Master the foundations first
Linux, programming, mathematics, and computer science - so I am never dependent on a single tool or AI assistant to think.
Tech journey · Gothenburg
Phase 01 · In progress
Tech Journey AI Generalist
I am aiming to become an AI Generalist and Independent Platform Builder.
I am building myself into a broad, production-capable AI generalist - someone who can research a problem, design a product, ship software, operate infrastructure, and use AI responsibly end to end.
I am currently in Phase 01 - Foundations. Building Linux, programming, math, and software craft in my personal time.
This is a long self-study journey in my personal time - after school, training, and life. No shortcuts. Real practice, real projects, real proof.
Phase 01 · In progress
Who I want to become
Not a single narrow specialty only - a builder who can take an idea from zero to a real, secure, measurable platform. Research the problem. Design the product. Build web and mobile clients. Engineer backends and data. Deploy and run cloud systems. Add machine-learning and generative-AI features. Grow and measure what ships.
The goal is independent end-to-end capability for small and medium digital platforms - a “one-person army” in the best sense: full-stack ownership with humility. I still respect specialists for safety-critical, regulated, or very large-scale systems. I want depth and range, not shortcuts.
AI
Why this matters when AI is everywhere
AI will touch almost every job, product, and habit. Staying relevant is not about fearing the future - it is about becoming someone who can build with AI, evaluate it, secure it, and keep learning when tools change.
- Build with AI
- Evaluate honestly
- Secure systems
- Keep learning
- Stay human
Goals
My goals to stay relevant
Six principles I hold while I study on my own time - so I stay useful as the tools keep changing.
Ship full products, not demos only
Web, mobile, backend, databases, cloud, security, and operations - so I can own the whole path from idea to production.
Use AI as leverage, not a crutch
Learn to research with AI, build with copilots and agents, then prove I understand the work: tests, defenses, rollbacks, and oral clarity.
Stay ethical and human-centered
Privacy, accessibility, sustainability, and respect for users - because technology without humanity is empty.
Keep a living portfolio
Document, version, measure, and publish real builds. Evidence over claims. Progress over perfection.
Never stop learning
When AI absorbs routine tasks, the winners will be people who design systems, ask better questions, and adapt faster than the tools alone.
Path
Overview of my path
A long, mastery-gated self-study map - four deliberate phases of practice in personal time. Right now I am in Phase 01 - Foundations.
Now · Phase 01 I am currently in Phase 01 - Foundations. Building Linux, programming, math, and software craft in my personal time.
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01 Phase 01 Now
Foundations
Computing literacy, Linux, programming, math, and software craft - the ground I stand on.
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02 Phase 02 Upcoming
Product software
Web, backend, databases, distributed systems, and mobile - building real applications people can use.
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03 Phase 03 Upcoming
Platform & operations
Cloud, DevOps, Kubernetes, reliability, and internal platforms - so systems stay alive under pressure.
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04 Phase 04 Upcoming
Intelligence & growth
Security, data, machine learning, LLMs, agents, evaluation, and digital growth - AI that is useful, measured, and safe enough to ship.
When I’m done
Skills I aim to achieve
By the end of this self-study journey - built in my personal time across these phases - I want production-ready range, not just certificates on a wall.
These are target capabilities inspired by a full AI-generalist path. I will earn them through deliberate practice, labs, and shipping real projects outside school hours.
Systems & Linux
Administer and automate Linux systems and networks with confidence and good hygiene.
Programming craft
Code solidly in Python, JavaScript/TypeScript, Bash and related tools - plus SQL and clear configuration.
Web & mobile products
Design accessible experiences and ship secure web and mobile clients people actually enjoy using.
Backend & data
Build APIs, services, realtime workflows, and reliable databases - with backup, recovery and search in mind.
Cloud & DevOps
Architect cloud systems, CI/CD, infrastructure as code, Kubernetes, observability and SRE habits.
Security mindset
Threat-model, test and harden web, mobile, cloud, supply-chain and AI systems - privacy first.
Data & analytics
Build governed analytical, batch and streaming data products that support real decisions.
ML & generative AI
Train, evaluate, deploy and monitor ML; build LLM apps, RAG, agents and local inference with accountability.
Product & growth
Research a market, launch a platform, measure growth, and improve conversion without empty hype.
AI as leverage
Use AI engineering tools productively while keeping human understanding, rollback ability and responsibility.
Platform thinking
Treat internal platforms as products - golden paths, templates, policy and self-service for builders.
Portfolio proof
Document, demo and defend real work - code, tests, runbooks and honest retrospectives.
Outcome
What “done” means to me
When this multi-phase personal journey is complete, I want to be able to say - with proof, not slogans:
- I can take a real problem from research to a running, secure product.
- I can own web, mobile, backend, data, cloud and basic ops end to end.
- I can add ML or generative-AI features only when they are justified and measured.
- I can explain my architecture, tradeoffs and failures without hiding behind tools.
- I keep learning in personal time so I stay relevant as AI reshapes work and life.
Connect
Want to follow the journey?
Training, tech, or building something real in free hours - say hej.