Alternatives
Products that do what Zero does
Vercel's programming language built for AI agents
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I've been working on a new programming language for AI agents. I would love your input on what makes programming languages good for AI agents, especially syntax, compiler, and tooling that could help AI agents write code. What makes Sigil good for coding agents? I've turned conventions into compiler rules whenever possible. The compiler owns the canonical printer and every AST has one accepted textual representation. For almost every syntax feature I tried to save tokens. Order and naming conventions are enforced. No more "I think this argument is important so it should come first." Most…
Apr 2026
- 17AI
The goal of Agentic is to create a set of standard AI functions / tools which are optimized for both normal TS-usage as well as LLM-based apps. It's designed to work with all of the major TS AI SDKs (LangChain, LlamaIndex, Vercel AI SDK, OpenAI SDK, Firebase Genkit, etc) via adaptors. Would love feedback from the HN community :)
2024 · github.com
- 18ZO
ZeroID is an open-source agent identity platform that automates the "plumbing" of RFC 8693 and SPIRE. It ensures that every sub-agent in a chain has a down-scoped, verifiable identity without the manual overhead of managing certificates and token exchanges.
Apr 2026 · github.com
- 19AF
Hi HN — I’m Abhi. We built Agint so PMs and engineers can design and edit software as a graph — architecture first — iterate with fast visual feedback, then generate deployable code from it when it’s ready. We presented underlying approach at NeurIPS (Deep Learning for Codegen) as an Agentic Graph Compiler: The graph (structure + types + semantic annotations) is the source of truth, and code is a compilation/export target. Paper: Agentic Graph Compilation for Software Engineering Agents: https://arxiv.org/abs/2511.19635 Live Demo: https://flow.agintai.com…
Jan 2026 · flow.agintai.com
- 20HA
Hi HN, I am Umer. I recently built an experimental framework called HyperFlow to explore the idea of self-improving AI agents. Usually, when an agent fails a task, we developers step in to manually tweak the prompt or adjust the code logic. I wanted to see if an agent could automate its own improvement loop. Built on LangChain and LangGraph, HyperFlow uses two agents: - A TaskAgent that solves the domain problem. - A MetaAgent that acts as the improver. The MetaAgent looks at the TaskAgent's evaluation logs, rewrites the underlying Python code, tools, and prompt files, and then tests the new…
Apr 2026
- 21AT
Hi Hacker News! We're launching Zalor, an agent testing platform. Agents often break when you tweak system prompts, swap models, or add tools. Zalor automatically generates test scenarios and evaluates your agent so you know it's reliable before deploying to production. We currently support the OpenAI Agents SDK and are onboarding other frameworks. A GitHub integration is coming so you can get feedback on every update. Looking forward to hearing feedback from people building agents.
Mar 2026 · agents.zalor.ai
- 22DA
Hi HN, Today I'd like to present the results of my weekend project of the last year or so. Given there are many posts on HN about LLMs and Prolog, I thought that this would be of interest. DeepClause is my own (possibly misguided :-) attempt at combining LLMs with Logic Programming, ultimately hoping to establish a foundation for building more reliable agents, that produce reproducible and fully traceable result. At the heart of DeepClause is a DSL called "DeepClause Meta Language" (DML) which can be used to encode agent behaviors as executable logic programs. DML is executed by a…
Nov 2025 · github.com
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