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.

Google on multimodality: has been truly impressive over the last six months and has the deep advantages of Chrome, YouTube, and being the default web indexer, but it's entirely plausible they flub the landing on deep product integration.

Chinese companies and pricing: facts, and it's telling to me that OpenAI seems to have abandoned their rhetorical campaign from earlier this year teasing that "maybe we could charge $20000 a month" https://techcrunch.com/2025/03/05/openai-reportedly-plans-to....

Coding: Anthropic has been impressive but reliability and possible throttling of Claude has users (myself included) looking for alternatives.

Social: I think OpenAI has the biggest opportunity here, as OpenAI is closest to being a consumer oriented company of the model hyperscalers and they have a gigantic user base that they can take to whatever AI-based platform category replaces social. I'm somewhat skeptical that Meta at this point has their finger on the pulse of social users, and I think Superintelligence Labs isn't well designed to capitalize on Meta's advantages in segueing from social to whatever replaces social.

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

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.

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.

    1. No one work arrangement is optimal for all firms.

    2. Most policies around RTO (or remote work) are not meaningfully exploring optima (with respect to organizational health and work product quality).

    3. Therefore, the amount of preserveration and energy spent on RTO steals focus from main drivers for firm success. Which is probably the point, as the article points out.

What I would add as someone who has been managing collaborative science teams embedded in large companies remotely, pre- and post-pandemic, is that some forms of alignment translate to the remote setting, but other forms of alignment are more challenged. I think the boundary is probably: if the teams were aligned pre-remote, you can sustain the alignment, even with new collaborative initiatives, but gaining new alignment with new teams is way more challenging.

Which is fine when what you are doing is Business as Usual, but falls apart when there are crises or disruptions that require net new collaborative relationships.

I think the full use case you describe is better suited for a passkey manager, since passkeys are marching generated already.