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AI · alternatives · 2026

24 alternatives to Principles of Building AI Agents book [pdf]

Hi, I’m Sam, the cofounder/CEO of Mastra, the Typescript agent framework. I wrote a book on building agents and wanted to share it with HN. The book is called Principles of Building AI Agents. Right now it has 34 chapters and 148 pages covering LLMs, prompting, agents, workflows, RAG, evals, multi-agent, tracing, deployment, MCP, tool use, and a few other topics. The backstory here is that last October when we started working on Mastra we knew very little about AI engineering, and had to learn as we were building. In January, we started going to local AI meetups. We met a lot of people…

Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.

  1. 1

    Hi HN, we’re Sam, Shane, and Abhi, and we’re building Mastra (https://mastra.ai), an open-source JavaScript SDK for building agents on top of Vercel’s AI SDK. You can start a Mastra project with `npm create mastra` and create workflow graphs that can suspend/resume, build a RAG pipeline and write evals, give agents memory, create multi-agent workflows, and view it all in a local playground. Previously, we built Gatsby, the open-source React web framework. Later, we worked on an AI-powered CRM but it felt like we were having to roll all the AI bits (agentic workflows, evals,…

    Jan 2026 · github.com · its alternatives →

  2. 2

    Build AI agents that respond with UI instead of text

    Feb 2026 · thesys.dev · its alternatives →

  3. 3

    Build AI agents. Share org-wide. 100+ Tools&MCP

    2025 · docs.zencoder.ai · its alternatives →

  4. 4

    Hello HN! The day has finally come to stop adding features and start sharing what I've been building the last 5-6 months. It's a bit of CrewAI, OpenDevon, LangFuse/Cloud all in one, providing devs who prefer TypeScript an integrated framework thats provides a lot out of the box to start experimenting and building agents with. It started after peeking at the LangChain docs a few times and never liking the example code. I began experimenting with automating a simple Jira request from the engineering team to add an index to one of our Google Spanner databases (for context I'm the…

    2024 · github.com · its alternatives →

  5. 5

    Hey HN, I spent my xmas break building an agent framework called mcp-agent [1](https://github.com/lastmile-ai/mcp-agent) for Model Context Protocol [2]. It makes it easy to build AI apps with MCP servers, and implements every pattern from the popular Building Effective Agents blog [3] as well as OpenAI’s Swarm [4]. I’m sharing it early to get community feedback on where to take it from here, and to ask for contributions. For those who aren’t familiar with MCP, I think of it as a standardized interface to let AI communicate with software via tool calls, resources and…

    2025 · github.com · its alternatives →

  6. 6

    Hey HN, Gabe and Alexander here from Hatchet. Today we're releasing Pickaxe, a Typescript library to build AI agents which are scalable and fault-tolerant. Here's a demo: https://github.com/user-attachments/assets/b28fc406-f501-442... Pickaxe provides a simple set of primitives for building agents which can automatically checkpoint their state and suspend or resume processing (also known as durable execution) while waiting for external events (like a human in the loop). The library is based on common patterns we've seen when helping Hatchet users run millions of…

    2025 · github.com · its alternatives →

  7. 7

    A collection of open-source TypeScript tools by @enmanuelmag. heimdall-mcp for MCP proxy telemetry. agent-harness-kit for multi-agent orchestration.

    May 2026 · ahk.cardor.dev · its alternatives →

  8. 8

    Enable LLMs to Program Themselves. Contribute to Osly-AI/Pocket-Flow-Framework development by creating an account on GitHub.

    2025 · github.com · its alternatives →

  9. 9

    Single-agent LLMs suck at long-running complex tasks. We’ve open-sourced a multi-agent orchestrator that we’ve been using to handle long-running LLM tasks. We found that single LLM agents tend to stall, loop, or generate non-compiling code, so we built a harness for agents to coordinate over shared context while work is in progress. How it works: 1. Orchestrator agent that manages task decomposition 2. Sub-agents for parallel work 3. Subscriptions to task state and progress 4. Real-time sharing of intermediate discoveries between agents We tested this on a Putnam-level math problem, but the…

    Feb 2026 · github.com · its alternatives →

  10. 10

    Hello! Introducing geniusrise, an agent framework and component ecosystem for building AI agent networks that are as flexible as your team. landing page: https://geniusrise.ai (fancy but useless) docs: https://docs.geniusrise.ai (please check this out) github: https://github.com/geniusrise (for dear devs) ## Thought process Since the ChatGPT disruption, I've been pondering on what the tooling layer is going to look like for building LLM-interfacing agents. Saw a plethora of tools coming out as we witness here every week. I'd broadly categorize them into the…

    2023 · github.com · its alternatives →

  11. 11

    Hi HN! Sean from MindStudio here. I wanted to share something we've been working on that I think introduces some new ideas into the "AI coding agent" space. Remy is an AI agent that builds full-stack TypeScript apps from a spec written in a new flavor of annotated markdown. The spec has two layers: prose describing what the app does, and annotations that carry the technical precision (data types, edge cases, validation rules, code snippets). The agent then "compiles" this into code: backend methods, typed schemas, frontends, test scenarios, and everything else are derived artifacts of the…

    Apr 2026 · remy.msagent.ai · its alternatives →

  12. 12

    Hey HN, I've made a groundbreaking discovery: procrastination can lead to questionable projects! While avoiding real work, I somehow created a directory of 130+ AI agents and frameworks. It's like I tried to organize a robot party and everyone showed up. What's inside: - A list of AI agents - Frameworks to build more agents So, HN, before I spiral into an existential crisis: did I accidentally create something useful, or should I go touch grass? P.S. If this somehow becomes the next big thing, I promise to pretend it was intentional all along.

