Middleware's core job? Injecting a special 'tool search' tool into the agent's default list. This allows the model to query and retrieve the right tools from a pool to accomplish its tasks.
Full video: youtube.com/watch?v=qYmidHAX…#TechExplained#Middleware
Challenging the assumption that AI belongs only to Python at @phpconference Berlin! 🌐
Great talk, tech discussions, and real networking. We even grabbed a copy of @ezimuel’s new book. 📈
PHP devs can build native, production-grade agentic systems: github.com/neuron-core/neuro…
Unlock powerful AI tools for your agent! The tool search middleware gives your model access to a pool of calendar tools, streamlining tasks by intelligently selecting the right tool for the job.
Full video: youtube.com/watch?v=qYmidHAX…#AITools#DeveloperTips
Best part wasn't the talks. It was seeing how differently everyone's living this shift: some already all-in, some still skeptical.
Same change, very different speeds.
Thanks for having me 🙏
Our Nola roundtable turned into an incredible room of CTOs & Devs proving you don’t need Python for production AI Agents. PHP is ready. ⚡@Barbalerio
Thanks to our sponsors and partner To bee @regolo_ai@asterixcapri@Inspector_rt & all attendees for the energy! 🚀
#PHP#laravel
As a frontend developer, chatbases have been invaluable for programming for years. Now, integrating AI agents like ChatGPT and Neuron is streamlining development, helping build entire pages and applications.
Full video testimonial: youtu.be/kW3RXaNC0LM#AI#FrontendDev
Why hardcode your AI agents to one LLM? 🌐
With Neuron AI’s new decoupled router component, you can dynamically route single inference calls between OpenAI, Anthropic, and Gemini transparently. No stack splitting. 🚀
Read the PHP breakdown:
buff.ly/pe4aBS4#php
Integrating features or developing entire applications? Front-end devs are using AI agents to streamline their work. This event offered valuable insights to accelerate future growth and skill improvement.
Full video testimonial: youtu.be/kW3RXaNC0LM#AIDevelopment#FrontEnd
See the final result of this implementation in action. Running the PHP script to observe the agent's behavior with dynamic tool search. The agent runs and we send it a prompt.
Full video: youtube.com/watch?v=qYmidHAX…#AI#Automation
PHP is no longer just for basic OpenAI wrappers. The ecosystem has evolved into a fully capable stack for Multi-Agent platforms. 🚀
This Medium deep dive maps this architectural shift, highlighting Neuron AI in the production-grade era:
medium.com/@leumas.a/the-ai-…#php#laravel
This tool searches its pool for the right function with a simple query. It tokenizes names and descriptions, then compares your search to available tools, returning an array of matches.
Full video: youtube.com/watch?v=qYmidHAX…#AITools#TechExplained
Our Nola roundtable turned into an incredible room of CTOs & Devs proving you don’t need Python for production AI Agents. PHP is ready. ⚡@Barbalerio
Thanks to our sponsors and partner To bee @regolo_ai@asterixcapri@Inspector_rt & all attendees for the energy! 🚀
#PHP#laravel
Models can now dynamically search for and use tools they don't have by default. This middleware lets them find and run the right capabilities for any task.
Full video: youtube.com/watch?v=qYmidHAX…#AI#Tech
Hardcoding 50 tools into your prompt is an architectural anti-pattern that kills PHP AI Agent performance. 📉
Neuron AI shifts the tool catalog into an on-demand layer via Vector Search to keep costs under control. 🚀
Read: buff.ly/U3WtF6c#php
Building production AI agents in PHP is a matter of software architecture, not microservices. ⚡
Stop forcing LLMs to carry heavy, static tool arrays. We built Neuron AI to run dynamic, vector-driven tool retrieval natively. 📈
Watch the deep dive: buff.ly/yfQo469#php
Hardcoding logic into workflow nodes limits adding new tracking strategies for max run limits. This design forces manual updates, hindering flexible tool enhancements.
Full video: youtube.com/watch?v=LhoOQD2J…#SoftwareDesign#DevTips
How a community PR sparked a core architectural upgrade in Neuron AI 🧠
Our CTO @Barbalerio breaks down how we solved the "infinite tool calling loop" by shifting responsibility directly to the tools. 🛠️
The power of open-source. 🚀
Watch: buff.ly/yN5wQuD
Even with large context windows (200k tokens), models perform best using only 50% of their capacity. Stick to around 30-40k tokens for optimal performance. @nevercodealone
Full video: youtube.com/watch?v=Ta4TO27e…#AI#LLMtips