itsMasita

Learning AI. Testing AI. Sharing what actually works.

[itsMasita @itMasita]

@nyla_amaya Less prompting, more doing.

[Diana @nyla_amaya]

The part of Eazo I find more interesting than “AI builds an app” is what happens after it builds one.

You come back tomorrow.

And the next day.

It becomes a persistent piece of software rather than another disposable AI conversation.

[Diana @nyla_amaya]

One thing I like about this:

You don't need to build a complicated automation first.

Connect Meta Ads → describe the job → set the schedule → let Twin run it.

The interface is basically the instruction.

Everything else happens in the background.

https://t.co/LYmVmVspjo

[itsMasita @itMasita]

@nyla_amaya Meta ads this easy with Twin? 👀 Okay, now I’m curious.

[Naila | AI Insights @Naila_Sync]

AI filmmakers should read this too even if you don't make ads. The way the inspirational example builds is how I want a trailer narrator to move, and ElevenLabs v4 picks up on the right tone and pacing.

[Naila | AI Insights @Naila_Sync]

Editing a recording used to take me the better part of a day or two, and it still felt incomplete. Viktor did it in hours.

Then he told me where to check his work.

I'm an AI educator covering tools, workflows and new AI products.

Every tutorial meant trimming, captioning, then hunting every frame for sensitive info I'd missed.

I handed the redacting to Viktor, my AI employee. I wrote "same standard as every time before"

He kept every rule: redact only what's sensitive, change nothing else, check everything, and say where he's unsure instead of guessing.

His first attempt let my username show for one frame. He caught it himself, asked before redacting two extra things, then named the two stretches he trusted least:

He redacted what he was sure of and asked about the rest. I checked both before posting.

The hours didn't disappear. They moved to him.

At my size, that's one tutorial. At a company, it's every training video and demo. Same standard, same checks, on every one.

The employees worth giving real access to tell you where they might be wrong.

Most AI tells you what to do. Viktor does it.

Hire @viktor_com for your team. $100 in credits included, no card. Full link in my first reply.

Paid Partnership

[itsMasita @itMasita]

@AIwithAriel Real automation: no more babysitting the tools.

[Ariel Christal | AI Tools & Workflows @AIwithAriel]

A lot of “marketing automation” still means someone checking whether the automation worked.

Twin's Meta Ads integration gets closer to the real thing.

The agent checks Ads Manager, pulls the data, watches pacing and moves leads into the CRM without someone manually kicking off the workflow.

https://t.co/mqR7ZxGpF9

[itsMasita @itMasita]

@nyla_amaya Okay, this is wild. The motion looks ridiculously real.

[itsMasita @itMasita]

@AIwithAriel Impressive results!

[Ariel Christal | AI Tools & Workflows @AIwithAriel]

This goes far beyond generating clips.

Pexo planned the scenes, camera movement, sound, captions, and transitions, then preserved the full creative direction while revising one selected area.

That level of control makes the workflow genuinely useful for commercial videos.

[Ariel Christal | AI Tools & Workflows @AIwithAriel]

Virality isn’t just people watching your idea.

It’s people finding new ways to use it.

With @EazoAI, a simple Bluetooth finder for lost glasses can become a tool for keys, remotes, luggage, and much more.

Build the idea. Let people multiply it.

[Ariel Christal | AI Tools & Workflows @AIwithAriel]

A solo founder can now build a $1M/month business without a marketing team.

AI search is changing the game.

12 months ago, this would’ve sounded ridiculous.

Today, one AI native tool can handle the kind of growth work that once took an entire team.

[itsMasita @itMasita]

@AIwithAriel No salary. No status meetings. No QA backlog.
Viktor builds the full dashboard, runs its own 42 checks, and only wakes you for the final yes.
That’s an AI employee that actually finishes the job.

[itsMasita @itMasita]

@AIwithAriel One prompt.
Full dashboard built, 42 tests run, waiting only for my yes.
Viktor doesn’t help you work, it does the work.

[Ariel Christal | AI Tools & Workflows @AIwithAriel]

Imagine an employee that works on demand, handles tedious tasks, uses thousands of tools, and checks its own work.

That’s the power of Viktor
AI employees are moving beyond assistance. They’re actually getting the work done, without the cost of hiring another full time employee.

[itsMasita @itMasita]

@nyla_amaya What I like here is that xLLM leaves room for curiosity. You can change one part of the training setup, run the experiment, learn from it, and keep building. That’s how open tooling should feel.

[itsMasita @itMasita]

@nyla_amaya Speed is nice.
Flexibility is better.
xLLM lets you change data, tokenizer, or model setup without starting over. That’s the real win.

[Diana @nyla_amaya]

What caught my attention about xLLM isn’t just the training speed.

It’s the flexibility.

You can change the tokenizer, data mix or even parts of the model setup without turning every change into a whole new pipeline rebuild.

That matters because at scale, experimenting is inevitable. The real advantage is making the next experiment cheaper and easier to run.

[Diana @nyla_amaya]

Viktor is starting to make the “AI employee” idea feel very real.

It can build, test, deploy, connect with 3,200+ tools, and handle end to end workflows from a single prompt, while still keeping humans in control of the important decisions.

And the crazy part? You’re getting all that without the cost of hiring an entire team.

More execution. Less overhead. One AI employee.