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Products that do what Build Your First Multi-Agent Workflow does

See how Graph Engineering helps AI agents work together

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    Anvil175

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    Your AI agents team, terminals, notes: one infinite canvas

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  14. 14SR

    Hello all, I'm a software developer. Over the last few months more and more of my work has turned into using coding agents instead of typing the whole code myself. Usually a few claude sessions at once, sometimes codex, one per feature or per revealed bug. I ran them in a split terminal for a few weeks, and quickly spotted two main problems. The first is that I couldn't easily tell which agent was stuck waiting on me and which was still working, so I'd cycle through sessions and checking on them. The second one: agents sharing a single branch step on each other. Two of them could be editing…

    Jul 2026 · shikigami.dev

  15. 15

    Browse, pick, and use AI agents for fun or productivity

    Nov 2025

  16. 16

    Visual editor to design conversation flows for Agents

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  17. 17AF

    Hey HN, Claude Code is powerful, but its execution is a black box. You see the final result, not the journey. Agent Flow makes the invisible visible in realtime: - Understand agent behavior: See how Claude breaks down problems, which tools it reaches for, and how subagents coordinate - Debug tool call chains: When something goes wrong, trace the exact sequence of decisions and tool calls that led there - See where time is spent: Identify slow tool calls, unnecessary branching, or redundant work at a glance - Learn by watching: Build intuition for how to write better prompts by observing how…

    Mar 2026 · github.com

  18. 18AE

    I’ve spent the past 10 years working on AI in finance, with much of that time focused on building evaluation systems for production environments. As agents become more widely adopted, more software engineering and product people have start building them. But I’ve noticed that many teams are not yet fluent in systematic evaluation, or in the processes needed to keep agent quality high over time. For large organizations, that gap is rarely the bottleneck due to dedicated teams. But after speaking with a number of startups, it became clear that building strong, up-to-date evals is much harder…

    May 2026 · github.com

  19. 19HG

    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

  20. 20AD

    Hey HN, as a former data analyst, I’ve been tooling around trying to get agents to do my old job. The result is this system that gets you maybe 80% of the way there. I think this is a good data point for what the current frontier models are capable of and where they are still lacking (in this case — hypothesis generation and general data intuition). Some initial learnings: - Generating web app-based reports goes much better if there are explicit templates/pre-defined components for the model to use. - Claude can “heal” broken charts if you give it access to chart images and run a…

    Mar 2026 · rubenflamshepherd.com

  21. 21FA

    Founder here. I built NEO, an AI agent designed specifically for AI and ML engineering workflows, after repeatedly hitting the same wall with existing tools: they work for short, linear tasks, but fall apart once workflows become long-running, stateful, and feedback-driven. In real ML work, you don’t just generate code and move on. You explore data, train models, evaluate results, adjust assumptions, rerun experiments, compare metrics, generate artifacts, and iterate; often over hours or days. Most modern coding agents already go beyond single prompts. They can plan steps, write files, run…

    Jan 2026 · marketplace.visualstudio.com

  22. 22AP

    I've been working on this internal project initially both to learn more Vibe-Coding but also to help our teams and projects to use AI more efficiently. As more people used it, it grew to support multiple teams/projects to analyze their Claude Code conversation and optimize them over time (understanding how to write better conversation with Claude Code and share knowledge between them) With time we added support for multiple Claude account management and monitor usage/rate limit. This is a simple project but has proved to be quite useful for our company. We have reached 5000+…

    2025 · github.com

  23. 23DA

    I've been running Claude agents for various automation tasks — monitoring crypto news, syncing Todoist, running health checks — and I kept hitting the same problem: there's no clean way to deploy an agent that just runs on a schedule without a human babysitting it. Every agent framework I looked at was built around chat interfaces or one-shot workflows. I wanted something closer to cron for AI agents — define a task, give it a schedule, let it run forever. So I built Ductwork. You define tasks as simple JSON files — a prompt, a schedule, optional memory and skills — and ductwork handles…

    Mar 2026 · github.com

  24. 24TA

    We’ve been seeing more and more developers use AI coding agents directly in their GraphQL workflows. The problem is the agents tend to fall back to generic or outdated GraphQL patterns. After correcting the same issues over and over, we ended up packaging the GraphQL best practices and conventions we actually want agents to follow as reusable “Skills,” and open-sourced them here: https://github.com/apollographql/skills Install with `npx skills add apollographql/skills` and the agent starts producing named operations with variables, `[Post!]!` list patterns, and more…

    Feb 2026 · skills.sh

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