Vibe coding won't save your career.
Those, who want to control AI must understand engineering.
And it’s not rocket science.
The best free resources to get started:
- System Design 101 by ByteByteGo (GitHub): github.com/ByteByteGoHq/s…
- Engineering Visual Guides:
Be careful. Most "products" are, in fact, projects.
9 red flags (and how it should work):
1. Large PRD: You start an initiative by documenting everything.
2. Feature factory: Implement the requirements. Don't ask why.
3. Waterfall: All the requirements are collected in the
Everyone in AI is talking about Context Engineering.
But just a few explain what the context is.
Save this template. It captures all scenarios and will help you maximize agents' performance: 🧵👇
Context engineering is the new prompt engineering.
And it’s becoming the most critical AI skill.
Together with @MiqJ (Product Lead at @OpenAI) we created a comprehensive guide.
Key insights: 🧵👇
Many PMs struggle to explain the difference between Vision, Strategy, Objectives, and Roadmap.
But those are extremely simple concepts.
Let's tackle them one by one:
(1/9)
Agents are the most valuable skill in AI and product right now.
So why not build one? Here's how:
Step 1: Define a System Prompt
It defines the goals, logic, and expectations.
Free guides:
- GPT-4.1 Prompting Guide
- Anthropic Prompt Engineering
- Prompt Engineering by
After an interview with @karpathy, everyone is talking about what AI agents can/can't do.
But an opinion without data is just a hypothesis.
So, I tested 3x185 workflow executions for a market researcher agent.
The results have shocked me🧵
