DEV Community: Abd Elaziz El7or

I Built Zizo AI: An AI App That Feels More Human, Speaks in Voice, and Supports Multiple Agents

Abd Elaziz El7or — Sat, 28 Mar 2026 06:59:17 +0000

A lot of AI apps still feel the same.

You type.
It answers.
End of story.

I wanted something that feels more alive, more interactive, and more useful in real conversations.

That’s why I built Zizo AI.

Try it here:
https://ai.zizo.work/

Zizo AI is not just a basic text chatbot. It is built to make AI feel more present while you use it.

What it currently supports:

Text chat
Voice replies
Voice generation
Image generation
Multiple AI agents
Multiple chats
Whisper-style interactions
Google login
Daily free credits
Invite rewards

One thing I really wanted was to make the AI feel less “dead” during the conversation.

So inside the app, you can see live states like:

typing
recording
active response flow

That small detail changes the experience a lot.

Instead of feeling like you send a message into a black box, it feels more like the AI is actually doing something in front of you.

Open it here:
https://ai.zizo.work/

Another big part of the idea is voice.

Zizo AI is built around the idea that AI should not only answer with text. It should also be able to speak in a more expressive way.

For example, users can ask for different voice styles depending on the mood or character they want.

That makes it more flexible for storytelling, role-style responses, content creation, and just a more fun user experience overall.

There is also a voice call feature in beta, which is part of the bigger goal of making AI interaction feel more natural.

I also did not want everything to depend on one single AI personality.

So the app supports multiple AI agents, where each one can stay more focused on a certain role or type of interaction.

That makes the product feel more organized than the usual “one chatbot does everything” approach.

Some practical user-friendly parts I wanted to keep simple:

Google login for faster access
Daily free credits
40 credits for each invited friend
Easy top-up flow
Affordable pricing direction

Because honestly, many AI products become annoying the moment you try to actually use them regularly.

Too many limits.
Too much friction.
Too much “pay first, try later.”

I wanted Zizo AI to feel easier to enter and easier to continue using.

There is still more to improve, and some features are still being refined, but the direction is clear:

Make AI feel more human.
Make it more expressive.
Make it more interactive.
Make it more useful.

If you want to try it, here it is again:

https://ai.zizo.work/

And yes, feedback is welcome.

If you try it, I’d love to know:

Which feature feels most interesting?
Do the multiple AI agents make the experience better?
Would you use voice more than text?
What would make this feel even more human?

Try Zizo AI:
https://ai.zizo.work/

Shadowhand AI: Your Local-First PC Operator (Not Just Another Chatbot)

Abd Elaziz El7or — Fri, 16 Jan 2026 04:39:53 +0000

Most “AI assistants” are really just chatbots with extra confidence. They can write messages, summarize text, maybe generate an idea or two… but the second you ask them to do real work on your PC, they crumble.

Shadowhand AI is built differently.
It’s a local-first operator for Windows designed to help you execute tasks—safely, transparently, and under your control.

Instead of “prompt → vibes,” Shadowhand follows an operator workflow:

Brief → Plan → Approve → Execute → Log

That one change is everything.

👉 https://shadowhand-ai.web.app/

1) Task Automation That Doesn’t Freelance

Shadowhand isn’t trying to be clever. It’s trying to be correct.

You tell it what you want:

“Open the report, extract Q3 totals, and draft a clean summary.”
“Go to the dashboard, export the data, save it with today’s date.”
“Find missing invoices and list what’s incomplete.”

Shadowhand responds by creating a step-by-step plan first. You can edit it, approve it, or stop it. Only then does it execute.

This means you’re not betting your work on a black box.
You’re supervising a reliable operator.

2) Full Transparency: Logs You Can Trust

Automation without accountability becomes chaos fast—especially for finance, ops, support, admin work, or anything with repeatable processes.

Shadowhand keeps clear logs of what happened:

what it opened
what it clicked
what it extracted
what it produced
what changed

So you can review, audit, repeat, and refine workflows with confidence.

This is what makes Shadowhand usable beyond demos:
it’s built for people who need outcomes they can defend.

3) Voice Mode That Actually Feels Useful

Voice AI is usually a gimmick. Shadowhand treats it like a real control layer.

You can speak naturally:

“Open Chrome and go to the financial folder.”
“Pull the totals and read them back to me.”
“Summarize the findings and prepare a message I can send.”

And as it works, it can narrate the steps so you know what’s happening without staring at the screen.

It’s designed to feel calm and precise—like talking to a teammate who doesn’t panic.

4) Hands-Free Control for Real Situations

Hands-free isn’t just for “cool factor.”

It matters when:

you’re multitasking
you’re moving around
your hands are busy
you want accessibility-first control

Shadowhand brings hands-free operation into the same operator workflow:
plan + approval + execution + logging, even when you’re using voice.

So it doesn’t become “voice autopilot.”
It stays voice-driven, human-controlled.

5) Note-Taker Mode: Turn Meetings Into Action

A lot of meetings create noise—few create clarity.