    2024 · aiagentsdirectory.com · its alternatives →

  13. 13

    Well, I wouldn't call it a framework, but rather an easy way to define tools and agents, allowing the agent to think and do the work. - Currently supports Open AI, and DeepSeek models. I tried building an HN title recommender agent with this framework that analyzes top-performing posts on HN and suggests titles for HN posts. And this was the agent's reply after inspecting 10 best posts: Having analyzed the top 10 performing posts on Hacker News, we've observed that successful titles are often concise, intriguing, and sometimes provocative or impactful. They tend to evoke curiosity, highlight…

    2025 · github.com · its alternatives →

  14. 14IM

    Hey HN, I’m Chris, a solo dev in Melbourne AU. For the past month I've been spending my after work hours building AgentVisa. I'm both excited (and admittedly nervous) to be sharing it with you all today. I've been spending a lot of time thinking about the future of AI agents and the more I experimented, the more I realized I was building on a fragile foundation. How do we build trust into these systems? How do we know what our agents are doing, and who gave them permission? My long-term vision is to give developers an "Agent Atlas" - a clear map of their agentic workforce, showing where…

    2025 · agentvisa.dev · its alternatives →

  15. 15

    I built a browser-only studio for designing and orchestrating MCP agent systems for development and experimental purposes. The whole stack — tool authoring, multi-agent orchestration, RAG, code execution — runs from a single static HTML file via WebAssembly. No backend. The bet: WASM is a hard sandbox for free. When you generate tools with an LLM (or write them by hand), the studio AST-validates the source, registers it lazily, and JIT-compiles into Pyodide on first call. SQL tools run in DuckDB-WASM in a Web Worker. The built-in RAG uses Xenova/all-MiniLM-L6-v2 via Transformers.js for…

    Apr 2026 · agentmcp.studio · its alternatives →

  16. 16

    we had hundreds of discussions with engineering leaders over the past few months, and everyone's trying to understand where they are in the AI journey. we collected all this data into a benchmark and built a free grader to let you know where you stand. you answer on a 1–5 scale (e.g., autonomy runs from "suggestions only" to "agents own multi-hour workflows across code, infra, and external systems") - takes about 5 minutes. https://agent-benchmarks.com/software-factory/ waiting for your results!

    Jul 2026 · agent-benchmarks.com · its alternatives →

  17. 17

    I’ve been building LLM tooling for a small VC fund and found myself explaining the same mental model over and over to non-technical people around me: how a stateless LLM becomes a chatbot, how tool use works, what an agent is mechanically, and why context windows shape all of it. I never found a guide that covered that full chain at the level I wanted, so I wrote one. It’s nine short chapters, each building on the last. Deliberately simplified: the goal is a useful mental model, not a textbook. Feedback, corrections, and contributions welcome: github.com/ymyke/aiaiai

    Apr 2026 · aiaiai.guide · its alternatives →

  18. 18

    Hi HN, I wrote a book on the Model Context Protocol (MCP) – the open standard from Anthropic that lets AI agents connect to external tools and data sources. I'm an RPA/automation practitioner (CEO of Niuexa, LinkedIn Learning instructor) and I noticed there was no comprehensive resource covering MCP architecture, security patterns, and enterprise deployment strategy. So I wrote one. The book covers: - MCP architecture deep dive (servers, clients, hosts, transport layers) - 20-point security checklist for MCP deployments - EU AI Act compliance for agentic systems - Real-world breach…

    Nov 2025 · blueprint-mcp.railsblueprint.com · its alternatives →

  19. 19

    Hi HN, Over Thanksgiving weekend I wanted to build an AI agent. As a design exercise, I wrote it as a set of React components. The component model made it easier to reason about the moving parts, composability was straightforward (e.g., reusing agents/tools), and hooks/state felt like a reasonable way to model behavior that changes over time. As I kept experimenting, I realized I was more interested in the framework (and it was a good excuse to explore React’s internals) than in the agent I originally planned, so I built this project instead. In this framework: - Agents are React…

    Dec 2025 · github.com · its alternatives →

  20. 20

    Em dashes welcome — learn how to build AI agents

    Sep 2026 · buttercup.sh · its alternatives →

  21. 21BA

    I'm one of the creators of The Edge Agent (TEA). We built this because we needed a way to deploy agents that was verifiable and robust enough for production/edge cases, moving away from loose scripts. The architecture aims to solve critical gaps in deterministic orchestration identified by *Prof. Claudionor Coelho Jr. (Stanford alum, ML/DL Faculty at Santa Clara Univ., and Senior Fellow for AI at Majestic Labs)* during our work on the Kiroku project. *Key Technical Features:* * *Neurosymbolic Native:* We integrated Prolog to logically validate LLM outputs. This combines neural…

    Jan 2026 · fabceolin.github.io · its alternatives →

  22. 22

    Hi HN folks, I have been building AI agents for quite some time now. The shift has gone from LLM + Tools → LLM Workflows → Agent + Tools + Memory, and now we are finally seeing true agency emerge: agents as systems composed of tools, command-line access, fine-grained system capabilities, and memory. This way of building agents is powerful, and I believe it is here to stay. But the real question is: are the systems powering these agents ready for that future? I do not think so. Using Docker for a single agent is not going to scale well, because agents need to be lightweight and fast. LLMs…

    Mar 2026 · github.com · its alternatives →

  23. 23

    Build AI agents, teams, and workflows in TypeScript

    May 2026 · confused-ai.github.io · its alternatives →

  24. 24

    TypeScript-first framework for reliable AI agents

    Apr 2026 · github.com · its alternatives →

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