Roadmap Pulse
From foundations to frontier systems
This version keeps the single-file flow but reorients the whole experience toward AGI readiness: self-supervision, agentic systems, alignment, scientific AI, multimodal robotics, and post-transformer thinking.
Curriculum
20 Phases
Skill Surface
400+ Skills
North Star
Top 0.01%
Study Workspace
Clean controls for planning, filtering, and review
Keep the roadmap readable as it grows. Filter by depth, hide what is already done, revisit starred skills, and jump back into the exact skill you were working on last.
Last skill: none
Search: off
Review queue: 0
Backup: never exported
Tier Filters
View Controls
Use favorites as a personal review queue, and hide completed skills when you want a tighter working view.
Search and Snapshot
Saved notes0
Starred skills0
Completed skills0
Next Best Action
Focus System
25:00
Current Level
1
Curious Builder
0 / 300 XP
Total XP: 0
Progress Stats
Phase Mastery
Focus and Momentum
Recently Unlocked
Recent Completions
Starred Skills
Tier Coverage
Daily Execution
Weekly Consistency
AI Architect Skill Map
Learning System
Milestones and ROI
Portfolio Builder
Projects and Boss Fights
Roadmap View
The full learning arc
The phases stack deliberately: code and math first, then learning systems, then foundation models, then agents, RL, safety, hardware, scientific AI, neuro-symbolic reasoning, and AGI-level research questions. Every phase also includes real projects, a visible boss fight, and a longer-term career signal so this stays useful for years.
Why This Path Wins
Structured, deep-work, project-first growth
This system is designed to compound for the long run: clear sequence, visible focus, measurable wins, and shipped output instead of passive content consumption.
Structured path instead of random tutorials
Focus system with Pomodoro, hours, and execution discipline
Gamification through XP, streaks, milestones, and boss fights
Project-first learning with portfolio-ready output
Industry-ready skill blend across ML, systems, cloud, and MLOps
20 phases
60 projects
20 boss fights
Anti-Failure System
Guardrails against wasted years
The point is not just to study more. The point is to stop drifting, force real execution, and keep architecture thinking in the loop from the beginning.
No tutorial-only learning
No random path switching
No skipping projects
No ignoring system design
Certifications
Industry signal boosters
Certifications are optional, but useful when you want an external signal on top of shipped work and portfolio evidence.
AWS Machine Learning Specialty
Cloud + ML platform credibility
Cloud + ML platform credibility
Google Professional ML Engineer
Production ML engineering signal
Production ML engineering signal
Azure AI Engineer / Architect
Enterprise AI delivery signal
Enterprise AI delivery signal
Industry Awareness
What to keep watching
GenAI products, agents, retrieval, evals, and guardrails
Inference cost control, routing, finetuning, and platform shifts
Safety, privacy, governance, and deployment risk
End Goal
AI Architect role preview
Design data to deployment AI systems
Balance cost, latency, reliability, safety, and business value
Lead architecture choices and technical roadmaps
Timeline to 2035
Where you are heading
2026-2027: Foundations
2027-2029: ML and deep learning
2030-2032: Systems and MLOps
2033-2035: AI Architect