Noah Habtemichael

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9 hours ago | [YT] | 1

Noah Habtemichael

AI Adoption Event NYC
Great open mic where various people shared use cases for AI Agents they built

The AI Adoption space is an interesting and constantly evolving space

Right now companies are stuck between overspending on AI tokens and having a proper adoption

A system of upskilling that creates use cases for each employee and tracks ROI becomes that middle ground that would drive adoption while proving returns

& from the core at GenAIx what got us started to empowering humans in this transitionary period led to that exact system

Team Human, GenAIx

1 day ago | [YT] | 1

Noah Habtemichael

Gen Z Entrepreneurs & Creators in NYC

Great seeing more & more Gen Z entrepreneurs in NYC

Gen Z entrepreneurs building startups, running ecom brands and agencies

Bringing more creative and bold energy into rooms

The world economy is going through a transition, and Gen Z will need to play a huge role in taking responsibility for a better future

Great meetup hosted by GenZtea

Upskilling humans and workforce education is key for the next phase of a better future!

Team Human | GenAIx!

2 days ago | [YT] | 3

Noah Habtemichael

Starting a company in NYC is not for the faint hearted.

A prominent 2026 WalletHub study ranked NYC last out of 182 US cities as the worst place to start a career, based on 25 different metrics.


But that’s exactly what makes NYC special.
If you can make it here, you can make it anywhere.


Starting out in the hardest place forces you to learn and grow fast. You become sharper, more resilient, and ultimately more competitive.


Moving here at 22 and building GenAIx in NYC for the past two years. has been an amazing growth experience of my life, and now this city feels more like home than anywhere else


Growth comes with discomfort, To seeking discomfort!

Team Human,GenAIx

3 days ago | [YT] | 1

Noah Habtemichael

Founders & Funders NYC mixer at Seville NoMad,

the vibe was no panels. Just builders & operators talking about what's next

The part of NYC with ambition, pragmatism, and people who actually ship.

At GenAIx, we’re not here to experiment with AI for the sake of it.

We’re here to build structure around the fragmented $350B corporate upskilling space.

The AI tools are there, but the way they are being used is not where it’s moving productivity, where it’s saving cost, where it’s impacting revenue.

Stuck in “AI pilots” with no clear path to P&L.

We’re building a system that upskills teams with role‑specific workflows, tracks how those skills translate into real productivity and efficiency, and quantifies ROI per department.


That’s the shift from pilot to production: structure,
clarity,
& measurable outcomes.

Thanks to Peiheng W. for bringing many interesting people into one room.

If you’re building in NYC and care about the next wave of human‑AI work, we’re in this together.
Team Human, GenAIx!

4 days ago | [YT] | 1

Noah Habtemichael

NYC to the world

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1 week ago | [YT] | 2

Noah Habtemichael

Current state of AI Adoption.Full Article:
www.linkedin.com/pulse/new-employee-level-pressure…

1 week ago (edited) | [YT] | 1

Noah Habtemichael

NYC Postgres meetup at Amazon’s JFK office, the talk was all about “Migrating at Scale

A Firestore to Postgres Story

We walked through zero‑downtime migration from a live Firestore database to Postgres, and came away with a practical playbook:

-Planning the migration with clear stages and rollback paths
-Keeping the live system running while data shifts
-Tuning Postgres for scale and performance
'Handling schema changes, connectivity, and observability through the whole process


It was a strong reminder that the hard part of scaling isn’t just choosing a database; it’s the execution around migrations, reliability, and ops.

That’s exactly the kind of “beyond the tool” mindset we need in corporate upskilling.

At GenAIx, we don’t just train people on AI tools; we build systems that upskill teams with role‑specific workflows, track how those skills translate to productivity and efficiency, and quantify ROI per department.

The shift from pilot to production is the same: structure, clarity, measurable outcomes.



Team Human, GenAIx!

1 week ago | [YT] | 1

Noah Habtemichael

The new Employee-level pressure & “productivity theatre” for proving ROI on AI Tools

For employees the trend shows up as a demand to both adopt AI tools and prove that they are delivering value.

Employees are increasingly spending more time producing stories, dashboards, and self‑reported time savings to justify AI licenses, contributing to what analysts describe as a shift from counting “users” to demanding “auditable outcomes.”

There are also signs of tension around monitoring:

internal tools that track AI usage can create competitive pressure among employees and may incentivize superficial tool use just to hit metrics rather than thoughtful integration into workflows.

At the same time, many people quietly adopt unapproved AI tools because official systems don’t meet their needs, making it harder for organizations to accurately measure where productivity gains actually come from.

The Token cost story:

The growth of usage‑based, token‑priced LLMs has created a new kind of stress:

Highly variable, hard‑to‑forecast AI bills that can reach six or seven figures per year.

Several high‑profile firms have publicly struggled

Uber reportedly exhausted its entire 2026 AI coding budget within four months, and Microsoft has scaled back some third‑party coding tools after compute and token costs exceeded the payroll of the engineers using them.

In response, enterprises are scrutinizing token consumption far more closely, tracking metrics like
cost per workflow,
cost per transaction,
cost per document reviewed,
and cost per software change delivered, and putting dashboards, thresholds, and approval mechanisms around expensive model use.

Audit and assurance teams are now reviewing large AI programs weekly or fortnightly to prevent budget overruns, making cost and ROI measurement an ongoing governance requirement rather than a once‑a‑year exercise


Boards and finance teams are pushing for frameworks that distinguish low‑value, low‑complexity tasks (e.g., simple summarization) from high‑complexity, high‑impact work (e.g., multi‑step coding or decision support) because the ROI profiles differ dramatically.


Many organizations accept that they will continue investing in AI even without immediate returns,but are “instrumenting to understand where it goes,” building infrastructure to track spend and value at finer granularity.

AI’s early impact is less about replacing workers and more about reshaping tasks and improving innovation, product development, and customer engagement, which are inherently harder to measure and thus add to the anxiety around proving ROI.

For leaders, departments, and employees, the core trend is that AI is entering a phase of accountability: the excitement over capabilities is giving way to a requirement to show concrete, auditable productivity and financial outcomes from every tool and agent that gets deployed

1 week ago | [YT] | 3

Noah Habtemichael

Andrew Yeung'sTech Rooftop Mixer last week at Arlo Williamsburg,

A room full of founders, operators, and investors, preppinf for what’s coming next, not just what’s happening now.

That’s the part of New York that hits closest to home. This city keeps pulling builders who want both ambition and real outcomes.


At GenAIx, we’re building exactly for that.
Corporate upskilling is a massively fragmented $350B space. AI is everywhere, but padding it with “AI” is not enough.

Companies need to know what AI is actually doing for them.
We’ve built a system that:
Upskills teams with role-specific workflows, not generic videos
Tracks how those skills translate into productivity, efficiency, and revenue

That’s the shift from pilot to production: structure, clarity, measurable outcomes.

Team Human, GenAIx

1 week ago | [YT] | 1