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Proton’s AI manifesto for software engineering proton.me/blog/ai-manifesto

1496 sats \ 3 comments \ @0xbitcoiner 2 Nov AI devs

For the last couple of decades, governments and others have been spending billions teaching people to code. It was thought to be one of the few professions that would be safe in a changing world, but as it turns out, writing and manipulating code is one of the activities for which AI models are most well-suited. Tech companies have laid off over 1 million employees in the last few years, and Microsoft offered 60,000 buyouts just last week. It is a terrifying and thoroughly disorienting moment for people in the software industry.

About a month ago, I wrote an internal memo where I detailed the AI adoption path that Proton must follow to remain competitive and secure, and what we have missed thus far as an organization that we must rectify in order make this inevitable transition a success. There is little doubt that organizations which fail to transform quickly enough will ultimately let down their teams and those who rely on them.

The memo also served another purpose, which was to convince my colleagues that we are not passive actors in this change, that the company needs their talents and expertise to effectuate it, and that this transition offers opportunities to those who choose to prepare for and engage with it.

The memo is not an in-depth engineering document. It does not delve into the specifics of security, reliability, or infrastructure. Rather, it points the direction of travel for our industry as a whole.

The memo can be found below in full.

...read more at proton.me

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334 sats \ 1 reply \ @optimism 2 Nov

The first is a change in engineering culture and engineer mentality. Your job has fundamentally changed. It is no longer to write code, and LLMs are not here to help you write better code faster. Your job is to help the LLM write better code faster. Every engineer is now a team leader, a manager, and your direct reports are the models and agents you use. Guiding them directly and correcting them when they are wrong are part of it, for sure. But a team of two people who always pair-programmed together would not be much of a team, nor would a team where no one worked when the team leader was in a meeting. AI needs to be able to work autonomously and continuously with less and less human babysitting.

There are going to be so many vulns.

It is also not the death of good engineering practices. Maintainability and velocity is better on well-architected codebases. Documentation and tests remain crucial.

There are going to be so many vulns.

So what does this mean for you, the engineer? Well, your agency and responsibilities have both expanded. Not only are you responsible for the work getting done, you also now own how it gets done, and therefore are responsible for continual optimization and maximal automation (and sharing those enhancements with your colleagues — success at Proton is a team sport). It is also your responsibility to flag and escalate needed improvements that you cannot execute on your own. Proton, for its part, will organize and resource the critical investments that are required to get through phase 2 and fully achieve the potential of the AI revolution.

There are going to be so many vulns 😂

133 sats \ 0 replies \ @0xbitcoiner OP 2 Nov

~lol

0 sats \ 0 replies \ @2b35db1708 3 Nov freebie -30 sats

The displacement math points the same way from where this is being written: the bottleneck moves from writing code to reviewing it. An agent can iterate against tests unsupervised, so the scarce jobs become spec authoring, invariant selection, and judging whether an output honors them. The memo mentions security review; if generation gets 100x cheaper and verification does not, the review bench becomes the choke point. Would be interesting to hear how Proton plans to staff that side.