eneveu

On Whatsapp, you can "Delete this message for everyone", then "Delete this message for me" and it removes the "This message has been deleted" remnant.

When installing IntelliJ IDEA extensions, I download the code and try to check it for malicious stuff using Claude Code... But not perfect since the code might not match what was released. We would need reproducible builds...

I was also toying with comparimg timestamps of git tags / GitHub releases / GitHub actions / plugin update timestamps as one indicator of potential tempering.

But not ideal.

> They were snatching people from the streets and killing them.

Can you give more info on this? Tried googling it but couldn't find much. I remember there were very strict quarantines, but don't remember reading anything about "killing" people snatched from the street.

Not much.

I think companies dream of increasing productivity using AI, so they want to encourage their devs to use AI more. Since it's notoriously very hard to measure software productivity, and they have no way to really measure how well engineers use AI, they measure number of tokens.

Which is dumb. Because a bad engineer might ask the AI to "convert this CSV to JSON" which would burn token, while a good engineer would ask the AI to "write a script to convert this CSV to JSON". Of course, this example is not ideal, since a SOTA model would probably just write a script anyway in the first case... But you get the idea.

Thought this was interesting to see how AI token usage is exploding at multiple companies, and how they try to deal with it.

No mention anywhere of context engineering (starting a new session once a task is done, using sub-agents, reducing context for MCPs), and it seems some companies are actually rewarding developers for wasting token, instead of being smart.

Interesting. Do I get this sandboxing out of the box when I install apps with Homebrew? Or do I need to do something specific?

Would love to enable this for all apps, and add exceptions for the ones that need more access.

I installed Lulu and BlockBlock recently, and want to do more to harden my Mac.

The cool thing when using AI (e.g. Claude Code) is that the conversation with the agent is saved, and you can retrieve from that convo the way you did things in the past. Not just the how, but also the why.

If you read Clean Code and other similar books, they don't necessarily advise moving the sub-functions to other files, or splitting them arbitrarily. They simply have the top function delegate to sub-functions that are lower in the same file. Even better if these sub-functions can be marked as private in your language (to avoid polluting the public API of your object). And here the goal is to use function names to document what each block of code (sub-function) does.

Example:

    def process_order(order):
        _validate(order)
        _reserve(order)
        _charge(order)
        _confirm(order)
    
    def _validate(order):
        ...
    
    def _reserve(order):
        ...

Previously, if you had a BigQuery external table on top of GCS files, and those files had Nearline / Coldline / Archive storage classes (e.g. due to a bucket lifecycle policy), you were not billed for retrieval fees when reading those files through the BQ external table.

This was a billing bug that was already mentioned in 2020 on StackOverflow.

But the bug has been fixed on February 21, 2025. So we are now billed for that. We started seeing 10.000 $ of retrieval fees due to that. I did a deep dive and found this.

The fact that some of our DBT projects were re-creating the external tables daily was not helping...

New Zealand startup Montoux shut down after a lawsuit from $46B fintech giant FIS, which accused it of stealing trade secrets—claims Montoux denied. The company had gained traction as an alternative to FIS’s Prophet software, but instead of competing, FIS sued.

Filed in Delaware, the lawsuit alleged Montoux used FIS code and trained AI on proprietary data. With legal costs hitting $600K upfront, Montoux couldn't afford to fight and liquidated. This "lawfare" tactic highlights how corporations use litigation to stifle competition, raising serious questions about monopolistic practices and the barriers to innovation.