Xolani Ndlovu

#Finance & #Banking, #Trader | #Digital, #Strategy, #Innovation | #Futurist, #ActiveCitizen Retweets are not endorsements

[Elon Musk @elonmusk]

Helpful tool for improvement. It’s just physics thinking in the limit.

[Anthropic @AnthropicAI]

Our internal data shows Claude is accelerating AI development—a possible path to recursive self-improvement, or AI autonomously building a more capable successor.

It’s happening faster than we thought, and the implications deserve greater attention. https://t.co/OVVPJO7VQx

[Anthropic @AnthropicAI]

None of this guarantees recursive self-improvement is on the horizon. It’s not yet clear that Claude is capable of research judgment—of choosing the right problems to work on.

But if these trends continue, AI systems designing and building their own successors is plausible. This could revolutionize society—medicine, technology, the economy—for the better. But it may also compound alignment issues and ultimately lead to loss of control.

The Anthropic Institute (in collaboration with external stakeholders) will conduct research to think through the implications of increasingly powerful, potentially self-improving systems—and how to create the ability for the world to make deliberate choices about the future development of the technology.

Read the full post: https://t.co/XkYALsONft

[Andrew Ng @AndrewYNg]

One of the new, buzzy jobs in Silicon Valley is the AI Forward Deployed Engineer (FDE), an engineer who is embedded within a client organization to help customize solutions, such as building and tuning agentic workflows that suit the client’s particular needs. I’ve heard from people who are wondering anew about the FDE career path since OpenAI and Anthropic started building new teams to place FDEs within client organizations.

The rise of FDEs for AI workloads is one way AI is creating new jobs (and why the jobpolcalypse narrative of upcoming job market collapse is false -- there will be many AI and non-AI jobs). However, I believe there will be far more AI Engineer jobs than FDEs, as I explain below.

The FDE role was pioneered about two decades ago by Palantir, which sent engineers to government locations to work on secure, air-gapped networks. In addition to having good technical skills, FDEs need communication skills and sometimes business skills. For example, they may need to speak with clients to understand their needs, formulate a strategy to prioritize projects, explain complex technology, and respectfully push back if a client asks for something unrealistic. They’re enjoying a resurgence because of the amount of work involved in taking an off-the-shelf LLM and building it into a custom agentic workflow that fits particular business needs.

However, I believe the number of AI Engineer jobs will be far larger. A company might accept a few FDEs to be embedded within its organization. But most companies will want far more of their own employees working on their projects. While my organizations do hire FDEs, we hire far more AI Engineers! Also, a common client concern is that it is hard to find vendor-neutral FDEs — they are, after all, there to deeply integrate a particular vendor’s product into a company. In this moment when it’s hard to predict which AI service will be the best one in a year’s time, optionality (the ability to pick whatever vendor turns out to fit best in the future) is very valuable. In contrast, letting FDEs tightly bind a company’s processes significantly reduces optionality.

Right now, I see surging demand for AI Engineers who can build software applications using AI software components (like LLM prompting, agentic frameworks, evals, etc.) and effectively use AI coding agents (like Claude Code, Codex, Antigravity CLI, and OpenCode). As the AI Engineer role matures, I expect it to fragment into more specialized roles, like the generic Software Engineer role from decades ago fragmented into frontend, backend, mobile, data engineering, devops, and so on.

What will be the future, specialized AI engineering roles? I don’t know. Perhaps there will be AI FDEs, LLMOps Engineers, Evals Engineers, AI Data Engineers, Harness Engineers, and other roles we don’t have names for yet. But for now, I see a lot of AI engineers who are generalists create a lot of value. Skilled AI Engineers are in very high demand! As our field continues to mature over the coming decade, I look forward to new specializations within AI Engineering that create even more job opportunities.

[Original text: The Batch newsletter]

[Anthropic @AnthropicAI]

We've raised $65 billion in Series H funding at a $965 billion post-money valuation, led by @AltimeterCap, Dragoneer, @Greenoaks, and @sequoia.

This investment will help us advance our research and expand our capacity to meet growing demand for Claude.

[Bojan Tunguz @tunguz]

Brutal, honest, and direct.

