Action items need an a forcing feature (like an SLO) to insure they are picked up. And someone needs to follow up when the item isn't handled timely. It should show up in team performance metrics and guide changes to processes to insure they get done.
Small tech companies (mix of product and consulting) primarily in Colorado, USA.
I would not say the hiring has been highly competitive (certainly not FAANG level) but the number of jobs are low because they are small. The tech was not cutting edge.
So says a former VP of product design who spent 14 years at Facebook. Say what you will about Facebook, I'm sure she learned a lot about product design at that FAANG, as well as at Stanford and the startups since.
But guess what. The average person isn't going to want to build every piece of software they use. And if they do want to build it, they sure as heck won't want to maintain it.
I saw a colleague build a custom marketing workflow a few months ago using AI. It was cool, but I thought to myself "welcome to the world of software debugging".
> If I have a team in pain and we need more people on it, or different people, I don't know if I can wait six months for the one person I want to hire to become available and willing. Sometimes, you gotta go with who is available.
I think the point is that you should be building your network of folks before you need them. And that you should go to your network with a specific ask rather than "who is a good engineer?".
Related, slightly: I had a business idea a few years ago when things were tighter for engineers to build a system that collected interested engineers email addresses and send them content about what the company was building. Basically a drip campaign tool for engineering talent rather than sales. I still think this would work for a company that was hiring regularly but that wasn't sexy enough to have name recognition.
I don't know if he's right, but Peter Zeihan thinks the breakdown in globalization will negatively affect the ability to continue to improve the chips that AI depends on[0]. Too many steps in the supply chain, too widespread, too vulnerable to deglobalization.
An invasion of Taiwan would definitely slow progress but it wouldn’t stop it.
We already have sufficient hardware that algorithmic (software) improvements alone should get us to GPT 7 / Greek Reference 6 even if not a single new chip is delivered to an AI data center ever again, starting today.
I wonder if the same thing could have been written about computers or the internet? Does every technology enable new good behavior but also lets you paper over previous weaknesses in process or business model?
I am not sure if it is recency bias but it feels like with AI, this problem is much bigger than before.
There is a misguided belief in early stage AI startups that, if the company is not growing, it is because the employees are not trying hard enough, working harder or not using AI enough. What really happens is that everyone is working harder, trying hard, using more AI… towards the wrong direction… against giving the proper scale up structure companies at these stages could benefit from to grow.
AI (compared to other technology) allowed people to play busy, play working hard, towards things that does not truly grow the startup at all, or worse, towards things that is working against a company’s ability to scale up and grow.
I would say, the ‘ability to appear busy’ is what’s different this time compared to before.
- Review of "The Box" which talks about this situation w/r/t the shipping container and the re-engineering that had to happen
All of these focus on the effort to re-engineer based on a new technology, because you couldn't get the true benefits without doing so. That's slightly different than the thesis of OP, which is that bad behaviors are being papered over by AI. But I think the first step towards re-engineering is to accept that some papering over is occurring.
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