My Workflow Is 70% AI, 20% Copy-Paste, 10% Panic. What's Yours?

33 points by jamessmithe ↗ HN
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

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I skip reading anything "written" by my analyst and get on with the work.

If I have a question I can just ask ChatGPT, perplexity and Gemini.

You should add "Ask HN:" to the title.
If I were your boss I would fire you.
So your work can be automated by AI. Don't tell your boss or you are fired
As a developer, it's a lot of docs and code reading. And writing reports on tickets. Sometimes some deep planning. Writing code is the guilty pleasure of the day.
As an analyst it is your job to prepare valuable information to other. If you drop AI generated stuff unreflected, uncorrected and outdated at people, you will loose your job. I am starting to reject meeting minutes created by AI which are not understood by the writer and are not polished.

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)

0% AI, 80% YAML Jockey, 10% SSH Shenanigans, 10% Python programming

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.

And get off your lawn?

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.

I’m not sure what the point of your statement is?

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.

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I generally come in at least fifteen minutes late after that I sorta space out for an hour. I just stare at my desk, but it looks like I'm working. I do that for probably another hour after lunch too, I'd say in a given week I probably only do about fifteen minutes of real, actual, work.
My workflow is probably 20% coding, 50% thinking about how to code whatever needs fixing, 10% looking at metrics and 20% getting distracted. AI has proven almost entirely useless for the type of disentangling spaghetti code that makes up most of my work. Then again I'm not an analyst so you do you.
Mine is probably 60% AI, 25% structured research, 10% copy-paste, and 5% staring at the screen until inspiration strikes. AI helps me brainstorm and speed up repetitive tasks, but I always double-check and refine everything manually. The “panic” part is real though — especially when deadlines creep up faster than expected. Curious to see how others balance between AI assistance and good old-fashioned problem-solving.
Where's the part where you verify what AI has given?
I hope you come back 2 years from now and let us know if you still have a job and how your wage has been developing. The way you describe your workflow does not look promising.
I really hope you don't just get your data from ChatGPT
I’m not an analyst but a product owner and developer. Sometimes I feel similarly. However, I notice a very interesting thing when I turn the AI off for a day and go back to the pre-copilot days: my work is more focused, concise, comprehensible, impactful, and memorable.

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 use AI almost exclusively for search, and usually force myself to grind against a problem a little before engaging it. I treat AI as a smart codemod tool when I do use it for software development: against easily verifiable, well-defined tasks, low mental effort but higher time commitment tasks.

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.

90% Bazel, 5% AI, 5% day dreaming.

Not sure if the Bazel or AI part is worse. :-D I think Bazel.

I spend my time like this

- 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.

My flow (with legacy software) is: manual strip > LLM > manual clean up > repeat
50% existential crisis, 50% meetings, 50% work a grad should be doing.

I've just taken a week off to help extended family with a project, and it's reminded me what a good job is.

10-20% AI. Typically for boring and repetitive coding tasks. Also for some quick reseach, bouncing off ideas, or finding different ways to do certain things.

The rest is actual coding (where using AI typically slows me down), design, documentation, handling production incidents, monitoring, etc.

be prepared to be laid off
When we write programs that "learn", it turns out that we do and they don't. —- Alan Perlis

So what do you learn?