@steve2bacon Thank you praise Jesus, Brother Steve
Can I get a hallelujah and an amen
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@plumberbutt97 i’ll say it with you
steve2bacon, CMT@steve2bacon
the lows are in and Russell will lead
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you see those gaps down there? we’re not filling those for a while
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📢 𝐉𝐔𝐒𝐓 𝐈𝐍: Aparna Ramani, $META Meta’s Vice President of Engineering for AI Infrastructure Has Left the Company - The Information
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These guys are just shipping 10x faster than anybody else right now.
There seems to be a lack of both focus and urgency everywhere else. I don’t know why… but it’s a bit weird.
Claude@claudeai
We've redesigned Claude Code on desktop. You can now run multiple Claude sessions side by side from one window, with a new sidebar to manage them all.
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Bearish divergence
Aesthetics 𝕏@aestheticsguyy
Post a picture YOU took. Just a pic. No description
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Semafor: Kraken has confidentially filed for an IPO. The crypto exchange was valued at $13.3B in an April funding round, down from a $20B peak in late 2025.
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As I’ve said before $META is a P*Q
Price is demand / ROAS based
Quantity is attention and load
I do actually think there is limits on ad effectiveness generally, and then it’s limited by relative ROAS (though likely they continue to have the best). If they are the best then it’s limited to how punitive it is for the businesses.
Quantity is tough. The core properties are fine but Zuck is clearly going very hard to find another property to stuff ads on and is mostly failing - at least against what they’ve spent.
They’ve built a magical money machine. If anyone is every wondering who can make money from AI, it’s meta, and they’ve been doing it since they lost the IDFA signal
My main disagreement is just how poor this capital allocation is vs the market always giving him the benefit of the doubt. 2x NI is tough against the spending over two and bit years vs 25 to maintain ROIC, and if the market knows that and it’s a permanently higher capital intensity business at like 30-40% and ROIC in the teens, then is the multiple actually wrong?
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I’m skeptical of these. I haven’t seen @TLAMB91 or @ChartsRUs0 or @snorlax_uw tweet about them. Take with grain of salt.
Cole@StockOptionCole
$META 800C 5/15... 31 days out & 20% OTM What do they know?
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@snorlax_uw $META going bananas with contracts
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Look, it happens to all of us.
NBC Sports Philadelphia@NBCSPhilly
Technical difficulties in the hot dog department
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“What should a software team look like?” is a question that’s been perplexing me since the move to AI. We see a few patterns now for strong engineers in the AI world but I feel like I see no patterns at all on what makes a strong team.
I go back and forth on whether we need hierarchy, whether we need PMs and/or designers, whether we need docs and meetings.
I find it ends up being more dependent on the individual rather than the role. I’ve worked with folks who can be both an engineer, a PM, and designer at the same time, and folks who do just one or none. A team might need to organically reconfigure based on the people and talent rather than trying to fit the old mold of “X fronted, Y backend, 1 manager, one PM, one designer, one data scientist, etc”
Andrew Ng@AndrewYNg
As AI agents accelerate coding, what is the future of software engineering? Some trends are clear, such as the Product Management Bottleneck, referring to the idea that we are more constrained by deciding what to build rather than the actual building. But many implications, like AI’s impact on the job market, how software teams will be organized, and more, are still being sorted out. The theme of our AI Developer Conference on April 28-29 in San Francisco is The Future of Software Engineering. I look forward to speaking about this topic there, hearing from other speakers on this theme, and chatting with attendees about it. We’re shaping the future, and I hope you will join me there! It is currently trendy in some technology and policy circles to forecast massive job losses due to AI. Even if they have not yet materialized, these losses certainly must be just over the horizon! I have a contrarian view that the AI jobpocalypse — the notion that AI will lead to massive unemployment, perhaps even rioting in the streets — won’t be nearly as bad as dire forecasts by pundits, especially pundits who are trying to paint a picture of how powerful their AI technology is. Among professions, AI is accelerating software engineering most, given the rise of coding agents. According to a new report by Citadel Research, software engineering job postings are rising rapidly. So if software engineering is a harbinger of the impact AI will have on other professions, this expansion of software engineering jobs is encouraging. Yes, fresh college graduates are having a hard time finding jobs. And yes, there have been layoffs that CEOs have attributed to AI, even if a large fraction of this was “AI washing,” where businesses choose to attribute layoffs to AI, even though AI has not changed their internal operations much yet. And yes, there is a subset of job roles, such as call center operator, that are more heavily impacted. Many people are feeling significant job insecurity, and I feel for everyone struggling with employment, whether or not the cause is AI-related. And many other factors, such as over-hiring during the pandemic and high interest rates, have contributed to the slowdown in the labor market, and the notion that AI is leading to unemployment is oversimplified. In software engineering, I see a lot of exciting work ahead to adapt our workflows. It is already clear that: (i) As AI makes coding easier, a lot more people will be doing it. (ii) Writing code by hand and even reading (generated) code is not that important, because we can ask an LLM about the code and operate at a higher level than the raw syntax (although how high we can or should go is rapidly changing). (iii) There will be a lot more custom applications, because now it’s economical to write software for smaller and smaller audiences. (iv) Deciding what to build, more than the actual building, is becoming a bottleneck. (v) The cost of paying down technical debt is decreasing (since AI can refactor for you). At the same time, there are also a lot of open questions for our profession, such as: - In the future, what will be the key skills of a senior software engineer? And for junior levels, what should be the new Computer Science curriculum? - If everyone can build features, what skills, strategies, or resources create competitive advantage for individuals and for businesses? - What are the new building blocks (libraries, SDKs, etc.) of software? How do we organize coding agents to create software? - What should a software team look like? For example, how many engineers, product managers, designers, and so on. What tooling do we need to manage their workflow? - How do AI agents change the workflow of machine learning engineers and data scientists? For example, how can we use agents to accelerate exploring data, identifying hypotheses, and testing them? I’m excited to explore these and other questions about the future of software engineering at AI Dev. I expect this to be an exciting event. Please join us! [Original text: The Batch newsletter.] ai-dev.deeplearning.ai
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We went from Praise Allah to bash the Pope to Jesus to Dr Jesus in one week.
Ok then . . .
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Do I wanna be regarded and try to swing something or just keep day trading?
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ANTHROPIC PREPS OPUS 4.7 MODEL, AI DESIGN TOOL - THE INFORMATION
ANTHROPIC’S FORTHCOMING DESIGN TOOL VOWS TO TAKE ON COMPETITORS LIKE GAMMA AND GOOGLE’S STITCH PLATFORM
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This is bull case for Meta/Google over Ant/OpenAI! Personal Superintelligence = AI that's RLed using YOUR reward function.
Still have to solve for reward hacking though. Recommendation algorithms of course represent your revealed preferences, but they are still trying to encourage sensory novelty at the expense of epistemic novelty. Once reward function realigns from just attention maximizing to solutions to your problems (however that's defined in various contexts), we should have it.
BuccoCapital Bloke@buccocapital
I would pay a lot of money for some AI solution that clips the 10 most interesting minutes from the podcasts I follow and gives me an hour or two of the best content each week
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