Shadowhand’s note-taker concept is about turning a session into:

structured notes
action items
decisions made
follow-ups
“what to improve next time”

So instead of “here’s a summary,” you get useful output you can actually work from.

And if you’re building a team workflow around meetings, this is where Shadowhand becomes a real productivity system—not just a tool.

Why People Switch: “Operator Brain” > “Chatbot Brain”

Shadowhand isn’t trying to be cute. It’s trying to be dependable.

If you want an assistant that:

does tasks, not just text
asks before acting
executes step-by-step
keeps logs
works local-first
and supports automation, voice, hands-free, and note-taking

Then Shadowhand AI is built for you.

👉 https://shadowhand-ai.web.app/

[Boost]

Abd Elaziz El7or — Fri, 14 Nov 2025 16:51:06 +0000

🧠💥 “Linear Algebra Ruined My Life (and Made Me Better at AI)”

Abd Elaziz El7or ・ Nov 14

#ai #machinelearning #deeplearning #beginners

🧠💥 “Linear Algebra Ruined My Life (and Made Me Better at AI)”

Abd Elaziz El7or — Fri, 14 Nov 2025 04:41:29 +0000

1️⃣ Vectors — Emo Arrows With Feelings

A vector is just a fancy way of saying:

“Here’s a direction and how strongly I’m going that way.”

In 2D, a vector is like:

v = (3, 4) → “Move 3 steps right, 4 steps up.”

But let’s be real:
In AI world, vectors are:

Your image turned into a long, miserable line of pixel values.
Your sentence turned into a long, confused list of numbers (embeddings).
Your soul after debugging a model for 5 hours: still a vector.

Imagine each vector as that one drama friend:

Has magnitude (how intense they are).
Has direction (where the drama is heading).
Can be scaled (more coffee → more chaos).

Mathematically:

Magnitude of v = (3, 4) → ||v|| = √(3² + 4²) = 5

So yes, we just reinvented the Pythagorean theorem and called it “length of a vector”.
Congratulations, math.

2️⃣ Matrices — Spreadsheets That Lift

A matrix is a bunch of vectors stacked like lasagna:

A = [ 1  2  3
      4  5  6 ]

Think of a matrix as:

A filter that takes your vector and spits out a new vector.
A function in disguise: instead of f(x), you have A * x.
Or a gym trainer: you walk in as a vector, you walk out “transformed” (sometimes better, sometimes broken).

When you multiply a matrix by a vector:

A * x = y

You’re basically saying:

“Take this vector, apply some structured chaos to it, and give me the result.”

In Machine Learning:

Your weights in a neural network layer? → a matrix.
Your input features? → a vector.
Forward pass? → output = W * x + b (plus sadness and ReLU).

3️⃣ Linear Transformations — The World Filters

A linear transformation is a matrix that:

Stretches space 🧻
Rotates things 🔄
Squashes directions like a pancake 🥞

Imagine the 2D world as a rubber sheet.
Your matrix says:

“What if I stretch it up, squish it sideways, and rotate it 30°… for science?”

Example:

A scaling matrix:

[ 2  0
  0  3 ]

This means:

Double everything in x direction.
Triple everything in y direction.

You put in a vector, it comes out taller, wider, and more dramatic.

That’s literally what happens when:

Your model learns important features → some directions are stretched (important).
Other directions get squished → model doesn’t care → noise.

4️⃣ Dot Product — “How Aligned Are We Really?”

The dot product is the math version of:

“Do we vibe or not?”

For two vectors a and b:

a · b = ||a|| ||b|| cos(θ)

If:

cos(θ) ≈ 1 → we’re going in the same direction → besties
cos(θ) ≈ 0 → completely different directions → don’t know you
cos(θ) ≈ -1 → opposite → enemies to the death

In AI:

Cosine similarity between word vectors:
- “king” and “queen” → high similarity.
- “cat” and “gradient descent” → low similarity (I hope).

5️⃣ Eigenvectors & Eigenvalues — Drama Queens of Transformations

You know those people who say:

“I don’t change for anyone.”

That’s an eigenvector.

An eigenvector of a matrix is a vector that, when transformed, keeps its direction.
The only thing that changes is how stretched it is.

Matrix: “I’m going to transform you.”
Eigenvector: “Cool. I’ll stay on the same line, but you can scale me.”

Formally:

A * v = λ * v

Where:

v → eigenvector
λ → eigenvalue (the “how much we stretched/squished it”)

In ML:

PCA (Principal Component Analysis) finds directions (eigenvectors) that explain most of the variance.
Those directions are like:

“Hi. I’m where the data actually changes. Look at me, I’m important.”

6️⃣ Why Does Any of This Matter for AI?

Because behind your “fancy” model:

Your inputs → vectors.
Your weights → matrices.
Your layers → linear transformations + non-linear spices.
Your attention mechanisms → dot products and matrix multiplications on steroids.

When you train a model, you’re basically:

Teaching matrices how to not be stupid.

And Linear Algebra is the language they speak.

