After 6 months of wrestling with deepset-ai/haystack: It’s good for prototypes, painful for anything real.
When I decided to give Haystack a shot, my goal was to integrate a simple search solution into a mid-sized application. We were building a knowledge base feature for a web application servicing around 10,000 users, hitting peak loads of
LangChain in 2026: An Honest Review After a Year of Use
After spending an entire year wrangling with LangChain, I can confidently say that while it has some great features, it also comes with more than its fair share of pain points.
Context
Over the last year, I’ve integrated LangChain into multiple projects ranging from
n8n vs. Make: An In-Depth Look for Side Projects
n8n boasts 180,218 stars on GitHub—a significant number that reflects a passionate community. Make, however, tends to lurk behind with less visibility, despite being a well-known tool in the automation space. Stars don’t give you functionality, though, and deciding between n8n and Make for your side
The Battle of vLLM vs TensorRT-LLM: A Developer’s Perspective
vllm-project/vllm boasts an impressive 73,811 stars on GitHub. In contrast, TensorRT-LLM isn’t quite as popular but has its own following. Depending on your production requirements, the choice between these two can significantly impact your project. To help you make a decision, let’s get into the specifics.
How to Add Vector Search with LangChain (Step by Step)
I’m going to show you how to add vector search functionality using LangChain, a library that’s gaining traction in the AI community. With a staggering 130,274 stars on GitHub, 21,484 forks, and 474 open issues, it’s clearly making waves. This isn’t just a buzzword; vector
After 3 months of working with Microsoft’s Semantic Kernel: it’s useful for quick automations, but you’ll hit walls if you aim for production.
In the ever-expanding field of AI development, the introduction of Microsoft’s Semantic Kernel in 2026 has stirred up quite the conversation. After 3 months of hands-on experience using it for a personal
DSPy vs Semantic Kernel: Which One for Side Projects
As of now, there are a multitude of frameworks and tools available to developers working on AI-related side projects. While many enthusiasts parade around claiming that countless stars on GitHub validate their choice of tech, the truth is statistics can often be misleading. For instance, LangChain
Setting Up Monitoring with Autogen Studio: A Step-by-Step Tutorial
We’re setting up monitoring with Autogen Studio so you can keep an eye on your pipeline, which is crucial for avoiding headaches later on.
Prerequisites
GitHub Copilot vs Cody: Which One for Production?
According to various recent surveys, developers spend an average of 6+ hours a day writing code, with 38% of them saying they face challenges due to repetitive tasks. With that much time on the line, tools like GitHub Copilot and Cody aim to enhance productivity by offering
Adding Memory To Your Agent with Pinecone
Memory is vital for any AI agent looking to perform complex tasks effectively, and with Pinecone, enhancing your agent’s memory is straightforward. This detailed tutorial will guide you through how to add memory to your agent using Pinecone, step by step. It’s not just about having a chatty