4 posts tagged with "ai"

Most AI projects don't need a fleet of orchestration tools to run a few prompt chains. The real work is state management, retries, scheduling, and simple persistence—the operational glue between LLM API calls.

This post shows you how to build a production-ready text summarization workflow using Codehooks.io, the Workflow API, and OpenAI. You'll learn:

• OpenAI API integration patterns: Error handling, retries, rate limiting, and cost optimization
• Workflow state management: Building reliable multi-step processes with caching and persistence
• Webhook triggers: Event-driven workflows that respond to GitHub issues (and other external services)
• Programmatic access: How to trigger and manage workflows via REST API, CLI, and webhooks

By the end, you'll have a working summarizer that caches results, stores them in a NoSQL database, and can be triggered via REST API or GitHub webhooks—all deployed with a single command.

Here's the workflow we'll build:

Ever notice how some days you're a caffeinated code ninja ready to refactor an entire codebase, while other days you can barely muster the energy to fix a typo? Welcome to the wonderfully human world of vibe coding – and the tools that get it.

ChatGPT, GitHub Copilot, Cursor and other AI tools using Large Language Models (LLMs) can quickly generate a lot of code, but quite often the process is not straightforward and requires many iterations and a skilled developer to get the best results.

In this article we will show how a well-structured prompt can improve the AI-supported development effort.

ChatGPT and other advanced AI language models have become an integral part of the modern development workflow. From GPT-4 to Claude and other competitors, these AI assistants have transformed how we approach coding and content creation. And we understand why! These AI models have proven themselves invaluable for producing all kinds of text and code, helping developers work more efficiently and creatively than ever before.

While modern AI models are now well-versed in a wide range of technologies and frameworks, we've found that providing concrete examples still leads to the best results. This approach helps the AI understand exactly how we want to use codehooks.io's specific features and conventions, ensuring the generated code follows our best practices.