Cofounder @ Morning Brew / Host @ Founder's Journal

Alex Lieberman

I’m saying fuck it. 

There’s not enough time to scale my recruiting team so I’m making everyone on earth a recruiter.

I have to hire 120+ people at Tenex by year-end.
- 70 AI engineers
- 35 AI strategists 
- 15 other roles

If you have a strong network, what I’m  offering you the opportunity to make $100,000 as a side hustle.

If:
- You refer a candidate (form below)
- Candidate applies for role
- We hire them
- They stay 90 days

We pay you $10,000…per hire.

I want to make this huge. 

Plans for the future: Referrer website with any info you need about Tenex/our roles. Leaderboard of our referrers. Top referrer gets sent on a baller vacation. 

Time to roll out the red carpet. 

All the info you need below…

Cofounder @ Morning Brew, Tenex, and storyarb

This guy made 40 Facebook ads, 100 landing pages, booked himself on 4 podcasts, and wrote 3 guest blog posts. In a single day. 

People called him a fraud. There was literally a Polymarket bet on whether he's a con artist. 

So i asked him to prove it to me. And he did. 

Here's Cody Schneider's actual system for AI-enabled paid marketing:

1) He uses Perplexity to search Reddit for his ICP's actual pain points in their own words. Not what he thinks they care about, what they've literally said online.

2) He feeds those pain points into Claude, which generates 40 ad variations, titles, supporting copy, and the actual creative using React components exported as PNGs via a library called HTML-to-canvas.

3) He tests all 40 variations in a CPC campaign on Meta. $100 over 3 days. Cheapest cost-per-click wins.

4) Winners get matched landing pages. He uses an open-source CMS called Strapi connected to Claude Code via API, so he bulk-generates a landing page for every winning ad angle. Same headline on the ad and the page = higher conversion.

5) Once he finds a winning concept, he scales it — AI avatar UGC via HeyGen, upgraded with V3, and only brings in a human creator if the AI version plateaus.

The whole thing runs on Claude Code + APIs + a .env file with all his keys.

No engineering team. Just him on multiple desktops with multiple Claude agents running simultaneously.

His best line: "you're not just hiring me anymore. you're hiring me and the 30 agents behind me and all the personal software i've built."

Jack Dorsey announced that Blocks (owner of Square, Cash App, etc) would be firing 40% of the company’s 10,000 employees because of…AI.

The largest % layoff of a S&P 500 company ever.
People freaked out.
The company’s stock jumped 20%.
People freaked out more.

Here’s my hopefully balanced but constructive take on the whole thing:

1) Jack has consistently been ahead of his time and I believe he is early this time, too. What he’s doing is the canary in the coal mine for so many other businesses.

2) We’re going to see various flavors of AI-related layoffs accelerating. the “using ai as a scapegoat to fire underperformers” flavor. the “our business is failing we need to cut costs” flavor. the “let’s pair 10x employees with ai” flavor.

3) A move like this will only work for certain companies right now. Flat structure, meritocratic reward system, high agency employees.

4) Trying this at non-high performance companies will lead to what I like to call “the boomerang”. Company lays off a lot of people to be replaced with AI. Talent density isn’t high enough. The weight of bureaucracy is strong. Output/customer satisfaction dips. Company reverses course (cough IBM).

5) The markets rewarded Blocks for the announcement and people are freaking out. The stock performing isn’t a harbinger of knowledge work’s demise. It’s simply the reaction to a company lowering its expenses 40% in a day.

6) Does this worry me? No more than any intellectually honest person worries about the impact of AI. Will this technology create structural impacts so certain areas of digital work? Yes. Will it also create new anticipated and unanticipated employment opportunities for humans? Also yes.

No alternative text description for this image

If you're worried you're behind on AI transformation...you probably are.

I have studied 100+ companies AI-readiness & every company can be mapped to one of these 9 levels:

Level 1 (Awareness): 
- leadership recognizes AI as strategically important, but it has not yet changed how the company operates.

Level 2 (Shadow AI): 
- employees independently use AI tools to improve their own productivity, but usage is informal, inconsistent, and largely ungoverned.

