Alternatives
Products that do what SVAHNAR does
The Operating System and Infrastructure for Agentic AI.
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I built Axe because I got tired of every AI tool trying to be a chatbot. Most frameworks want a long-lived session with a massive context window doing everything at once. That's expensive, slow, and fragile. Good software is small, focused, and composable... AI agents should be too. Axe treats LLM agents like Unix programs. Each agent is a TOML config with a focused job. Such as code reviewer, log analyzer, commit message writer. You can run them from the CLI, pipe data in, get results out. You can use pipes to chain them together. Or trigger from cron, git hooks, CI. What Axe is: - 12MB…
Mar 2026 · github.com
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The stack: two agents on separate boxes. The public one (nullclaw) is a 678 KB Zig binary using ~1 MB RAM, connected to an Ergo IRC server. Visitors talk to it via a gamja web client embedded in my site. The private one (ironclaw) handles email and scheduling, reachable only over Tailscale via Google's A2A protocol. Tiered inference: Haiku 4.5 for conversation (sub-second, cheap), Sonnet 4.6 for tool use (only when needed). Hard cap at $2/day. A2A passthrough: the private-side agent borrows the gateway's own inference pipeline, so there's one API key and one billing relationship…
Mar 2026 · georgelarson.me
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One framework for chatbots, webhook, voice & data agents
Apr 2026 · dronahq.com
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Hi HN, Founder here. We built Pica, an open-source platform in Rust to enable agentic AI with three main focus areas: - Access to APIs and tools: Universal SDKs that let AI agents use thousands of external actions without blowing up your context window. - Visibility and traceability: Full audit logs of every decision/action to ensure transparency and accountability. - Alignment with human intentions: Seamless guardrails for autonomous tasks; e.g., restricting certain email actions to human approval. Why this matters: As autonomy in AI grows, we need robust solutions for trust and…
2025 · picaos.com
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I've been building computer-use tools for a while, and I quietly launched this about a month ago (122 Stars on GH). I figured it was worth sharing here. Over the last few months, a lot of computer-use agents have come out: Codex, Claude Code, CUA, and others. Most of them seem to work roughly like this: 1. Take a screenshot 2. Have the model predict pixel coordinates 3. Click x,y 4. Take another screenshot 5. Repeat That works, but it's slow, expensive in tokens, and fragile. If the UI shifts a few pixels, things break. And the model still doesn't know what any element actually is. But the…
May 2026 · github.com
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Hey HN, We are Winston, Edward, and James, and we built Meka Agent, an open-source framework that lets vision-based LLMs execute tasks directly on a computer, just like a person would. Backstory: In the last few months, we've been building computer-use agents that have been used by various teams for QA testing, but realized that the underlying browsing frameworks aren't quite good enough yet. As such, we've been working on a browsing agent. We achieved 72.7% on WebArena compared to the previous state of the art set by OpenAI's new ChatGPT agent at 65.4%. You can read more about it here:…
2025 · github.com
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What's up HN! This is Jared and Art. We met on HN and started building together. Over the last few months we've been thinking a lot about how AI agents are going to impact the future. We want agents to be something that's actually useful for normal people as well as the 10x'ers. This lead us to building Meha over the last few months, our first swing at our vision! We saw OpenAI release Operators then we said f*k it let's post. Meha is a desktop app that uses your Chrome browser to execute tasks in the background. It controls your installed Chrome browser and uses LLMs with playwright to plan…
2025 · meha.ai
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