Activepieces @activepieces

@54nz_ @Tiny_Fish @shengkunye Let's do it 👀

You can now build @activepieces flows with Claude or other MCP clients 🔥 No need to think through the full workflow logic step by step. Just connect to the Activepieces MCP server, describe the flow you want, and your AI agent can build and run it for you inside Activepieces. You can find the MCP server in your project settings. Check it out now and let us know what you think.

Building pieces in Activepieces just got easier 🚀 We shipped 2 big updates for developers: → 𝗪𝗲 𝗿𝗲𝗽𝗹𝗮𝗰𝗲𝗱 𝗡𝘅 𝘄𝗶𝘁𝗵 𝗧𝘂𝗿𝗯𝗼 ↳ Faster builds, less setup, and easier debugging Learn more: community.activepieces.com/t/piece-buildi… → 𝗪𝗲 𝗮𝗱𝗱𝗲𝗱 𝗮 𝗣𝗶𝗲𝗰𝗲 𝗕𝘂𝗶𝗹𝗱𝗲𝗿 𝗦𝗸𝗶𝗹𝗹 𝗳𝗼𝗿 𝗔𝗜 𝗰𝗼𝗱𝗶𝗻𝗴 𝗮𝗴𝗲𝗻𝘁𝘀 ↳ This teaches tools like Cursor or Claude Code how Activepieces pieces work, so they can build better pieces with less guesswork Check out the knowledge base: github.com/activepieces/a… This is part of our ongoing work to make building on Activepieces faster, simpler, and more AI-friendly. Let us know what you think.

If your AI “pilot” has been running for months… It’s not a pilot. It’s a bottleneck. AI in production requires structure to scale fast. Activepieces gives you the system to ship it. 🚀 Start building: activepieces.com

An effective AI workflow isn’t magic. It’s structure. → A trigger → An AI step → Human approval → Logged actions Humans decide. AI executes. Everything is tracked. That’s how it should work. Start here: activepieces.com

AI inside a workflow doesn’t just give you output. It gives you accountability. Because AI isn’t powerful in isolation. It’s powerful when it runs inside a system you can trust. This is how companies use Activepieces activepieces.com

AI without security is risk. AI with security is control. Activepieces connects AI agents + your work softwares into a governed workflow. activepieces.com

A flashy AI demo gets attention. A governed AI workflow gets adoption. Activepieces enables you to give AI to every team with IT control and enterprise security activepieces.com

A flashy AI demo gets attention. A governed AI workflow gets adoption. Activepieces enables you to give AI to every team with IT control and enterprise security activepieces.com

AI adoption works when:   • It has an owner.   • It has approvals.   • It has visibility. Otherwise, it’s just another demo. Activepieces turns AI into operational workflows. activepieces.com

“AI saved us time” isn’t proof. Proof looks like: • Faster processing • Logged actions • Clear workflow owner • Defined approval gates • Clear impact That’s what real workflows look like in Activepieces. 🚀 See how: activepieces.com

This flow turns every incoming support email into a proper Linear issue:   •  The problem is rewritten clearly   • The description is cleaned up   • The priority is set automatically Template: cloud.activepieces.com/templates/rnuO…

New tickets shouldn’t be stuck in Zendesk until someone remembers. This flow sends a Slack message every time a new Zendesk ticket is created, including:   •  Ticket subject and requester   • Key details for quick triage   • A direct link back to the ticket Template: cloud.activepieces.com/templates/1A7m…

Shipping features is fun. Writing release notes? Not so much. This automation:   • Watches GitHub for new releases   • Turns them into clean, structured release notes   • Shares updates in Slack   • Logs full details in Notion Template: cloud.activepieces.com/templates/0m0t…

Most AI ROI slides are fiction because they measure intent. Real ROI shows up as:   •Clear time and money saved   • fewer handoffs   • faster cycle time   • fewer escalations   • fewer errors

Most security teams are fine with AI. They’re just not fine with unknown outcomes The following needs to be clear for successful AI implementation:   • What the AI can access   • What it’s allowed to do   • How you’ll log and audit every action Governance is what makes AI safe enough to deploy.

The fastest way to kill an AI pilot: Tell everyone to “try AI” without agreeing on what success looks like. A real pilot should be able to answer: • What specific task is being improved? • How will success be measured? • Who owns the outcome? • What safeguards are in place if something goes wrong? If you can’t answer those, it’s not a pilot. It’s just experimentation with no path to results.

If your AI strategy is “give everyone ChatGPT”… you don’t have a strategy. You have a new writing app. Real adoption starts when AI can:   • Pull data from systems   • Act inside workflows

Most enterprise AI rollouts fail for a simple reason: Using it means leaving your tools, opening a new chat window, and copy/pasting This makes people hesitate to adopt it. Effective AI adoption uses AI to remove extra steps to getting work done

If you can explain a task, you can automate it. Automation isn’t only for “serious” workflows Even small, random things can be automated. Here are 6 interestingly specific things you can build with Activepieces. gamma.app/docs/6-Interes…