Alternatives
Products that do what layerAI does
Decide Before AI Acts.
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Deep Work Plan▲114Models matter. Context matters more. Give your agent a plan.
Jun 2026 · deepworkplan.com
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I've been exploring the (not so=) amazing potential of AI in coding and have compiled a list of tools. From AI-powered IDEs to code generators, this resource is my contribution to the community. I'm still on the fence about including txt2sql projects, as their functionality seems too basic to me. And I'm personally maintaining this, so your feedback is wellcome.
2025 · aicode.danvoronov.com
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Jan 2026 · railly.dev
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Jun 2026 · github.com
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Hi Everyone!! Our team is made up of passionate AI enthusiasts with backgrounds in marketing, and engineering. We’re united by a shared belief that the future of AI should be collaborative, accessible, and community-driven. With experience building consumer products and scaling platforms, we’re focused on creating a space where anyone from hobbyists to professionals can discover, organize, and share the best AI prompts and workflows. Promptly is built with a community-first mindset, where user contributions, creativity, and learning are at the heart of the experience.
2025 · searchpromptly.com
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We’ve been building visual rule engines (clear spreadsheet interfaces -> API endpoints that map incoming data to a large number of potential outcomes), and had the fun idea lately to see what happens when we use our decision table UI with Claude’s PreToolUse hook. The result is a surprisingly useful policy/gating layer– these tables let your team: - Write conditional, exception-friendly policies beyond globs/prefixes (e.g. allow rm -rf only in */node_modules/*, deny / or $HOME, ask if --force or network call; gate kubectl delete / SQL DROP with a clear reason) -…
Jan 2026 · github.com
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We built an open sourced coordination layer for AI agents working on the same repository. Detects work duplication and design conflicts early
9d ago · twing.dev
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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
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Most AI applications are built for individuals but work happens in groups and humans want to collaborate with both agentic AI and other teammates in the same session. We created Hybrid Groups for that purpose. In Hybrid Groups, agents join group chats as virtual team members in Slack and GitHub. They participate in group conversations, proactively contribute when needed and perform actions on behalf of individual users, like managing your calendar for meeting suggestions or updating your todo list without sharing access to your private resources to the group. The project is open-source at…
2025 · youtube.com
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Hi HN, I’m the creator of Cordum. I’ve been working in DevOps and infrastructure for years (currently in the fintech/security space), and as I started playing with AI agents, I noticed a scary pattern. Most "safety" mechanisms rely on system prompts ("Please don't do X") or flimsy Python logic inside the agent itself. If we treat agents as autonomous employees, giving them root access and hoping they listen to instructions felt insane to me. I wanted a way to enforce hard constraints that the LLM cannot override, no matter how "jailbroken" it gets. So I built Cordum. It’s an open-source…
Jan 2026 · github.com
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Hi HN! I'm building Hopsule. If you use AI coding tools like Cursor, Copilot, or Claude, you’ve probably seen this happen: The AI writes good code - but it ignores your architecture. It doesn’t know: - why you chose a specific pattern - which conventions your team agreed on - which decisions are already locked in So it falls back to generic patterns, outdated examples, or random GitHub training data. Over time this slowly breaks the consistency of the codebase. Most teams try to fix this with: - giant Markdown files - wiki pages - long prompts - Slack threads But those aren't…
Mar 2026
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