The French government did not provide a specific timeline for the switchover, or which distributions it was considering.

Got to be Mandrake right?

What resonated most for me was the "Finding Your Threshold" section. Your "Developers need the dopamine hit of creation." is memorable. I have also blogged about this phenomenon at https://www.exploravention.com/blogs/soft_arch_agentic_ai/ but I frame it more as how leaders can help the organization arrive at a healthy and sustainable balance between writing and reviewing code.

https://www.higherscoresdfs.com/dfs/spa/welcome/

Here is the pitch.

We seek to empower DFS fans through education about predicting professional sports athlete outcomes. We do that through strategy advice, hot player tips, optimized lineups, and pick’em style game-friendly player props. We're not trying to take away your control or do your thinking for you. We are just here to support you in making better decisions. Let the app do the number crunching so you can get back to competitive play that gets results and is also fun.

There are plenty of articles on review fatigue including https://www.exploravention.com/blogs/soft_arch_agentic_ai/ which I published recently. The focus there is less about the impact on the developer and more about the impact on the organization as letting bugs go to production will trigger the returning to high ceremony releases and release anxiety.

The OP article talks about AI fatigue of which review fatigue is a part. I guess that I would sum up the other parts like this. The agentic AI workflow is so focused on optimizing for productivity that it burns the human out.

The remedy is also not new for office work, take frequent breaks. I would also argue that the human developer should still write some code every now and then, not because the AI cannot do it but because it would slow the process down and allow for the human to recover while still feeling invested.

1. Since the same AI writes both the code and the unit tests, it stands to reason that both could be influenced by the same hallucinations.

2. Having a dev on call reduces time to restore service because the dev is familiar with the code. If developers stop reviewing code, they won't be familiar with it and won't be as effective. I am currently unaware of any viable agentic AI substitute for a dev on call capability.

3. There may be legal or compliance standards regarding due diligence which won't get met if developers are no longer familiar with the code.

I have blogged about this recently at https://www.exploravention.com/blogs/soft_arch_agentic_ai/

Do we still need humans to manage tech debt?

Do we still need humans to review the AI output?

Do we still need humans to care about non-functional requirements such as scalability and fault tolerance?

Do we still need a human developer on call?

If you said “yes” to any of the above, then do you believe that it is only a matter of time until your answer would change to “no,” or do you believe that it would always be “yes, humans are needed.” Please elaborate on why.

Comments URL: https://news.ycombinator.com/item?id=46736122

Points: 4

# Comments: 1

https://www.exploravention.com/products/sports/

Not sure about your information architecture. What is the difference between the web frameworks and web server abstraction tags?

This next question is more for the Clojure community. From https://clojure.land/?tags=Web%20Frameworks we see 34 web frameworks. That seems like a lot to me. Why is there so much "scratching your own itch" because you don't like ring?

If you are considering the use of a graph database for AI based search and you are not already familiar with graph database technology, then you should be advised that graph databases are not relational databases. If you cognitively model nodes = tables and edges = joins, then you will be in for some nasty surprises. You should consider some learning, and some unlearning, to do before proceeding with that choice.

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Like the rest of online mass media, HN covers generative AI a lot but there is still plenty of value in predictive AI. Both forms provide plenty of technical challenges to the AI engineer. I miss the days when you could get a stack trace to when debugging an issue.

The question is this. Do the costs of monorepo justify the benefits for your situation? The answer is not always yes.

https://www.exploravention.com/products/askarch/

It is an interesting discovery journey on extracting relevant information from both code and documentation with a sufficient density to stay within the context window and extracting efficient criteria from arbitrarily phrased questions.