AI

Agents rely on long-lived workflows, but when happens when they fail midway through? Here are the tools you need to manage correctness and reliability: transactions, idempotency, retries, durable functions, journaling, and state machines. The missing abstraction layer for agentic is durable workflows, which bring them all together.

With this new backend component, augment Agents to automatically save and search message history per-thread, providing realtime results across multiple tabs and users. Use it with the Workflow component to run reliably with retries and durability across server restarts.

I reimplemented Mastra’s agentic workflows with durable functions in Convex, and it was the wrong decision. Look at three common strategies (reimplementation, API wrapping, and “blessed” plugin paths), along with learnings along the way and reflections on what I’d do differently next time. TL;DR: Do less, do it smarter, and prototype faster.

AI coding is here: The most productive developers are leveraging AI to speed up their workflows. This ranges from asking models questions about system design to letting AI take the driver's seat with tools like Cursor Composer.

Convex now supports a powerful MCP server that lets you introspect your deployment's state, run functions, and read and write data.

Coding agents can do more autonomously when they write code that has tight, automatic feedback loops; use systems that express everything in standard, procedural code; and have access to strong, foolproof abstractions.

A step-by-step guild using daily bots open-source real-time voice and video AI cloud technology to build an AI real-time shopping list app—all controlled by voice.

After much experimentation I have found some good ways to improve the coding experience when using Cursor and Convex. In this article I share 6 tips to improve your workflow.

Ever wondered what word sits perfectly between "sporty" and "practical"? Or perhaps "sweet" and "crunchy"? Midpoints is a new word game that gives you 10 chances to find the best match and scores you accordingly!

I was curious to see if I could prompt my way through developing an entire app with Cursor and Claude. It went pretty well - but there are some important caveats to keep in mind.

Learn the basics of HTTP streaming with Convex by re-implementing OpenAI's SDK using built-in fetch and async iterators. No npm dependencies needed.

By leveraging HTTP actions with streaming, this chat app balances real-time responsiveness with efficient bandwidth usage. Users receive character-by-character updates to their own responses directly from ChatGPT, while other users see periodic updates, minimizing database bandwidth.

Implementing "work stealing" - a workload distribution strategy - using Convex's reactive database.

I recently built a full-stack app called notesGPT. It allows you to record a voice note, transcribes it, and extract action items and display them as action items. It’s fully open source and comes equipped with authentication, storage, vector search, action items, and is fully responsive on mobile for ease of use.

Using Convex, 4 web devs built their own fullstack app based on this prompt: > Build a way to show real-time updates on the website for a Dungeons and Dragons-themed small business! See what they built, learn how they did it, and watch their reactions to each other's work in this installment of the "4 Web Devs, 1 App Idea" video series.

This year vector databases have sprung up like mushrooms to enable applications to retrieve context based on semantic search. A large portion of these applications have used the retrieved context to augment the ability of large language models (LLMs) in a pattern known as RAG. On November 7th OpenAI released its Assistants API, enabling the implementation of AI chat interfaces with context retrieval without needing a separate message store or vector database. Does this new API make vector databases obsolete?

Convex is a full-stack development platform and cloud database, including built-in vector search. In this third post in our [series](https://stack.convex.dev/ai-chat-using-openai-assistants-api), we’ll build an AI-powered chat interface using Convex, with our own message storage and context retrieval.

In this second post in our series, we’ll build an AI-powered chat interface using LangChain and its new Convex integration.

On November 7th OpenAI released its Assistants API, enabling chat bot with context retrieval implementations without needing a messages or vector database. In this post, we’ll cover how to leverage this API to build a fully functioning AI chat interface.

It's never been a better time to make your own town of AIs.

Stream GPT responses without brittle browser-based HTTP streaming. Multiplayer reactivity, persistence, reactivity via Convex. Using OpenAI’s Node SDK server-side, and Convex's useQuery hook client-side.

Generating rhyming words via GPT-4, along with Dall-E cartoon images and ElevenLabs speaking with a specific voice to make a game to teach words.

Build a text adventure game with Next.js, Convex, OpenAI, and DALL-E. Full stack walkthrough.

Learn more about how AI Town works and how to customize it. In this post, we'll dig into how character identities are represented: how to alter them, and how to add entirely new characters.

Embeddings, why they’re useful, and how we can store and use them in Convex.

So you have a pretty good grasp on web development, but you want to learn more about building with generative AI? You're not alone. In this live-coding course, follow along as we build a full-stack generative AI app using LangChain.js, Replicate, and OpenAI.

In this post, we’ll look at how to use the moderation API to flag messages before sending them to Chat-GPT, and patterns for handling these errors in a full-stack React app.

How to store multiple personalities Convex and provide them to the chatGPT API, enabling changing personalities mid-conversation. This is a follow-up to Building a full-stack ChatGPT app.

Let's build a full-stack chat app to talk to ChatGPT on its new API!

Use Convex to fetch an image from OpenAI’s image generation service based on a user-provided prompt.