AI & Data Career System
Practical guides for every stage of a Data & AI career — from making the move into the field, to landing the right role, negotiating the right comp, and building the visibility that brings opportunities to you.
Updated April 2026 · 2 free playbooks
Role Transition Roadmaps Free
Step-by-step paths into every major Data & AI role. The fastest transitions combine your existing background with targeted skill additions — dual credentialing beats bootcamps by 3–5x in interview conversion rates.
SWE → AI Engineer
Your coding skills are the moat. The gap is LLM API patterns, RAG architecture, vector databases, and evals — not software engineering fundamentals.
- The SWE → AI Engineer 90-day plan
- Skills to add — what matters vs what doesn't
- Portfolio projects that signal readiness
- How to position SWE experience in AI interviews
- Full stack system architecture — every layer, every technology, PM vs SWE ownership
Data Analyst → Data Scientist
The gap is probabilistic thinking and model deployment — not Python. Most analysts already have the hardest part: business context and data intuition.
- The DA → Data Scientist 90-day plan
- Statistics and ML concepts that close the gap
- End-to-end portfolio project scaffold
- How to tell the transition story in interviews
PM → AI Product Manager
Add technical vocabulary, one shipped AI feature, and the ability to write a model card. AI PMs who can do this get 40% more interviews than those who can't.
- The PM → AI PM transition plan
- AI vocabulary every PM must know
- Portfolio moves that land AI PM interviews
- Positioning existing PM work for AI PM roles
Domain expert → AI specialist
Domain expertise is your unfair advantage. Healthcare AI, legal AI, and fintech AI desperately lack people who understand both the domain and the model.
- The domain expert → AI specialist path
- The technical minimum by domain
- Leading with domain, not apologizing for it
Academia → industry AI
Translate publications into business value during interviews. "Improved F1 by 3 points" → "reduced false positives that cost X per incident." Reframe, don't hide.
Personal Brand for AI Free
Build the visibility that brings opportunities to you. In a crowded AI market, being technically strong is necessary but not sufficient. Personal brand is what makes hiring managers remember you and clients reach out.
LinkedIn content strategy
- The 5 LinkedIn post formats that perform in AI
- Hook writing for AI content — with examples
- Posting cadence that builds habit without burnout
- Why failure posts outperform tutorials — and how to write them
Building in public
- The building in public playbook for AI practitioners
- What to share, what to protect, what to lead with
- How audience compounds around journey, not launches
Technical writing strategy
- One deep technical post per month beats four shallow ones
- SEO-optimized technical post title framework
- Where to publish — Medium, Substack, personal site, LinkedIn
Newsletter launch
- How to launch a Data & AI newsletter from zero
- The issue format that retains subscribers
- First 100 subscribers — the exact tactics that work
- Beehiiv vs Substack — which to choose and why