Level 3 (Tool Standardization): 
- the company formally approves and deploys AI tools through IT and security, reducing risk but not yet transforming workflows.

Level 4 (Workflow Integration): 
- ai becomes embedded within defined processes and operating workflows, improving consistency and measurable output.

Level 5  (Business-Aware Systems):
- ai systems are grounded in internal data and company-specific definitions, enabling context-aware analysis and decision support.

Level 6  (Supervised Autonomy): 
- ai systems begin executing tasks within guardrails and human oversight, shifting people from doing the work to supervising it.

Level 7 (Role-Based AI Teammates): 
- ai collaborators are aligned to functional roles, and roles are redesigned assuming AI participation in daily operations.

Level 8 (Unified Intelligence Platform):
- the organization operates from a shared intelligence layer that provides a consistent, company-wide source of truth.

Level 9 (Adaptive Organization):
- the company continuously adjusts decisions and operations through closed-loop AI feedback systems, with humans guiding strategic intent.

I thought AEO (read: SEO for LLMs) was a hunk of bullsh*t. 

And then i spoke to Kipp Bodnar, CMO of HubSpot, who knocked the skepticism out of me. 

His first jab: In one year, they grew AI search traffic by 15x. It went from rounding error to real line item on the P&L.

His second jab: AI search conversion rates are 5x higher than Google search. On some queries, 13x higher.

His hook: 60% of AI citations don't come from the top 20 Google results. The companies dominating Google aren't automatically winning in AI search, which creates a huge advantage for early adopters. 

He then took me through his process for crushing AEO & seeing results in days, not months (like SEO): 

1) Grade: your current AEO presence across ChatGPT, Perplexity, and Gemini with a tool like Hubspot's AEO grader. 

2) Restructure: your content into chunked, answer-first pages with natural language headers. 
- one consolidated page, not 8-10 interlinked pages
- lead with natural language questions like "What is X?"
- 1-2 paragraph sections, not 1,000 word sections
- table of contents on a single page

3) Separate: Mentions from citations and optimize differently for each
- Mention = when AI references your brand or product in its answer but doesn't link to you
- Citation = when an AI references you AND links to your page

4) Open up: your information — ungate content, build Reddit presence, make pricing public
- Optimize for entity understanding: how well do AI models understand what your company does, based on every signal from Reddit to review sites, awards lists to help docs

5) Tool up: with AEO-specific software to track prompts and share of voice
- Check out Xfunnel or Limey[.]ai

6) Rethink attribution: measure source of customers, not source of traffic. 
- Metrics that matter: share of voice, citation count, sentiment, mention frequency, source of customers not traffic

Check out our full convo about AEO below 👇

I've been asking $100m+ company execs one question: 

"What is the #1 thing slowing/stopping your company's AI transformation?" 

A non-exhaustive list of responses: 

1) Data quality and connectivity of systems. Plus systems that play nice with AI.
2) Lack of leadership buy-in and implementation
3) Data governance restrictions.
4) Willingness of staff to adopt AI.
5) Incurious culture. Lack of knowledge of the current state of AI
6) Tooling doesn't have API access; team is still learning how to use LLMs. 
7) Industry regulation/privacy. 
8) Data quality and lack of a comprehensive AI system across the full company. 
9) Unclear ownership across teams.
10) Time to actually build solutions. 
11) Mixed AI literacy levels across teams. 
12) No clear strategy / I'm starting the initiative from scratch. 
13) Quality output. 
14) Upskilling developers.
15) Silos. 
16) Data Security and Security Guideline unclear.
17) Lack of training.
18) Data quality is unclear across multi-product teams.
19) Time. 

What would your answer be to this question?

We truly have the most cracked AI engineers in the world. 

They are all VERY opinionated about their tech stacks, which change constantly.  

