ProWebier

Most people think all AI tools are the same.

These slides will show you why Jev AI is different from ChatGPT, Claude, and other LLMs and where it actually shines.

We usually think of AI as something that generates text.

ChatGPT, Claude and other LLMs take a prompt and generate an answer token by token.

But `Jev AI by TypeSafe AI` is built differently.

Jev is not mainly designed to write content or chat with users.

It is designed to help software make fast, structured decisions.

For example:

→ Which tool should an AI agent use?
→ Is this message spam or genuine?
→ Which department should receive this support ticket?
→ Should the agent continue, retry, or ask for human review?

Instead of returning a long paragraph, Jev can return:

Choice → Score → Yes/No probability

along with confidence information your code can directly use.

And the interesting part is the price.

Jev currently costs around:

$0.042 per 1 million input tokens
Output tokens: Free

That is only about $42 for 1 BILLION input tokens.

TypeSafe AI says its input pricing is around 238× lower than Claude Fable 5.1.

But this does NOT mean Jev replaces ChatGPT or Claude.

A better way to understand it is:

LLM → Think, write and generate
Jev → Decide, classify and route

This could become very useful in AI Agents and automation systems, where thousands or millions of small decisions need to happen quickly and cheaply.

AI is slowly becoming more specialized.

Not every task needs a large language model anymore.

Send a message to learn more

Aap business chala rahe hain - ya Excel, WhatsApp aur manual records aapko chala rahe hain?

Leads, customers, sales, staff, inventory aur payments ko alag-alag jagah manage karna time bhi waste karta hai aur mistakes bhi barhata hai.

Main aapke business ke workflow ke mutabiq Custom CRM, Business Management Software aur Restaurant POS Systems develop karta hoon.

✅ Leads & Sales Management
✅ Staff, Tasks & Payments
✅ Inventory & Reports
✅ Restaurant POS, Billing & Orders
✅ Solar CRM & Installation Management
✅ Custom Dashboard & Automations

Koi fixed template nahi software aapke business ke process ke according build hoga.

Apni requirements WhatsApp ya Inbox par share karein aur main aapko suitable solution suggest kar karunga.

Send a message to learn more

Agar aap business owner hain, to sirf “website hona” enough nahi hai.

Aaj kal website ko 3 cheezein zaroor karni chahiye:

User ko quickly samajh aaye ke aap kya offer karte hain
Website fast aur mobile-friendly ho
Visitor ko clear next step mile Call, WhatsApp, Book, Buy, ya Contact

Bohat si websites achi dikhti hain, lekin convert nahi karti.

Reason?

Too much text.
Confusing navigation.
Slow loading.
Weak mobile experience.
No clear CTA.
Aur unnecessary animations jo user ko distract karti hain.

Ek professional website ka goal sirf “beautiful” hona nahi hota.

Uska goal hota hai:
Attention lena → Trust build karna → User ko guide karna → Action karwana.

Simple rule:

Har page par user ko yeh pata hona chahiye ke “ab mujhe kya karna hai?”

Agar user ko 5–10 seconds mein samajh nahi aa raha ke aap kya offer karte hain, to design chahe kitna bhi premium ho, website apna kaam properly nahi kar rahi.

Good design impress karta hai.

Good UX convert karta hai.

Aur strong development ensure karti hai ke sab kuch fast, smooth aur reliable chale.

Aapki website ka sabse important goal kya hona chahiye branding, leads, ya sales?

Agar aapko apne business ke liye professional website ya high-converting landing page chahiye jo sirf achi na lage balki real results generate kare, feel free to DM me.

Send a message to learn more

A startup has around 200 active users.

The product is working, the team is small, and traffic is still manageable.

Then someone says:

“Let’s move to microservices now so we can scale later.”

Sounds smart, but is it?

Microservices can improve scalability and team independence, but they also introduce:

→ More infrastructure
→ More deployments
→ Service-to-service communication
→ Distributed debugging
→ Monitoring complexity
→ Higher operational cost

Sometimes, a well-structured "modular monolith" can take a product much further than people expect.

So here’s the question:

When does “building for scale” become over-engineering?

If you were leading the engineering team, would you choose:

A) Microservices from the start
B) Modular monolith first
C) Depends on the product
D) Something else

Would love to hear how experienced developers and architects approach this.

Everyone is talking about AI Agents.

But here is a question I find more interesting:

How much control would you actually give an AI agent?

Would you allow it to:

→ Send emails to clients
→ Update your CRM
→ Modify database records
→ Handle customer refunds
→ Deploy code to production

All without asking for human approval?

Building an agent that can take actions is one thing.

Trusting it to take those actions is another.

Where would you draw the line?

Send a message to learn more

AI Won’t Replace Developers. But It Will Raise the Bar.

AI is making development faster.

Features that once took days can now be prototyped in hours. Boilerplate is easier. Debugging is faster. Even complex workflows can be accelerated.

But that doesn’t make developers less valuable.

It makes basic ex*****on less valuable.

The real advantage now comes from being able to:

→ Understand the business problem
→ Design the right system
→ Know when AI-generated code is wrong
→ Make strong architecture decisions
→ Connect products, data, APIs, and automation
→ Ship something people can actually rely on

AI can help you write the code.

But it still needs someone who understands what should be built, why it matters, and how everything should work together.

The bar for developers isn’t disappearing.

It’s getting higher.

The Best Developer Won’t Write the Most Code.

For a long time, being a great developer meant writing more code, faster.

That’s changing.

AI can already generate components, APIs, tests, documentation, and even complete features in minutes.

So the real value is moving somewhere else:

→ Understanding the actual problem
→ Choosing the right architecture
→ Giving AI the right context
→ Reviewing what it generates
→ Making better technical decisions
→ Knowing what *shouldn’t* be built

A developer who writes 500 lines manually isn’t automatically more valuable than someone who uses AI to produce the same result in 50 lines and ships it correctly.

The skill is no longer just writing code.

It’s knowing how to turn requirements, AI tools, architecture, and business goals into a reliable product.

The future developer isn’t just a coder.
They’re an engineering decision-maker.

AI Coding Is Fast. Bad Architecture Is Faster.

AI has made software development incredibly fast.

You can generate a dashboard, API, authentication flow, or even an entire feature before your coffee gets cold.

But there’s a problem.
AI can generate code faster than your codebase can handle bad decisions.

Without clear architecture, you quickly get:
→ Duplicate logic
→ Poorly structured APIs
→ Components nobody understands
→ Security issues
→ Unnecessary dependencies
→ A codebase that becomes harder to maintain with every feature

The problem isn’t AI-generated code. The problem is using AI without engineering discipline.

Use AI for speed.

But keep architecture, standards, testing, security, and final decisions under your control.

AI can accelerate development.
It can also accelerate technical debt.

Good developers write code. Great developers remove business friction.

A client rarely wakes up thinking:
“I need a better tech stack.”

They’re usually thinking:
→ Why are leads being missed?
→ Why is my team doing this manually?
→ Why are customers dropping off?
→ Why is this process taking so long?

That’s where real value starts.

Your job isn’t just to build features.

It’s to understand the bottleneck, simplify the process, and build something that actually moves the business forward.

Code is the tool. The business outcome is the real deliverable.