kyle_grove

Sounds like an experiment I'd like to give a try--what integration layer did you use to get LLMs to control the civ?

thecutline.ai , a Product Management Suite. I call it "A Product Manager That Says No", which stems from previous challenges I had using AI that was too sycophantic and optimistic to help with product decisions.

Working heavily right now on Customer Personas to use in validating/invalidating , which are configured with viewpoints, biases, and tendencies. Coming very soon will be Persona Journeys, in which you can get live, goal-oriented evaluation of your web app by a Persona.

Anthropic sign-on is surprisingly bad.

The problem of running a $4 Trillion consumer hardware company, with incredibly optimized supply chain operations, is that it heavily constrains the directions a new CEO would take the company, and by extension, the set of plausible people who could take the helm. I think even if the next CEO has a new or different product vision, they'd need deep knowledge on the hardware side of the house just to steer in any different direction.

There's the technique of model orthogonalization which can often zero out certain tendencies (most often, refusal), as demonstrated by many models on HuggingFace. There may be an existing open weights model on HuggingFace that uses orthogonalization to zero out positivity (or optimism)--or you could roll your own.

Honestly, I think the mode that will actually occur is that incumbent businesses never successfully adopt AI, but are just outcompeted by their AI-native competitors.

IMO the lack of real version control and lack of reliable programmability have been significant impediments to impact and adoption. The control surfaces are more brittle than say, regex, which isn’t a good place to be.

I would quibble that there is a modicum of design in prompting; RLHF, DPO and ORPO are explicitly designing the models to be more promptable. But the methods don’t yet adequately scale to the variety of user inputs, especially in a customer-facing context.

My preference would be for the field to put more emphasis on control over LLMs, but it seems like the momentum is again on training LLM-based AGIs. Perhaps the Bitter Lesson has struck again.

I think in part because of YouTube demonization, which is how TikTok could poach the creators in the first place.

I suspect if they're mirroring content to YouTube, it's more to try to attract audience to TikTok than monetize through YouTube.

I would use the word 'fresh' for TikTok; like old school YouTube, there's quirkiness and variety.

My belief is that while eng manager empire building was the easier path to get promoted before 2022, it's not anymore, for two main reasons:

1. HC doesn't accrue like that anymore. 2. Many organizations are looking to delayer; harder to promote up to director when your org went from 9 runs to 5.

I hear a lot of the focus going to Tech Lead Manager roles--fewer reports but more hand-on keyboard than EM roles of the past.

As I understand it, the Q-hypothesis is often situated within the hypothesis of Marcan priority (Mark was the source for Luke and Matthew), and Q is a way of explaining agreements within Luke and Matthew that are not also found in Mark. The hypothesis would be that Luke and Matthew each combined text from Mark with Q.

I think (but cannot prove) that along the way, it was decided to explicitly measure ability to 'study to the test'. My theory goes that certain trendsetting companies decided that ability to 'grind at arbitrary technical thing' measures on-job adaptability. And then many other companies followed suit as a cargo cult thing.

If it were otherwise, and those trendsetting companies actually believed LeetCode tested programming ability, then why isn't LeetCode used in ongoing employee evaluation? Surely the skill of programming ability a) varies over an employee's tenure at a firm and b) is a strong predictor of employee impact over the near term. So I surmise that such companies don't believe this, and that therefore LeetCode serves some other purpose, in some semi-deliberate way.

I lived in Woodland for a time and I really wish I had heard about them back then so I could arrange a plant tour.