podnami

There’s no way to not look AI generated these days. Give it a break.

This was pure fun for 62s until I found out how lousy I am

I run a benchmark and independently check all new models. They are very spiky.

If you are doing coding only then official benchmarks are mostly right, but as many people are starting to do for instance marketing work with LLMs now there’s very little correlation between coding and creativity for instance.

The cheaper models such as DeepSeek Flash look surprisingly good but I guess that’s because all models are using Remotion and not actual video editing software

A collection of 30k-250k apps? Like individual unique apps?

What is the point of actively choosing a web framework in the age of LLMs?

I’ve spent time doing software at VW and a few of its subsidiaries, and this matches my experience.

Compliance is everything, and SAFe (Scaled Agile) is deployed as a blunt instrument.

Management treats software exactly like hardware production lines—everything is just an "engineering process" that can be optimized on a spreadsheet.

The underlying assumption is that individual engineering talent is just an interchangeable commodity. Once you view developers as replaceable cogs, outsourcing the entire infrastructure to the lowest bidder in India becomes the logical conclusion.

It’s a textbook case of process-over-people driving institutional tech debt.

Coding on the go is definitely a use case. Especially if you want something answered or make a big decision on an architectural change but need both docs and get informed about trade offs. The biggest productivity boost we made was auto deployment of new PRs so that the agent can make live changes and we can review stuff on the to. Suddenly you can do QA in a park in the sunshine without being in front of a desktop

This is snark. Since when has a junior level dev managed to debug and deploy say a cloudformation stack and follow up with notes under 3 minutes?

They lost me at Opus 4.7

Anecdotally OpenAI is trying to get into our enterprise tooth and nail, and have offered unlimited tokens until summer.

Gave GPT5.4 a try because of this and honestly I don’t know if we are getting some extra treatment, but running it at extra high effort the last 30 days I’ve barely see it make any mistakes.

At some points even the reasoning traces brought a smile to my face as it preemptively followed things that I had forgotten to instruct it about but were critical to get a specific part of our data integrity 100% correct.

Do you have to know Assembler to be able to write code in Java? With the point being that you rarely know the underlying mechanics - and the same if true for vibe coding.

What happens before the probability distribution? I’m assuming say alignment or other factors would influence it?

I would assume this is from case to case, such as:

- How aligned has it been to “know” that something is true (eg ethical constraints)

- Statistical significance and just being able to corroborate one alternative in Its training data more strongly than another

- If it’s a web search related query, is the statement from original sources vs synthesised from say third party sources

But I’m just a layman and could be totally off here.

Is your prediction that most people actually like to use software?