflow interrupted at ".$savedInterrupt->getCurrentNode()::class;
}
// Resume the workflow providing external data
$finalState = $workflow->start(true, 'approved')->getResult();
// It should print "approved"
echo $finalState->get('received_feedback');
Check out this example: https://github.com/inspector-apm/neuron-ai/blob/2.x/examples/workflow/workflow-interrupt.php
The workflow state persists during these pauses, meaning the system can wait hours or days for human feedback before continuing. This persistence enables complex approval processes that span multiple stakeholders and time zones.
Performance at the Foundation
Under the hood, v2 addresses performance from the ground up. Large dataset iterations automatically chunk data, file access uses generators for better performance and memory management, and the strong type system helps PHP’s engine optimize reference lookups.
These optimizations aren’t visible in the API but it makes PHP applications handling large AI workloads with easy.
Neuron CLI – Enhanced Developer Tools
V2 ships with practical developer experience improvements that address common friction points. The CLI tool brings the new “make” command that helps you scaffold common classes reducing boilerplate fatigue:
php vendor/bin/neuron make:agent App\\Neuron\\MyAgent
php vendor/bin/neuron make:rag App\\Neuron\\MyChatBot
php vendor/bin/neuron make:workflow App\\Neuron\\MyWorkflow
Seeing It in Action – Deep Research Agent
The deep-research-agent demo project demonstrates these capabilities in practice. This implementation creates comprehensive research reports by orchestrating multiple AI services through an event-driven workflow that includes planning, research, content generation, and formatting phases.
The demo shows how complex agentic workflows can remain readable and maintainable while handling real-world requirements like API calls, result aggregation, and structured output formatting. Developers can examine the complete workflow implementation and see how each node contributes to the overall process.
Check out the GitHub repository >> https://github.com/neuron-core/deep-research-agent
Is PHP Ready For Agentic Application Development?
The release of Neuron V2 makes me feel one step closer toward answering whether PHP is ready for serious agentic application development. The event-driven architecture, streaming capabilities, and production-focused performance optimizations create a foundation for building AI systems that can compete with implementations in other languages.
For teams with substantial PHP expertise, v2 removes the primary arguments for switching to Python for AI development. Complex agentic workflows are now feasible within the PHP ecosystem, using familiar patterns and deployment infrastructure.
The framework maintains a general backward compatibility while introducing advanced capabilities. Teams can adopt v2 features without requiring full rewrites.
Getting Started With Neuron
The most effective way to understand v2’s capabilities is to experiment with the Deep Research Agent at https://github.com/neuron-core/deep-research-agent. This implementation demonstrates real-world workflow patterns and provides a starting point for building custom agentic systems.
For developers ready to explore how quickly ideas can become working applications, Neuron v2 offers the tools to turn concepts into production-ready AI systems without leaving the PHP ecosystem. The question isn’t whether PHP is ready for agentic development anymore – it’s what you’ll build with it.
Check out the official Neuron Documentation.
