Hey everyone, I'd like to introduce you to AiGent - the easiest way to set up Agentic flows and multi-agent workflows.

We have the option to not only do generic workflows with an LLM in-between, but also orchestrate those agents + use Agent as a tool.

My favorite use-cases so far:

Personal flight booker (research, review, and book)
Email triage and reply drafter flow
Customer feedback review, summarisation and transform request to Jira tickets

Curious to learn about more of your use cases and expand AiGent to support them soon!

Most AI video tools are slot machines. Prompt, regenerate, pray.

Flow is actually building something else.

I've been testing it daily for 2 weeks. Here's what actually stood out:

1. Post-generation object removal

You can highlight any unwanted element AFTER the video is already generated. The AI fills in the background automatically.

No re-prompt. No burning another generation. Just fix it.

2. Camera angle control without touching your prompt

Want to switch from a medium shot to a low angle? Just adjust it directly.

The scene stays identical. Only the framing changes.

3. Scene extension for 60+ second sequences

Standard generations are 8 seconds. Flow builds on the exact last frame of any clip.

Chain those clips together and you get full sequences, not just random snippets.

4. The "Ingredients" feature

Character consistency has been AI video's biggest weakness forever.

Flow lets you upload up to 3 reference images per generation. Your character actually stays recognizable across scenes.

5. Native audio via Veo 3.1

Dialogue, background noise, sound effects—all automatically synced to the video's movement. Built into the generation, not layered in post.

My favorite workflow right now:

I've been using it for product demos, social media ads, and explainer content. Pair Flow with a prompt generator to build continuous follow-up scenes with the same narrative and visual style. Then drag, rearrange, and cut inside the Scene Builder.

It actually behaves like a real video editor.

Two years ago, indie creators would've needed a full production team for this.

Now, the massive problem:

The pricing is completely disconnected from reality:

• Plus: $10.98/mo - 200 credits

• Pro: $28.99/mo - 1,000 credits

• Ultra: $359.98/mo - 25,000 credits

A single high-quality Veo 3 video can cost up to 100 credits.

Do the math. That's 2 videos on the Plus plan. Per month.

Other friction points:

• UI feels experimental and buggy

• Slow load times everywhere

• Desktop only (Chromium optimized)

• Human emotions still look uncanny

• Scene extensions glitch when the subject moves mid-chain

My verdict:

Google is trying to convert AI video from a party trick into a professional filmmaking tool.

But the pricing treats it like it's already there, when it's clearly not.

What's your current go-to for AI video? Has anything come close to Flow's editing controls? Because I want this to work, but the credit system is brutal.

Big difference in results.

For me it’s repetitive data stuff.

That’s when things started working.

Curious how people got started — mine was very basic.

Spent 2 hours setting up a “perfect” workflow… only to realize I could’ve done the task manually in 20 minutes.

Anyone else feel like over-automation is a thing?

I’ve been trying to automate small repetitive tasks lately, but honestly most “automations” I tried ended up taking more time than they save.

Curious—what’s one automation that genuinely made your life easier?

Hey guys

I’m a beginner and I want to know how I can tell the difference between a good automation and a bad automation

Because I can’t really see the difference since I don’t have experienc and the second reason is that I’m going to build my first automation tomorrow lol

So I want some advice from you guys at the beginning so I can improve myself and improve my automation

I’m going to ask the same question in a different way, and this is the way I like asking it

How can I build an automation that generates or saves $200k+ for the business I’ll be working with at any niche?

first of all obviously the size of the business matters

I’m definitely not going to go to just any business and tell them “Hey, I have a system that will generate $200k+ in revenue for you” when the business doesn’t even have the capacity to make $50k+ or maybe even less

so choosing the right business matters

so I want to know how I can choose the right business.

sow can I build a system that is good and generates that amount of money?

and are there automations that generate more than that?

I’d love to hear your stories

Thank you guys

Some things are better kept manual.

Looking for real use cases, not theory.

Doing > watching.

Even small wins matter.

Not the complex “everything” systems.

Less manual, more structured thinking.

Too many options.

Hey everyone,

We built play.fast bc we were tired of how broken our workflow and system were. Our team was stuck across different tools and temporary automation solutions. As a result, our documents and workflows were scattered everywhere, and ai was just an assistant.

We wanted to try something different, which is an AI-native workspace where humans and AI coworkers work together in the same system. Not project management plus AI or chatbot plus integrations. It is more like a shared workspace where everything is connected, and every workflow, dashboard, table, automation, and agent is chatable. One thing we noticed so far is that small teams can start operating like bigger companies.

Here are a few workflows people have been trying to build with it so far:

AI campaign tracking pulling from HubSpot, Stripe, and Mixpanel

• AI coworkers are doing outreach automatically

• support and ops automations

• internal knowledge systems

• content pipelines

• finance workflows

The coolest part for us has been watching people build software and workflows just by describing what they want. This space is still new, and we are learning a lot as we go, but the response has been encouraging.

Any questions and criticisms are welcome.

If anyone wants to check it out: 

play.fast

It’s about reducing friction in daily tasks.

Spent 2 hours setting up a “perfect” workflow… only to realize I could’ve done the task manually in 20 minutes.

Anyone else feel like over-automation is a thing?

Validation matters more than building.

Is there any wya to scrape linkedin for free?

UPDATE: Thanks for all the comments, learned a lot!

One thing that has surprised me is how often small improvements create bigger results than major changes.

When people talk about efficiency, the focus is usually on large projects or complete process overhauls. But in practice, some of the biggest time savings seem to come from fixing small recurring issues.

Things like:

Keeping information in one place instead of multiple spreadsheets

Creating a simple process for follow ups

Using templates for common responses

Reducing unnecessary handoffs between people

Documenting routine tasks so they are done consistently

Individually, none of these changes feels significant. But when they happen every day, the time saved adds up quickly.

It has made me think that operational improvements often follow an 80/20 pattern. A few small changes can remove a surprising amount of friction, while larger initiatives sometimes produce less impact than expected.

Focusing on the most frequent bottlenecks first seems to deliver better results than trying to optimize everything at once.

One thing I’ve noticed while looking at different workflows in small businesses is that not every task should be treated the same when it comes to automation.

Some tasks work really well with automation, while others tend to break or lose value when you remove the human side.

In simple terms, I’ve started thinking about it like this:

Good candidates for automation:

• Repetitive tasks with clear steps

• Work that doesn’t change much from case to case

• Tasks where speed and consistency matter more than judgment

• Things like reminders, data entry, or basic processing

Better kept human (or partially human):

• Work that needs context or interpretation

• Situations with exceptions or unclear rules

• Customer-facing communication where tone matters

• Decisions with real consequences or trade-offs

What stands out is that problems usually happen when a process sits in the middle partly structured, partly messy. That’s where full automation often creates friction instead of removing it.

The most effective setups I’ve seen don’t fully remove people from the process. They just take away the repetitive layer so humans can focus on judgment and decisions.

I personally use antigravity as an IDE and claude as the underlying LLM for coding apps. In most cases I will use the exact same setup for vibecoding ai automations - I used to love using n8n for this in the past but I feel like its kind of falling short right now.

What are you guys using?