TOP 3๏ธโฃ things you need to become a Data Engineer.
1. A domain to specialise in.๐ก
2. The book: Fundamentals of Data Engineering https://t.co/zv82pa7Hje
3. This roadmap: https://t.co/OHYr1ICZNe
Aren't you tired of hitting your AI credit limits just by scanning and going through content?
When you start working in big enough repositories or knowledge base, it's a nightmare to understand a design decision, business metric or a feature.
It can even send your coding assistant into rabbit hole and once you realise it... boom! Your credits are gone.
Imagine being able to achieve an Incremental efficiency โ 99.95% ๐คฏ.
This is when cocoindex enters the picture.
- No more full greps
- No more blind searches
- No more token limits scanning content
Just live incremental context ready for your AI agents.
Try it out for FREE: https://t.co/3wlxKBwSRK
One of the most difficult tasks when you coding is to stay consistent.
- With naming conventions
- With a chosen design
- With a discussed approach
When you are implementing, there will be things stopping you mid way that you didn't anticipated. It's very important that you zoom out and think what's the wider impact of implementing something in this way and not that way.
That's the reason why context stalls and misguides LLMs, not even us humans can keep everything as tidy as we make it to be.
I'm a Sr Data Engineer with +7 years of experience. But I wasn't readily qualified for any position I have taken.
So how did I manage?
- Stay curious and ask for help.
- Be honest about your shortcomings.
- Find a champion that can take you to the next level.
Most often than not a genuine interest and motivation will go a long way. People hire people they want to work with, then it's a matter of learning fast how to get the job done.
@chaocacbannn Yes!! it was a total game changer. By now my bigger flex went from that into Claude + Obsidian. ๐คฏ But it's hard to keep up so I only change or push further if there's an actual need or blocker I'm facing otherwise I stick with my own ways of working now.
Iโm a Sr Data and AI engineer and it took me almost a year to adopt AI to its full potential.
This was my journey:
- Chatting with ChatGPT, copy and pasting
- Started using copilot to understand projects and features.
- Switched to kiro-cli to give better access and manage context across projects
- Finally adopted Claude Code and embedded into all my workflows ( After 10 months since launch)
Still learning. Still improving. Youโre not late. โฐ
@NgocMy18x For me it was the free intermediate step between texting on a chat interface and have an agent (for free) being able to actually see what I was doing ! That gave me the final push before diving into Claude Code.
@MPhuong609 It was at the time when I wanted the AI agent to have more seamless control over what I'm doing before investing any $$$. There are good models for free !