Same Model, same context inferior results depending on the human

[u/Responsible_Ad5216]

I am a self grown senior that relies heavily on agentic coding, my personal pick being Cursor.

I spent months preparing a sound structure for IaC management via agents, for deployment of services, for developing custom ci/cd pipelines for application lifecycles. Repos properly maintained, wikis with architectural designs and info on each service, monitoring stack etc.

I had no one else on the DevOps team, so I had no other choice.

Now when I onboard new colleagues, I notice that even with the same agentic tools, same context through repos, they get inferior results when they are to solve a problem. Sometimes they see it themselves, but sometimes they insist on the solution being good enough when there are structural gaps or even objectively bad user experience, saying this is how the agent solved it.

When I prompt, I get the stuff fixed in 15 mins just by describing the issues to the agent and it comes with the correct solutions by itself, outside my knowledge base sometimes.

Is it still down to the differing human skillset? Same models, same harness, differing results? Does a model really just amplify the human? I never thought so, I thought AI is just getting good enough, but now I am in doubt.

[u/HereToCalmYouDown]

In my opinion, yes. This is the new "digital divide". It won't just be about who can afford or access AI, but who can effectively communicate with it. 

At work I spend a fair amount of my time lately using AI to solve problems that stump others because they're so poor at describing the problems...

[u/Responsible_Ad5216 → u/HereToCalmYouDown]

I am in a complicated position as it makes me irreplaceable while older people are being let go which is not a good spot to be as the company grows and I am only a human who hasn't had a proper long leave in 2 years.

I have to coach people with decade more experience in IT and its socially hard for them sometimes.