Founder | Helping startups hire pre-screened devs in 24 hrs.

I’ve spent the last 10+ years building and scaling tech products — including founding and growing two startups to 7-figure revenue, fully bootstrapped.

Along the way, I worked closely with early-stage founders, CTOs, and product teams on one core problem: turning ideas into real, shipped products — without burning time or money.

After helping dozens of startups with product strategy, hiring, and execution, one pattern became obvious:

Great startups aren’t held back by ideas.
They’re held back by slow execution and bad hiring.

Hiring developers the “traditional” way is broken — endless CVs, multiple interviews, long onboarding cycles… and still no certainty you hired the right person.

So I built Y Interval — a dev partner designed specifically for startups.

We combine:
• Startup-grade product thinking
• Vetted senior engineers who work like in-house
• Fast MVP builds without over-engineering
• Flexible, no-drama engagement models

The result:
Startups ship faster, hire smarter, and scale with confidence.

Since then, I’ve worked with 100+ startups and product teams, from early MVP stage to scale-ups, helping them:
• Build and launch MVPs
• Extend or replace in-house dev teams
• Execute AI, web, and full-stack products properly

Credibility highlights:
→ Built and exited two tech startups
→ Generated 7-figure revenue across services businesses
→ Helped 100+ startups build and scale remote dev teams
→ Worked with teams connected to Microsoft, Meta, and other large orgs
→ Built a media + newsletter brand read by 50K+ founders

If you’re a founder or CTO:
• Building an MVP
• Struggling with dev execution
• Or tired of unreliable agencies

Happy to connect and share how we usually help. Just connect via DMs here or check out our website: yinterval.com

Samee Hassan

RIP Privacy 

AI Glasses Can Now Recognize Anyone, Anywhere 🤯

A Dutch journalist just tested a pair of AI-powered glasses that can instantly identify strangers on the street.

No government database. No police system. Just public data and off-the-shelf AI.

You look at someone and in seconds, their name, LinkedIn, and background appear before your eyes.

The scariest part? You can’t really stop it.

You can ban it, regulate it, add blinking red lights… but once tech like this exists, someone will always find a way to use it.

To me, this marks a turning point.

We’ve officially blurred the line between seeing people and knowing them.

Between being in public and being exposed.

So here’s the question:
When every face becomes a dataset, how do we protect the meaning of being human?

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Founder | Helping startups ramp up dev capacity and speed up product development. Built & shipped 50+ products | 100+ clients including owner.com, moonpay, shortimize and more. Deep in AI and data.

A big mistake I’m seeing with the whole “vibe coding” wave:

People think writing code faster has leveled the playing field for non-technical founders.

It hasn’t.

Speed of typing code was never the bottleneck.

If faster code was the advantage, the winning strategy would always be “hire more developers.”

Anyone who’s built real software knows that usually makes things worse, not better.

At a certain point, building a product stops being about bulk code.

It becomes a series of precise decisions that need context, tradeoffs, and deep understanding.

Once an app reaches any real complexity, most of the work isn’t coding.

It’s planning, sequencing, reviewing, and deciding what not to build.

That’s why senior engineers don’t spend 12 hours a day writing code.

They spend time thinking through systems, edge cases, and second-order effects.

And being non-technical was never a real moat anyway.

Founders were already “vibe coding” long before the term existed.
Writing specs.
Explaining flows.
Sketching features.
Setting direction.

The hard part was never typing the code.

It was execution, prioritization, and shipping something people actually use.

The real shift now isn’t that a solo founder will replace Salesforce.

It’s that customers can build small, custom tools to replace parts of your product.

That’s the new game.

Curious how others are thinking about this shift - what changes when users can build their own solutions?

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For a long time, voice AI has felt close… but not quite there.

Great demos.
Impressive transcripts.
Still very robotic conversations.

The missing piece was always the same:
real-time, natural, end-to-end speech - not stitched together systems.

That’s why this launch caught my attention.
Chroma is the world’s first open-source, end-to-end, real-time speech-to-speech model - with personalized voice cloning built in.

No handoffs.
No brittle pipelines.

Just voice in → voice out, instantly.

What makes this especially interesting is how it was built.

Chroma is trained by FlashLabs, with a focus on real-world latency, natural speech patterns, and voices that actually feel human. Not just readable. Not just accurate. Human.

This is the shift.

Voice AI is moving from:
“transcribe and respond”
to
“listen, think, speak.”

> And that unlocks entirely new use cases:
- Voice agents that don’t feel scripted
- Real conversations at scale
- AI that sounds like your brand, not a generic assistant

If you want to build on top of this, FlashLabs is already making it practical through FlashAI - where teams can create real Voice AI Agents, not just experiments.

