Markdown is the easy part
Mintlify might look like a Markdown hosting service from the outside. But the build versus buy question for content infrastructure goes much deeper than rendering Markdown.
Mintlify Blog6 min read
Model Context Protocol
2,194 stories
Hexabot vs n8n for AI Workflow Automation: Which One Should You Use?
Compare Hexabot and n8n for AI automation, agentic workflows, chatbots, integrations, self-hosting, memory, extensibility, and production use cases.
Hexabot Blog13 min read
OpenAI frontier models and Codex are now available on AWS
OpenAI frontier models and Codex are now available on AWS. Learn what this means for enterprise AI adoption, Amazon Bedrock, and production workflows.
Hexabot Blog12 min read
Radar OSS or Radar Cloud? An Honest Take on When to Use Each
The most common question in our GitHub issues: do I need Radar Cloud, or is OSS enough? Here's the honest answer, with the five questions that actually decide it.
Radar Blog8 min read
Designing a CLI for AI agents
How we designed the Arcjet CLI in Go as a stable, defensive interface for humans and AI agents: predictable commands, machine-readable output, strict validation, and confirmation before production changes.
Arcjet Blog11 min read
Headless or Headed
A perspective on software as interfaces and underlying capabilities, and why MCP apps change how businesses reach customers through AI agents.
Noodle Seed Blog8 min read
Paste MCP: Turn clipboard history into context for AI tools
Connect Paste to Claude, Codex, or other AI tools, then use clipboard history as context without leaving your AI tool.
Paste Blog5 min read
DigitalOcean Serverless Inference: A Deep Dive
A deep dive into DigitalOcean Serverless Inference—how we built a scalable, API-first AI inference platform and the architecture powering it.
DigitalOcean Blog16 min readThe Whole Platform Is Now Open Source: LangWatch May 2026 Update
LangWatch is now open source under Apache 2.0. Plus native voice testing in Scenario, the GA Traces UI, and the new AI Governance beta. See what shipped in May 2026.
LangWatch Blog4 min read
How MCP is Changing The Way Product Teams Work With AI
MCP became the default way AI agents connect to external data in 2025. In 2026, it’s quietly rewriting how product orgs make decisions. Here’s what’s actually happening, and what engineering leaders should be building toward.
Bagel AI Blog12 min read
What is an Autonomous Product Decision Layer? A Guide for AI-Native Teams
Product teams are surrounded by AI tools that don’t share context. The autonomous product decision layer is the architecture that fixes that, and it’s how AI-native orgs ship the right thing at scale. What is an autonomous product decision layer?
Bagel AI Blog15 min read
How to Set Up a New Hexabot Project: From Zero to Your First AI Automation Workspace
Learn how to create and run a new Hexabot project. Set up your AI workflow automation workspace with local development, MCP, and AI coding agents.
Hexabot Blog9 min read
Hexabot v3 Is Here: From Chatbot Builder to Agentic AI Workflow Automation Platform
Discover how Hexabot is evolving from a chatbot builder into a self-hosted AI automation platform for building agentic workflows across channels.
Hexabot Blog7 min read
Stateless MCP and the Economics of AI Commerce
On July 28, a single architectural change turns ChatGPT and Claude integrations from clever developer demos into enterprise-scale infrastructure.
Noodle Seed Blog5 min read
21 Best Social Listening Tools in 2026 (Compared)
We compared 21 social listening tools side by side — G2 ratings, real pricing, platform coverage, and what actual users say about each one.
Octolens Blog24 min read
A year of openstatus: what we learned
A year after our Reality Check post: what we shipped, what we killed, what we got wrong, and the people who helped us see what we couldn't. The honest receipt — positioning, design, distribution, ~8× the Google impression rate, and a defensible wedge.
OpenStatus Blog21 min read
Announcement: Deterministic PR Refactoring Agents
CodeScene’s new PR Refactoring Agent analyzes the branch using deterministic Code Health data, performs targeted refactorings, and commits improvements back to the PR. The result is code that’s easier to review, AI-friendly, and more token efficient.
CodeHealth MCP Server by CodeScene Blog4 min read
Unhealthy Code is Burning Your Token Usage - Here's the Data
Our research across C++, Java, and Python shows that agents working on unhealthy codebases consume 35-45% more tokens to complete the same tasks. That’s in addition to the increased defect risk covered in earlier research. You're not just getting worse output.
CodeHealth MCP Server by CodeScene Blog5 min read
Showing 1,926 of 2,194 stories
Load more storiesAiByts Weekly Brief
Get the top AI news and tools straight to your inbox every week.
Weekly · AI news
Join 15,000+ AI enthusiasts