Do not spend 2 years learning AI agents the slow way Andrew Ng just shared a complete 2-hour roadmap On becoming an agentic AI engineer in 2026: 00:00 - Learn the foundations of AI agents 12:12 - Design agentic workflows 53:27 - Build agents that work in practice 1:20:30... - Create self-improving loops 1:30:19 - Orchestrate multi-agent systems Most people are still learning how to prompt one model Andrew Ng is already teaching the complete stack: Agents → Workflows → Loops → Multi-Agent Systems Prompting is the old workflow Building autonomous systems is the new one Anthropic pays top engineers up to $750K a year to understand this stack Bookmark this and give it two hours today Then read the full graph engineering guide belowshow more

@0xwhrrari man, gotta love when someone breaks it down like this. wish I had this kinda stuff when I was starting out 🙃

same bro wouldve saved me a lot of random tabs xd

@0xwhrrari haha same here, i swear i'm a tab hoarder. what's your current tab count?

enough to make my browser beg for mercy lol whats yours

@0xwhrrari haha I hear ya! mine's barely hanging on too 😂

yeah now I got it..

😼😼

two hours of roadmap can save months of wandering around agent twitter

fr agent twitter has too many side quests

the timestamps are useful, but “work in practice” gets 27 minutes while foundations get 12:12. what specific failure modes does the roadmap teach you to debug?

mostly broken handoffs context drift and tool loops from what i caught

context drift is usually the sneaky one. are you debugging it by tightening the handoff schema, or by trimming what each agent can see?

both tbh tighten the handoff schema first then trim what each agent sees using traces and evals

the handoff schema is probably the bigger lever. what fields are you keeping in the trace—just tool calls and failures, or the full reasoning context too?

agent engineering starts where prompting ends

agree with u brotha

well explained fr

glad it landed bro

I made a loomgraph, please check it out

Thank

All you need is the Bible to learn Agents. To learn Ai you need

2 hours to skip 2 years, that's a serious shortcut.

两小时路线图从基础到自改进循环，照着走能少绕很多弯路

I’d spend more time on loops than prompts.

I’ve been getting value from much simpler workflow, so I'm excited where this is going. And keen to keep up, so this type of share is useful.

750k is just a flashy number, not proof. Where the source ?

The societal implications of blockchain architecture depend heavily on transparency, accountability, and governance over the next decade.

The slow way can involve months of trial and error with poorly documented tools and vague model outputs, but its usually just a lack of clear tool metadata and eval metrics that slows progress.