This feels like one of those moments where the tech quietly crosses a threshold.

Curious how others are thinking about voice right now - interface, channel, or full product layer?

CHECK IT OUT: https://tryit.cc/HMzo5HL

One of the most common startup mistakes I see is trying to fix slow execution by adding more people.

It feels logical.

More devs should mean faster shipping.

In reality, it usually does the opposite.

> More people means:
More coordination
More opinions
More handoffs
Slower decisions

I’ve watched small, focused teams ship MVPs in weeks while larger teams got stuck debating scope, architecture, and “future-proofing.”

Early on, speed doesn’t come from headcount.

> It comes from clarity.
Clear priorities.
Clear ownership.
Clear definition of what not to build yet.

The best founders I’ve worked with obsess over momentum, not perfection. 

They ship something small, learn fast, and adjust - instead of waiting for the “right” version.

If execution feels slow right now, it’s usually not a talent problem.

It’s a focus problem.

Curious to hear from other founders here - what’s been the bigger bottleneck for you lately: hiring, scope creep, or decision-making?

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Most startups don’t fail because of bad ideas..

They fail because execution takes forever.

I’ve seen this play out again and again.

A founder has a solid idea.
Market timing is decent.
Users are interested.
But then execution slows everything down.

Hiring takes 2–3 months.
The “perfect” dev never shows up.
Agencies over-engineer.
Specs get bloated.
Timelines slip.

Suddenly, a simple MVP turns into a 6-month project.

By the time something ships, one of three things happens:
 • The market has moved
 • The budget is gone
 • The founder is exhausted

The painful part? Most of this is avoidable...

In my experience, startups don’t need:
– Huge teams
– Perfect architecture
– Endless planning

They need:
 – Clear priorities
 – Senior execution
 – Fast feedback loops

That’s it.

The best teams I’ve worked with all followed the same rule:
build the smallest thing that creates momentum.

Ship → learn → iterate.

Not plan → re-plan → still waiting to ship.

This is exactly why we built Y Interval the way we did — around speed, A+ talent, and zero hiring drama. Because execution is the real bottleneck, not ideas.

Curious to hear from founders and builders here: what’s slowing execution for you right now - hiring, tech decisions or scope creep?

A lot of founders ask, “Should we build this ourselves or outsource it?”

That’s usually the wrong question.

The real question is:
Where do we need control, and where do we need speed?

If something defines your core product, you need deep ownership.

If it’s plumbing, integrations, or early MVP work, speed matters more than perfection.

The mistake happens when everything is treated as “core.”

Suddenly nothing ships.

I’ve seen teams stall for months trying to own every line of code, even when momentum mattered more than elegance.

> The fastest startups separate:
What must be owned long-term
What just needs to work right now

That clarity changes hiring, architecture, and timelines.

If execution feels slow, it’s often because this line isn’t clear yet.

Curious how others think about this - what do you treat as core vs commodity in your product?

For a long time, influencer marketing felt messy to us.

Not because creators weren’t good.

But because everything around them was fragmented.

The real issue was that once collaboration started to scale, the execution system began to break down.

Briefs lived in docs.
Approvals happened in DMs.
Pricing negotiations went back and forth.
Tracking lived in spreadsheets.
And once content went live, half the context was already lost.

At a small scale, this setup could barely function. 

But when you need to consistently run dozens—or even hundreds—of influencer collaborations every month, everything starts to fall apart.

What finally clicked for us was realizing the problem wasn’t creators.
It was the lack of a real system around collaboration.

That’s when we started using "Aha"
Not as another SaaS product, but as a complete execution workflow powered by AI employees.

> One place where:
- Large-scale influencer sourcing, filtering, and matching
- Automated outreach and price negotiation based on real data and algorithms
- Contracts, workflows, and compliance execution
- Continuous follow-ups and status management during content production
- Performance is tracked without chasing screenshots

The brand team only needs to make decisions at key checkpoints:
whether to move forward, approve, or reinvest. 

The biggest shift wasn’t just efficiency.
It was a fundamental change in decision quality. 

When everyone works from the same structured brief, execution status is continuously tracked by AI rather than human memory, and outcomes are accumulated as comparable, reusable data assets, influencer marketing finally gains stability at scale.

Curious how other teams here manage creator or partner workflows today - docs, spreadsheets, tools, or pure chaos?

>> CHECK IT OUT:  https://tryit.cc/bKyQqdA

One of the biggest reasons startups stall isn’t bad ideas or weak developers.
It’s bad delegation.

As founders and CTOs, we hire engineers so we can move faster.
 
More hands. More leverage. More output.
In theory.

In practice, what usually happens is this:
You explain a task once.
You assume it’s understood.
You move on.