Here's the current stack for one of our engineers: 

1) Typescript - everything eventually becomes JavaScript, and you can basically build everything with typescript. Types are good for agents.
2) Ruby on Rails - RoR curious because it's very structured, which is really good for agents (David Heinemeier Hansson)
3) Ghostty - nice terminal, native pane splitting, big context copy and pasting (cc: Mitchell Hashimoto)
4) Cursor - agnostic harness to switch between models
5) Codex CLI - daily driver / the Mac app was cool for a week but CLI is more functional (cc: OpenAI) / pro: high quality code / con: trips over its own feet, too literal
6) Claude Code - use when need something to just happen. pro: will get you a result quick / con: sometimes it’s messy (cc: Anthropic)
7) Wispr Flow - work way faster yapping to text, especially when WFH
8) Raycast - better spotlight with clipboard history, snippets, custom scripts
9) OpenClaw - place to keep structured data, stay organized, handle certain tasks
10) Vercel - super smooth for hosting, prototypes, etc
11) Neon Postgres - really easy to integrate with a vercel project + preview deployments are great for agent to raise a PR & test in-browser

P.S. if you think you're a cracked AI engineer & want to surround yourself with the best & brightest, we're hiring at Tenex. 

P.P.S. the cracked engineer behind this stack is CJ Hess. he's absolutely worth a follow for the latest and greatest in ai engineering.

📌 Schedule a consult → breakroombuddha.com/partnership
✉️ partnerships@breakroombuddha.com

My #1 Goal: Disrupting autopilot in education-to-employment systems.

My work lives between the education and employment gap, where people are asked to make life-shaping choices without clear insight into their skills, interests, or how opportunity systems actually work. This gap is where talent is most often misjudged, not because people lack ability, but because systems recognize effort too late.

I build programs, tech products, and measurement frameworks that surface early signals of career intent, enabling regions to reduce talent & job mismatch, strengthen talent pipelines, and plan more responsively. Most recently, I built Scouta, a predictive labor market intelligence tool, that translates career curiosity into actionable regional insight.

I do this work because the future of work isn’t just about jobs, it’s also about, "The Future of Talent," and whether regions learn to see talent early enough to keep it.

~~~
I’ve led large-scale system builds across education, workforce development, and talent pipelines, including:

📌 Architecting and launching a federally backed AI literacy education initiative on track to serve 400,000 learners

📌 Building scalable, AI-enabled career guidance infrastructure through proprietary technology, Scouta and Career CoPilot, now used by classrooms, career counselors, and learners

📌 Designing and leading multi-cohort college and workforce readiness programs for first-generation high school and college students


Across my work, I focus on:

- Helping regions build future-ready talent pipelines
- Translating workforce trends into practical, skills-based readiness
- Designing clear, navigable paths from learning to employment
- Rapidly building and launching programs that work in real-world settings
- Telling clear, evidence-based stories that help communities understand, and invest in talent


💼 Organizations I’ve Worked With: Uber, Warner Bros. Discovery, ACT, CUNY, Google Women Techmakers, and Morning Brew

My Causes:
❤️ Google Women Techmakers Ambassador
❤️ Scholastic Innovation Lab Ambassador

Let’s connect if you’re shaping early-talent pathways, strengthening youth career readiness ecosystems, or rethinking how workforce systems identify and develop talent.
--
In constant pursuit of my Jīva (my living essence) and helping others discover theirs.

Deja White

Tonight was powerful!!

I introduced the girls to engineers during Discovery Lab (Tulsa Children's Museum)'s “Introduce a Girl to an Engineer” Night

 and not just any engineers…

✨ Black Women Engineers!!✨

Happy Black History Month 😁 


But I didn’t stop there, we explored every single discipline of S.T.E.M.

We explored the stories of Black women inventors, scientists, cosmetic chemists, NASA astronauts, mathematicians, and trailblazers across STEM who changed the world.


Here are just a few of the women the girls learned about tonight:

💁🏾‍♀️ Aprille Ericsson
💁🏾‍♀️ Patricia Bath
💁🏾‍♀️ Marie Van Brittan Brown
💁🏾‍♀️ Evelyn Boyd Granville
💁🏾‍♀️ Christine Darden
💁🏾‍♀️ Annie Easley
💁🏾‍♀️ Sarah E. Goode

(Seriously… look them up. 🔎)

And we didn’t just talk about these women, we built, just like they did!

1️⃣I introduced them to Scouta by Breakroom Buddha first to help them explore even more STEM careers that were related to the women they learned about.

THEN...

2️⃣ I exposed them to the “T” in STEM by teaching them how to 'vibe code", and then I showed them their code. And for many, it was their first time ever seeing what real code looks like.

The girls were floored!


I know seeds were planted tonight and I'm so excited to see how the future engineers, inventors, technologists, and innovators will change the world.

