AI Agents
Open Source and AI: Exploring Langbase State of AI Agents Research
Langbase Founder & CEO Ahmad Awais and GitHub’s Andrea Griffiths unpack findings from the State of AI Agents report.
Thoughts, guides, and updates on languages, learning, and AI. Focused on real strategies that actually work.
Langbase Founder & CEO Ahmad Awais and GitHub’s Andrea Griffiths unpack findings from the State of AI Agents report.
Step-by-step guide to build an AI app that generates concise news headlines by researching and transforming long-form news.
Build a Slack insight agent that connects to your Slack using Langbase SDK
Why the Best AI Agents Are Built Without Frameworks (Primitives over Frameworks) — a talk by Langbase Founder & CEO Ahmad Awais at AI Engineer World's Fair 2025
Explore the strengths, weaknesses, and cost efficiencies of OpenAI o3-mini and DeepSeek-R1 models. Learn which model suits your requirements best.
Explore the top LLM API providers in 2025 — Fireworks AI, Together AI, Groq, Perplexity AI, and Mistral. Compare their strengths and use cases to find the best fit for your AI apps.
Five days. One team. A shared sense of direction.
Google Gemini Flash 1.5 has surpassed OpenAI GPT-4o mini on Langbase, offering a 1M token context window at a lower cost and higher performance.
Understand what is Composable AI and how Langbase is bringing the concept of composition to AI.
Learn the key concepts of Memory in Langbase to build a RAG system. Understand RAG prompt, document processing, chunking, embeddings, and retrieval testing.
Learn the core concepts of Pipes in Langbase to build AI apps. Understand how to create, configure, and run Pipes effectively.
A step-by-step guide to use Vision capabilities by a Vision model using Langbase Pipes. This guide will help you send an image to a Vision model and get it to answer questions about it.
A step-by-step guide to implement RAG using Langbase Pipes and Memory. Build a Documents QnA RAG App.
A step-by-step guide to build a Retrieval-Augmented Generation (RAG) chatbot on your documentation files using Langbase and BaseAI. This will enable you to create an AI question-answer chatbot on your docs with very low hallucination.
A step-by-step guide to build a Video Wisdom Extraction Tool using Langbase SDK. This tool extracts wisdom from YouTube videos and answers questions related to the video content.
Learn how to build an AI email agent using Langbase SDK. This guide covers sentiment analysis, summarization, decision making, and email response generation.
A step-by-step guide to build an AI coding agent called CodeAlchemist aka Devin using Langbase SDK. It uses multiple AI Pipes to analyze user prompt and generate code or SQL queries.
A step-by-step guide to replace an existing document in Memory using the Langbase API. This is useful when you need to update the content of a file that is already stored in a memory.
A step-by-step guide to insert raw text into Memory using the Langbase API. This way you can turn your text into a file and store it in Memory for RAG.
A step-by-step explanation to understand how RAG works. Learn how to implement RAG with Langbase.
Learn how Langbase Pipes and Netlify bring back the nostalgic GeoCities experience, powered by modern AI and LLMs.
"Langbase is transforming the AI market. Easy to use, handy integrations, and serverless AI agents infra. What else could we ask for."
What developers and founders are saying about Langbase.
“The real breakthrough here is how easily we can test RAG via Langbase memory agents—actually seeing which chunks get retrieved for specific queries. That kind of visibility just isn't available with other providers. Typically, you'd need specialized vendor knowledge, framework-centric coding, or custom actions to get the same result. But with Langbase, there's next to no overhead or prior expertise needed. The straightforward setup, developer experience, collab features, and built-in version control instantly give it a huge plus for anyone building AI-driven apps. Langbase basically turned me into an Al engineer overnight.”
"Ahmad is uniquely positioned to dramatically improve the AI developer experience.He has done exactly that with Langbase, building on his deep expertise creating products for developers"
"LLM's are redefining the meaning of an application andLangbase is the Vercel of AI that supercharges every developer & company's efforts in building for this new wave."
"Langbase AI serverless dev experience is powerful and unique, truly designed to meet the needs of developers building and operating LLM apps."
"Langbase lets us manage all our LLM-related infrastructure in one place, quick-iteration, actionable analytics, version controlled prompts, and rapid testing of different LLM models. Read more in FQ's customer story."
"Really impressed with Langbase (we use at Ignition) - it's one of the most "need to have" tools i've seen in the past decade. AI is moving so quickly so a serverless composable infra to mix / match / test / deploy new models as they are released is the fastest way for an org to stay on the bleeding edge without vendor lock-in. Seeinghow excited my team has been using Langbase.Langbase is simplifying the complexity of it all."
"Langbase is unique for its composable serverless AI cloud that just works . Makes AI dev dead simple for everyone, not just the ML experts. I believe an AI Pipe is the easiest way to build AI features you can actually use.Build, ship, and innovate with zero-config, making ship happen."
"Langbase is transforming AI development with serverless AI agents infrastructure, making it easy for any developer to build, collaborate, and deploy AI apps. Think Docker containers, but for AI agents! Proud to have supported them from the beginning."
Build, test, & deploy in minutes. Scale your agents instantly, with built-in
memory and tooling.