7️⃣ Mini Practice (for Ninjas Who Actually Want to Learn)

You can drop this as a task in your Discord 👇

🧪 Challenge

Take two vectors:

   a = (1, 2),  b = (3, 4)

Compute a + b
Compute the dot product a · b
Compute the length of a

Take this matrix:

   A = [ 2  0
         0  3 ]

And vector:

   x = (1, 1)

Compute A * x
Describe in words what happened to x (stretched? squished?).

Extra spicy:

Google: “PCA visualization 2D”
Look at any plot where data is rotated → that’s linear algebra doing parkour.

8️⃣ TL;DR for the Lazy Ninja

Vectors → arrows with attitude.
Matrices → filters that transform those arrows.
Linear transformations → stretch, rotate, squish space.
Dot product → “how much do we point in the same direction?”
Eigenvectors/values → the “unchanged direction” celebrities of transformations.

If you understand just this, you’re already more dangerous than half the people copy-pasting code from YouTube.

🥷 “AI is just linear algebra wearing a hoodie.”
You’re not just learning math — you’re learning the secret engine inside Machine Learning.

I Tried Manus AI — The "Do-Everything" Agent Everyone's Talking About

Abd Elaziz El7or — Thu, 12 Jun 2025 06:08:37 +0000

What if AI didn’t just chat—but actually opened your browser, wrote your report, designed your logo, and sent the email… all by itself?

That’s the bold promise of Manus AI—and I had to try it.

I recently discovered Manus, an ambitious autonomous AI agent launched in March 2025. Unlike typical bots that only chat, Manus can plan and execute multi-step tasks: it reads websites, writes code, simulates environments, designs visuals, and more—all without constant supervision (manusai.io, en.wikipedia.org).

⚙️ How Manus Stands Out

Tool‑calling & independent execution: Manus interacts with a browser, CLI, files, and even image-generators—finishing tasks end‑to‑end, not just sketching solutions (manusai.io).
State‑of‑the‑art GAIA benchmark results: It reportedly surpasses models like OpenAI DeepResearch—humans score ~92%, GPT‑4 plugins ~15%, and Manus reportedly hits ~86–90% (manusai.io).
Integrated visuals: It can generate images (e.g. logos, mockups) within context-based workflows—like branding a food truck—rather than serving one-off art (techradar.com).

👀 What People Are Saying

Opinions are mixed:

Praise: “The most impressive AI tool I’ve ever tried… could eliminate the need for coding as we know it” (businessinsider.com).
Critiques: Users report slowness, task failures, and that credit costs can add up quickly .

Manus is still invite‑only. A waitlist is active, but invites are rare (reuters.com).

✅ Why You Should Try It

➡️ If you've ever wanted AI that actually does things—plans, executes, integrates visuals—without babysitting, Manus is worth exploring.
➡️ It's perfect for workflows like data scraping, report creation, slide generation, code prototyping, or even startup‑style branding.
➡️ And—if you use my invite link, we both get credits to get started faster:

🎁 Want to try Manus AI for free?

Use my invite link and we’ll both get credits to explore its full power:

👉👉 https://manus.im/invitation/Y28BAHOA6WTI 👈👈

📝 TL;DR

Strengths	Weaknesses
Full task planning & execution	Slow & sometimes unstable
Integrated visuals & docs	Credit‑heavy & warranty limits
Outperforms standard agents	Privacy & invite constraints

DEV Community: Abd Elaziz El7or

I Built Zizo AI: An AI App That Feels More Human, Speaks in Voice, and Supports Multiple Agents

Shadowhand AI: Your Local-First PC Operator (Not Just Another Chatbot)

1) Task Automation That Doesn’t Freelance

2) Full Transparency: Logs You Can Trust

3) Voice Mode That Actually Feels Useful

4) Hands-Free Control for Real Situations

5) Note-Taker Mode: Turn Meetings Into Action

Why People Switch: “Operator Brain” > “Chatbot Brain”

[Boost]

🧠💥 “Linear Algebra Ruined My Life (and Made Me Better at AI)”

Abd Elaziz El7or ・ Nov 14

🧠💥 “Linear Algebra Ruined My Life (and Made Me Better at AI)”

Read Also on:

Kaggle

Notion

Join 💥Ninja Neural Nets 🥷 AI Group to learn together: https://discord.gg/DNmnmGDCxz

1️⃣ Vectors — Emo Arrows With Feelings

2️⃣ Matrices — Spreadsheets That Lift

3️⃣ Linear Transformations — The World Filters

4️⃣ Dot Product — “How Aligned Are We Really?”

5️⃣ Eigenvectors & Eigenvalues — Drama Queens of Transformations

6️⃣ Why Does Any of This Matter for AI?

7️⃣ Mini Practice (for Ninjas Who Actually Want to Learn)

🧪 Challenge

8️⃣ TL;DR for the Lazy Ninja

I Tried Manus AI — The "Do-Everything" Agent Everyone's Talking About

⚙️ How Manus Stands Out

👀 What People Are Saying

✅ Why You Should Try It

📝 TL;DR