[Mira Murati @miramurati]

We started Thinking Machines to advance human-AI collaboration, and this is our first bet on what that looks like. Most labs treat autonomy as the goal and interactivity as scaffolding around a turn-based core. We think the way we work with AI matters as much as how smart it is. Interactivity has to be in the model, and it has to scale with intelligence rather than trail behind it.
https://t.co/U4c0uC7tnT

[Marc Andreessen 🇺🇸 @pmarca]

Asking AI to ask questions is hugely underrated.

[Y Combinator @ycombinator]

AI has stopped being a feature and started being the foundation.

We're excited about a new wave of startups rebuilding software, services, and silicon— and pushing AI into the physical world.

https://t.co/QCIz6DnQnN

[Ronnie Chatterji @RonnieChatterji]

Interesting study by @erikbryn and @avi_collis showing big consumer welfare gains from AI. Reminds us that large portion of the economic value of AI will not show up in traditional economic indicators. https://t.co/KZamgFevc9

[Marc Andreessen 🇺🇸 @pmarca]

👀

[Marc Andreessen 🇺🇸 @pmarca]

This is the way.

[Rohit @rohit4verse]

https://t.co/jo9mBLzweh

[Jaya Gupta @JayaGup10]

https://t.co/yiGW8jKKXk

[Codie Sanchez @Codie_Sanchez]

Harvard MBAs watching plumbers make $100k+ while entry level finance jobs get fully replaced.

[NASA @NASA]

It's not just a phase 🌕

Artemis II astronauts captured these views of the Moon as the Orion spacecraft flew around the far side of the Moon on April 6, 2026.

[Xolani Ndlovu @xolanee02]

@NASA Stunning!

[Dustin @r0ck3t23]

Palantir CEO Alex Karp just exposed the absolute mathematical failure of the American education system.

We’re actively filtering out our apex builders.

The system is still training the biological workforce to be compliant, administrative cogs for an industrial machine that superintelligence is currently overwriting.

Karp: “All of our tests are built around things that were valuable in the Industrial Revolution.”

Sitting perfectly still and memorizing compliance metrics is a zero-margin commodity.

The highest-output operators of the next decade are the exact people the archaic system actively punishes.

The neurodivergents. The dyslexics. The hyper-kinetic builders.

Karp: “Everybody who can’t sit or needs to build or wants to build have to go into a separate slot.”

Don’t force apex cognitive talent to beg for a mid-level banking job at Goldman Sachs.

Weaponize their chaotic, non-linear execution to build the physical infrastructure of the future.

And here’s the brutal reality check.

Karp: “Vocational training in Germany is very technical. The people building the cars at BMW or even in the French version Airbus, very complicated jobs, they didn’t go to college. They went to a very, very high-end high school. And they come out without any debt.”

The elite establishment treats vocational training as a biological failure state.

It’s the ultimate sovereign moat.

We’re mass-producing millions of debt-saddled knowledge workers whose entire skill set is about to be absorbed by an LLM.

The algorithm cannot manufacture a jet turbine.

It cannot secure a power grid.

The nations that win the next decade will completely bypass the bloated university system.

Aggressively route the highest-IQ operators directly into elite, zero-debt physical execution.

Karp: “You also need to change our testing system. Different forms of intelligence. Pull out all the dyslexics, all the neurodivergent.”

Standardized testing doesn’t measure cognitive velocity.

It measures biological obedience.

The system measures the entire species on a single, archaic axis of compliance.

Fail to sit in a chair and memorize the curriculum?

The system discards you.

The AI arms race won’t be won by compliant valedictorians who are excellent at filling out rubrics.

It’ll be won by hyper-obsessive, neurodivergent builders who mathematically cannot tolerate the friction of a traditional classroom.

By actively filtering these operators out, the current education system is bleeding out its most valuable resource.

And it doesn’t even know it’s doing it.

Karp: “We should have gotten you before you got turned down at Goldman and said this is a waste of your time. You could be building something important.”

Identify the builders before the system breaks them. Hand them the compute.

Because the system is filtering out the exact people who will build what replaces it.

They won’t come back to reform it. They won’t ask for permission.

They’ll just build over it.

And they already started.

[Polymarket @Polymarket]

BREAKING: New startup "RentAHuman" allows AI agents to rent humans to perform tasks they cannot physically perform themselves.

[Elon Musk @elonmusk]

I use this analogy a lot.

This is what a room full of computers looked like in old times: