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Personal Brand

Identity, frameworks, pitches, content pillars, and publishing strategy

Brand Identity

Tagline

AI Without the Hype

Core Belief

Most leaders make AI decisions out of hype or fear. Both are wrong.

Alternate Lines to Rotate

1

AI is a tool, not a strategy. If your AI strategy starts with a tool, it's not a strategy.

2

The companies winning with AI aren't the ones with the best tools. They're the ones who understand the problem.

3

The hardest part of AI isn't the technology. It's knowing when to use it.

4

The gap between AI demos and AI in production is where businesses fail.

5

AI should make your business simpler, not more complicated. If it doesn't, you're doing it wrong.

6

Every AI decision is a business decision. Treat it like one.

7

Good AI decisions come from understanding systems, not following trends.

Named Enemies

AI Theatre

Demos, buzzwords, pilots that die after the presentation

Format: AI theatre vs AI plumbing (show vs substance)

Tool-First Thinking

Buying AI tools before understanding jobs-to-be-done

Format: Tool-first vs problem-first (buying vs understanding)

Prompt Influencer AI

Tips and tricks that never ship to production

Format: Demo thinking vs production thinking (what looks good vs what works)

Vendor-Led Strategy

Letting salespeople define your AI roadmap

Format: Vendor roadmaps vs real needs

The 4D AI Adoption Filter

A named, drawable, repeatable framework. Every post is a slice of this.

Data

"Do we have the data?"

No data = no AI. Audit before you build.

Can we?

Demand

"Does it solve a real problem?"

If the problem isn't painful enough, the solution won't stick.

Should we?

Delivery

"Can we deploy AND maintain it?"

Shipping v1 is 20% of the work. The other 80% is keeping it running.

Will it work in practice?

Defensibility

"Is this durable or a gimmick?"

If a competitor can copy it in a week, it's not a moat.

Will it last?

NSFAG Pitch Variations

30-Second Networking

I'm Doron. I build data and AI systems at Meta -- automated platforms, pipeline frameworks, the infrastructure that makes AI work at scale. I also teach GenAI at IE University to executives and MBA students. What I've found is that most people are making AI decisions based on hype or fear, and both lead to bad outcomes. So I write and teach about making AI and automation practical -- AI without the hype.

6 Content Pillars

1

Building AI at Scale

What building data platforms and automation systems at a company like Meta teaches about AI (generalized, no proprietary info). Includes data architecture thinking, platform design, how systems actually work.

2

AI & Automation for Leaders

Practical frameworks for evaluating AI tools, automation opportunities, and data-driven decisions. The "without the hype" pillar.

3

From the Classroom

Real questions from executives/MBA students/undergrads, answered. What leaders and students actually struggle with. Includes wins like "my students built a functional AI Telegram bot in 12 sessions."

4

AI Myths vs. Reality

Contrarian takes debunking AI hype and fear. What works, what doesn't, what's overhyped.

5

The Automation Playbook

Frameworks for when/what/how to automate. Principles that are tool-agnostic, with current examples (Claude Code, Airflow, Make.com, etc.) for relevance.

6

Building with AI

Practical showcases AND process of building: SaaS pages, chatbots, automations, pipelines. "I built X with Y -- here's how and what I learned." Includes the thinking process, not just finished products.

Book Concept

AI Without the Hype: A Practical Guide for Leaders Who Want to Get AI Right

Working title -- Month 6-12 | 15-25 EUR

Format

35,000 words, practical frameworks with case studies

Approach

Draft emerges organically from 6 months of LinkedIn posts and newsletters

Core Idea

Bridge the gap between AI engineering reality and business decision-making

Publishing Strategy

Weekly Content System (4 hr/week)

Sunday evening

Batch-write 2-3 LinkedIn posts for the week

1.5-2 hr
Wednesday

Write and send weekly newsletter (repurpose best LinkedIn + 1 exclusive)

1 hr
Throughout week

Engage: 10-15 thoughtful comments on others' posts

30 min
Monthly

Review metrics, identify top-performing topics, adjust

30 min

CTA Rotation

1

"I'm collecting AI adoption problems to cover in next week's newsletter -- reply with yours."

2

"If you want the 1-page 4D Filter framework, comment 'framework' and I'll send it."

3

"Follow for more AI without the hype."

4

"Save this for your next AI vendor meeting."

5

"Share this with someone making an AI decision right now."

6

"Subscribe to my newsletter for the deep-dive: [link]"

Content Repurposing Chain

IE University lecture -> 3-5 LinkedIn posts -> Best post becomes newsletter deep-dive
Meta work patterns -> Generalized frameworks -> LinkedIn post -> Newsletter
Automation project -> 'How I built this' post -> Tool spotlight -> Course material

Brand Rules

Tagline everywhere: "AI Without the Hype"

Public face: Meta engineer + AI professor (never mention Rebundle/Wadoom publicly)

IE University reference: Mix it up -- sometimes "IE University" by name, sometimes just "I teach AI to executives and MBA students"

Implicit audience: Leaders and founders (not stated explicitly -- let them self-identify)

Content type: Idea promotion (frameworks, insights, practical knowledge) + practical demos/builds

Tone: Expert practitioner -- "Here's what I learned building this at scale. Here's how you can apply it."

Content depth: Accessible + occasional technical deep dives for credibility

Show builds: Showcase real things you've built as proof of expertise

Tools: Pick individual tools from your stack and showcase them one at a time

KPI path: 5K-50K followers in a high-value niche with high conversion

Language: English only

Time: 3-5 hours/week

No em dashes -- use double hyphens instead

Every post ends with a CTA (rotate between variations)

Reference the 4D Filter when relevant but don't force it

Never reuse closing lines across posts