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Aident AI Beta 2

Open-world automations, managed in plain English

Artificial Intelligence
No-Code

Hunted byJustin JincaidJustin Jincaid

Meet the future of work—AI that actually runs with you. Build and manage open-world automations in plain English across Discord, Slack, X, Shopify, and more with 1000+ integrations, 23000+ actions, and 1000+ templates. Trigger on real-world events, get updates in your favorite chat apps via IM + MCP, and monitor runs, approvals, and issues from one live dashboard.

Top comment

Hi everyone👋. I’m Edward, the designer of Aident AI

One thing we kept running into while building automation tools: the hardest part isn’t wiring steps together — it’s handling the messy, unpredictable real world.

For Beta 2, I tried to rethink automation from a design perspective:

1. From UI design → Instruction design.
Instead of drawing flows, users describe intent. The system interprets and structures it.
That shift changed how we design everything.

2. Reducing cognitive overhead.
Node graphs are powerful — but they demand constant mental mapping.
We asked: can automation feel more like delegating to an assistant than managing a dashboard?

3. Closing the “demo vs real work” gap.
Supporting live triggers (Discord, Slack, Shopify, etc.) forced us to design for reliability, not just flexibility.

Also curious about this: for non-technical users, what’s been the hardest part about turning a vague goal into something automation can actually run? 👇

Would love to hear real frustrations — they help us design better.

Comment highlights

This looks awesome. Making automation this simple could be a game changer.

The plain English approach to automation is a really smart unlock — most no-code tools still require users to think in logic trees. Curious how you handle ambiguity when a user's instruction could map to multiple action chains? That edge case is where these tools usually break trust. Would love to see how the error handling surfaces back to the user when something unexpected happens in a real-world trigger scenario.

Like the AI product that reduces cognitive load and make automation straightforward

The plain English automation angle is what gets me — most tools in this space still feel like you need an engineering degree to set up a basic workflow. How does it handle edge cases when a trigger fires but the downstream action fails halfway through?

curious about the "open-world" aspect here. most of these natural language automation tools tend to break once you step outside a very rigid happy path. since you're supporting 23k+ actions, how do you handle state management when one of those mid-stream actions fails or returns an unexpected schema? i'd love to know if there's a way to inspect the underlying logic tree or if it's all just black-box magic.

Really interesting framing! I’m curious who you see as the ideal user for Aident right now. Is this primarily built for non-technical operators who want automation without thinking about logic, or more for technical teams who just want to move faster? Also wondering where you see the main difference vs tools like Zapier, Make, or newer AI automation layers. Is the key advantage the instruction-first interface?

Love the design perspective you’re bringing into automation!

Its amazing how the world of automation software has improved over the last few years - between manually stitching them together in platforms like Zapier to using AI to figuring it all out.

Very cool guys!

Looks cool! Curious how Aident handles reliability when automations get complex across many tools. If a step breaks or an API changes, does the Playbook automatically adapt or flag the issue?

I'm not always the best at prompting so I always appreciate a "Plan" mode to get me started. Is there something similar in Aident so that the automation that gets set up is what I intend it to be?

Really cool concept — automations described in plain English is where everything is heading. We built something similar for our AI routing at TubeSpark (AI for YouTube creators): each task type is described in natural language and the system picks the best AI model automatically. Curious — how do you handle edge cases where the plain English instruction is ambiguous? That's been our biggest challenge with natural language interfaces.

Me describing my automation to Aident: "Do the thing like Zapier/n8n but don't break every Tuesday" 🙏

"AI was smart, the glue was not" is the most honest description of why the current automation stack keeps breaking. Zapier plus RPA plus prompt engineering duct-taped together fails in exactly the ways you'd expect and the 1000th time is never the last time.

The shift from UI design to instruction design that Edward describes is the right framing for what makes this feel different. Node graphs are powerful but they're a UX paradigm built for engineers. Describing intent to a teammate and having it figure out the structure is a completely different contract with the user.

To answer Edward's question from someone building their own AI platform: the hardest part of turning a vague goal into a running automation is usually defining the edge cases. People describe the happy path clearly, but when something unexpected happens mid-run, the automation either fails silently or does something wrong. How does Aident handle ambiguous situations mid-playbook? Does it stop and ask, or make a judgment call? Congrats on the launch! 🤖

Does Aident sit on top of existing tools or replace them?

I already have a bunch of Zaps running, so migration cost is a real concern for me.

Huge congrats on the launch! I've been looking for a way to bridge my Slack and Google Sheets without the node-graph headache. Signing up for Beta 2 now, and I'll be sure to send over some honest feedback! 🚀

About Aident AI Beta 2 on Product Hunt

Open-world automations, managed in plain English

Aident AI Beta 2 launched on Product Hunt on March 5th, 2026 and earned 424 upvotes and 56 comments, earning #1 Product of the Day. Meet the future of work—AI that actually runs with you. Build and manage open-world automations in plain English across Discord, Slack, X, Shopify, and more with 1000+ integrations, 23000+ actions, and 1000+ templates. Trigger on real-world events, get updates in your favorite chat apps via IM + MCP, and monitor runs, approvals, and issues from one live dashboard.

Aident AI Beta 2 was featured in Artificial Intelligence (466.2k followers) and No-Code (5.6k followers) on Product Hunt. Together, these topics include over 91k products, making this a competitive space to launch in.

Who hunted Aident AI Beta 2?

Aident AI Beta 2 was hunted by Justin Jincaid. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.

Want to see how Aident AI Beta 2 stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.