~~~~~~~

I’m excited to continue hosting my Scout It & Build It session! If you missed this one tonight, there will be more.


And if you have a class, career day, or upcoming event and want your students to explore vibe coding, AI, and STEM careers in a hands-on way, let’s connect! I’ll bring my session (and the energy), and your students will walk away with something they built themselves.

📌 Déja White 

*All thoughts and programming are my own.

📌 Déja White

Future of Talent Systems Architect | Education-to-Work Readiness | Workforce Intelligence

I'll be in Austin for SXSW EDU! If you'll be there, shoot me a message and let's connect IRL.

Learn more about my mentor session here: https://lnkd.in/g8rqwKRP

YOU ARE EXACTLY WHO YOU THINK YOU ARE.




Sorry for screaming, but this took me a while to understand, and I want you to get it quicker than I did. 🥲


For a long time, I dismissed the things that came naturally to me: 

the blend of creative marketing, communications skills, community engagement, tech, web development, and now AI & “vibe coding.” 

Because all of these things feel so easy to me, I assumed they weren’t that valuable.

Then I crossed paths with a parent at an event I hosted a session at and she said something that stuck with me:

"Just because something is easy for you doesn’t mean it’s insignificant."

She said this after I kind of downplayed what I was teaching kids at my booth.


And I immediately snapped out of it. I learned a while ago that the work that you do, especially if it's for money, is supposed to be easy (to you). 

When it feels easy and natural, it usually means it’s where you’re meant to operate.

This mindset shift changed how I see my work. 

We often undervalue our “zone of genius” because we don’t struggle there. We think real value must feel hard, complex, or draining. But the opposite is often true.

Your zone of genius is the space where:
🧠 You move fast without forcing it
🧠 You connect ideas naturally
🧠 Other people see magic where you see “normal”
🧠 Your energy increases instead of drains


The work you do for money should live in this zone most of the time, not occasionally, not as a side thing, but consistently. 

Whatever you do, make sure you:

📌 Teach in that zone.
📌 Build in that zone.
📌 Create in that zone.
📌 Get paid in that zone.
📌 Stay in that zone.

What feels effortless to you is someone else's weakness. Capitalize on that, always!

📌 Déja White 
*All thoughts are my own

Machine Learning Engineer | Real-Time AI Systems | Deploying Production-Ready ML Systems

How I Built a Real-Time Driver Drowsiness Detection System Using Computer Vision
Body:
Driver fatigue is one of the major causes of road accidents.
So I built a real-time drowsiness detection system using computer vision and deep learning.
Here’s how it works:
• Detects face and eyes using OpenCV
• Monitors eye state (open/closed) frame-by-frame
• Triggers an alert when prolonged closure is detected
• Runs in real-time with live webcam inference

Tech Stack:
 PyTorch | OpenCV | YOLO | Real-Time Video Processing

Key Challenge:
Handling lighting variation and false positives during head movement.
This project strengthened my experience in building AI systems that work beyond just notebooks — real-time, deployable solutions.

I’m currently open to ML / Computer Vision roles.

taplio

The Battle

Alex Lieberman

Deja White

Followers

Posts

Engagements

Likes

Performance ScoreAlex Lieberman's LinkedIn Performance

Performance ScoreDeja White's LinkedIn Performance

Ready to grow your LinkedIn presence?

taplio

The Battle

Alex Lieberman

Deja White

Followers

Posts

Engagements

Likes

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Alex Lieberman's LinkedIn Performance

Performance ScoreDeja White's LinkedIn Performance

Ready to grow your LinkedIn presence?

Performance ScoreAlex Lieberman's LinkedIn Performance