The feed is loud. Your path shouldn’t be.
AI is moving fast, and most of what’s written about it lives on social media — hot takes, hype threads, and contradictory tutorials. For a developer trying to actually get good at this, that noise blurs the whole picture. You can’t tell signal from noise, so you jump between fragments and nothing sticks. pepolon.dev exists to replace the scroll with a clear, end-to-end path built for developers.
- ✗One viral thread says RAG is dead. The next says it’s everything.
- ✗A dozen “build an agent in 5 minutes” clips — none that survive production.
- ✗A new framework every week, and no idea which ones matter.
- ✗Prompt “hacks” with no explanation of why they work.
- ✗You bookmark everything and finish nothing. The picture stays blurry.
- ✓One deliberate sequence — mental model first, hype last.
- ✓Each concept builds on the last, so your understanding compounds.
- ✓Taught by people who’ve shipped it, pitfalls and all.
- ✓Practice every idea, then prove you can actually do it.
- ✓You come out able to build — and able to show it.
One sequence, from mental model to production
Not a playlist of disconnected videos. A deliberate order where each step earns the next.
- 1
AI, ML & LLMs: the big picture
What AI, ML, DL and LLMs actually are, and where they fit. Mental model first.
- 2
Prompt engineering
Talking to the model: structure, few-shot, structured output, injection safety.
- 3
Tokens, embeddings & vector search
How text becomes tokens and meaning becomes searchable.
- 4
Build a RAG application
Retrieval-augmented generation end to end: chunking, grounding, citations.
- 5
Tool use & AI agents
An LLM as a reasoning engine that calls tools, plans and acts safely.
- 6
Fine-tuning & LoRA
When to fine-tune vs. prompt or RAG — and how LoRA makes it practical.
- 7
Evaluation, safety & guardrails
Knowing it works: golden sets, judges, drift — plus guardrails and injection defense.
- 8
Productionizing
Shipping AI features: cost, latency, observability, and reliability.
Then it keeps going the way real skill does: practice each idea on real tasks, and prove it with verified badges you own — not a certificate for watching, but evidence you can do the work.
Learn
From practitioners, in order
Real workshops on shipping AI systems that work — sequenced so each concept builds on the last.
Prove
Evidence, not attendance
Badges earned in monitored sessions on model-calibrated tasks. No multiple choice, no auto-passes.
Own
A profile that’s yours
Portable proof of skill, private by default — shown to employers only when you choose.
I got tired of watching great developers fail poorly designed hiring tests, while people who could ace an interview but couldn’t consistently deliver got hired. Pepolon is what I wish existed to measure what actually matters.
Hosts the AI Engineering series
Trade the scroll for a path.
Core tracks are free, and premium tracks are free during launch. Learn AI-era engineering in order, practice on real tasks, and earn verified proof of skill.
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