A week later, it’s half-done.
Or done differently than expected.
Or technically correct but wrong for the product.

Then frustration kicks in.

Here’s the part most founders miss:
delegation isn’t a handoff. It’s a process.

I’ve seen this pattern repeatedly while building and scaling dev teams.

A founder spots an issue.
Maybe a frontend flow feels off.
Maybe a feature isn’t behaving the way users expect.
They message a developer:
“Can you fix this?”
The dev says, “Yep.”

And everyone assumes it’s handled.

But what actually happened?
No shared context
No discussion of tradeoffs
No definition of “done”
No follow-up

So the change technically ships… but the problem doesn’t go away.

Effective delegation in engineering usually follows three stages:
First, it’s my job.
I explain the why, not just the what. I walk through edge cases. I show examples.
Then, it’s our job.
 
We review together. I give feedback. I course-correct early. This is where most learning happens.
Only then does it become your job.

At that point, I trust the execution because the context is already embedded.
This takes time.
Sometimes weeks. Sometimes longer for critical parts of the product.
And that’s normal.

You wouldn’t expect a junior dev to internalize your entire architecture after one meeting.

Yet founders often expect decision-level thinking after one Slack message.
That gap is where velocity dies.

One more thing founders underestimate:
communication decay.
Long docs don’t get read.
Long videos don’t get watched.
Long explanations don’t stick.

Clear, short, repeatable instructions win every time.

The best engineering leaders I’ve worked with do three things extremely well:
They keep instructions simple
They repeat what matters
They follow up consistently
Delegation isn’t “fire and forget.”
It’s guidance, repetition, feedback.

If your team isn’t executing the way you expect, it’s rarely a talent problem.
More often, it’s a delegation problem.

Curious how other founders and CTOs think about this:
what part of delegation has been hardest for you - context, follow-through, or trust?

One of the most expensive decisions a startup can make is hiring “cheap” developers to save money.

On paper, it looks smart.

Lower hourly rate.
More runway.
Less burn.

In reality, the cost shows up later.

Slower delivery.
Rewrites.
Missed deadlines.

Founders spending nights debugging instead of building the business.

Global talent is real - great developers exist everywhere.

But cheap and good rarely overlap for long.

What actually matters isn’t location or rate.

It’s seniority, ownership, and how much hand-holding someone needs.

I’ve seen founders pay twice:
Once for the cheap hire.
And again to fix what shipped.

The best teams I’ve worked with didn’t hire the cheapest devs.

They hired the right ones - and moved faster because of it.

Curious how others think about this:
When hiring globally, what matters most to you - cost, experience, or speed?

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One thing founders underestimate when hiring developers:

The real cost isn’t the salary or hourly rate.
It’s the management overhead.

Every extra sync.

Every unclear requirement.
Every “can you rework this?”

That cost compounds fast.

A senior engineer might look expensive on paper.

But if they:
Need less context
Push back on bad ideas
Ship without constant supervision

They’re usually cheaper in the long run.

The opposite is also true.

Low-cost hires often come with hidden taxes:
Your time.
Your focus.
Your momentum.

That’s why the best teams don’t hire for price.

They hire for leverage.

Curious how others here think about this - what’s been the biggest hidden cost in your hiring experience?

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One lesson that took me longer than it should have:
Most startup problems are framed as “tech problems.”

Very few actually are.

When things slow down, founders blame:
The stack
The tools
The developers

But in most cases, the real issue is alignment.
Unclear priorities.
Vague definitions of “done.”
Too many decisions floating without ownership.

I’ve seen teams rebuild features that technically worked - just because the original goal was never clear enough.

Good engineers don’t fail because they can’t build.
They fail when they’re asked to build without context.

That’s why execution improves dramatically when founders get specific:
What problem are we solving?
Who is it for?
What does success look like this month, not someday?

Once that’s clear, the tech decisions usually follow.

If execution feels harder than it should right now, it’s worth asking:
Is this really a technical bottleneck… or a clarity one?

Curious how other founders and CTOs here think about this.

Project Manager for Kloud-12

I’m a Project Manager and Technical Solutions Estimator with experience managing large-scale facility technology projects across multiple states. At Kloud-12, I help schools modernize communication and safety through our proprietary intercom and paging system, MoreVoice Unity.

My role combines technical assessment, cost estimation, and vendor coordination to ensure every system fits each site’s unique needs. I collaborate with cross-functional teams to align scope, budgets, and timelines while maintaining quality and reliability.

Over time, I’ve developed a deep appreciation for how structured processes, data, and collaboration drive successful outcomes. Whether improving allocation workflows, optimizing vendor performance, or creating clearer documentation, I focus on delivering measurable efficiency and value on every project.

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