My Workflow Is 70% AI, 20% Copy-Paste, 10% Panic. What's Yours?
Being an analyst I need to research about the market and work accordingly. With the help of ChatGPT, perplexity and Gemini, I get done 70% of my research work. The rest of the 30% is just pure brainstorming. Then if I need some graphics then I use Canva for designing them. I get the images from them. Sometimes, I create ppts too using it. If I need any videos then i usually use tool like fliki, Lunabloom Ai or invideo to generate video. These tools give me good quality AI generated videos. Then nowadays, AI is also available on social medias. It makes the job easier for me. So basically, Most of my work is completed by AI. The one thing I need to do properly is to give them proper instructions. How do you go about it?
46 comments
[ 3.8 ms ] story [ 71.7 ms ] threadIf I have a question I can just ask ChatGPT, perplexity and Gemini.
AI is a tool for you to create better results not an opportunity to offload thinking to others (like it is now done so often)
Been doing sysadmin since the 90's. Why bother with AI, it just slows me down. I've already scripted my life with automation. Anything not already automated probably takes me a few minutes, and if longer I'll build the automation. Shell scripts and Ansible aren't hard.
I’ve been developing professionally since 1996 and started on Dec Vax and Stratus VOS mainframes in Fortran and C, led the build out of an on prem data center with raised floors etc to hold a SAN with a whopping 3TBs of storage along with other networking gear and server software.
Before I started developing professionally, I did assembly language on 65C02, 68K, PPC and x86 for 10 years.
In between then and now, I’ve programmed professionally in C, C++, VB6, Perl, Python, C#, and JavaScript.
Now all of my work is “cloud native” from development to infrastructure and take advantage of LLMs extensively.
It’s not a mark of honor to brag about you don’t use the latest tools.
Some people aren’t using LLMs to do development. Some people aren’t doing stuff in hyperscaler clouds. Some people don’t work in environments where code is allowed near LLMs. Some people are and some people do. This is perfectly fine and to be expected.
Still I have this feeling that AI is very close to “doing my work” but yet when I step back I see it may be a rather seductive mirage.
Very unclear. Hard to see with the silicon-colored glasses on.
I keep a list of "rules of engagement" with AI that I try to follow so it doesn't rob me of cognitive engagement with tasks.
Not sure if the Bazel or AI part is worse. :-D I think Bazel.
- reading papers, blogs, articles, searching google scholar, and chatting with perplexity about them to help find other papers
- writing research proposals based on my reading and previous research
- analysing data lately this means asking Claude code to generate a notebook for playing around with the data
- writing codes to explore some data or make some model of data, this also has a lot of Claude code interaction these days
- meetings, slack, email
- doing paper and proposal reviews which includes any or all of the above tasks plus writing my opinion in whatever format is expected
- travelling somewhere to meet with colleagues at a conference or their workplace to do some collaboration that includes any or all of the above plus also giving talks
- organising events that bring people together to do any to all of the above together
I’m a soft money research scientist with a part time position in industry working as a consultant.
I've just taken a week off to help extended family with a project, and it's reminded me what a good job is.
The rest is actual coding (where using AI typically slows me down), design, documentation, handling production incidents, monitoring, etc.
So what do you learn?