Akshay Chalana

Co-Founder, @saphira_ai | Automating Hardware Standards Compliance

[Aaron Levie @levie]

Again, maybe counterintuitive, but in the majority of conversations I have with CIOs, CTOs, and CEOs in large enterprises, they are either growing due to AI (in new job functions like FDEs, engineering, etc.) or at a minimum reinvesting efficiency savings back into the business in new areas (sales, marketing, etc.).

David Solomon, CEO of Goldman Sachs, articulated this perfectly in a NYTimes OpEd last week. The AI boom is both creating all new jobs in the build out of AI systems and the implementation across sectors, but also freeing up dollars to invest in areas that have been underfunded or have more demand now because of AI.

Most businesses have been constrained by how much software they can produce at a given cost, how many sales reps they can hire, how many marketing campaigns they can run, how they can do outbound customer success motions with enough tailoring, how they can find more risk in their business and prevent it, and 100s of other things.

When AI makes it possible to do more of this, investment goes back into the business. The companies that better serve their customers win over the long run, and those that just try and find savings end up doing worse.

[Sam Altman @sama]

OpenAI Robotics is hiring, looking for exceptional full-stack hardware, ops, systems, and ML engineers to help us program and manufacture robots that are useful for society.

AI should be able to help people in the physical world. In the short term, we are focused on robots to support skilled workers to build our future infrastructure; in the long term, we imagine everyone having a personal robot doing anything they need.

Our world simulation research program, led by Aditya Ramesh (@model_mechanic), has evolved over the past year into OpenAI Robotics. Progress is rapid, and based on a foundation of co-design between robotics hardware and ML research.

If you love working hands-on across the robotics stack and want to build the future, please consider joining us. Send an email with your background and evidence of exceptional accomplishment to: [email protected]

[Yuchen Jin @Yuchenj_UW]

Google is fighting every final boss at once:

OpenAI & Anthropic in models, Nvidia in chips, AWS & Microsoft in cloud, Meta in ads, Tesla in self-driving, Apple in phones and OS.

At $4.6T, it feels weirdly undervalued.

[Jason Shuman @JasonrShuman]

I spent the last week in over a dozen pitches with robotics companies across Silicon Valley, NY and Europe...then I looked at the US Census Bureau Data

Turns out 88% of US manufacturing plants don't own a single robot...and that's the opportunity Founders are seeing.

Despite the endless deluge of humanoid robot demos and "AI factory" hype in our feeds, nearly 9 out of 10 American factories look exactly the same as they did 20 years ago.

Manual labor, mechanical machinery, a retiring workforce and challenges in filling roles.

The reasons why they haven't been "updated" historically breaks down into two clear buckets that I call:

1. The Integration Iceberg: A robot arm might cost $25,000 and has come down in price, but the custom tooling, safety cases and software integrations to make it work cost $125,000.

2. The Agility Tax: A traditional robot does one thing a million times. But the average US shop does "high-mix, low-volume" work. To reprogram a robot for a new part has required an expensive software engineer and could take days depending on engineer availability.

The next generation of massive robotics outcomes won't come from building shinier hardware for the 12% of factories that are already automated.

It will come from the Founders solving the integration and business model friction for the 88% that aren't.

If your GTM strategy doesn't solve the 18-month ROI math of a shop owner in Ohio who needs financing, fast onboarding and the ability for the robot to handle a variety of tasks, then you're likely going to struggle.

If you're working on a robotics business solving our countries biggest talent bottlenecks, I want to chat.

[Abhay @AbhayVenkatesh1]

I just published The AI Economy (link in thread):

I am surprised that most people — even in 2026 — are applying the same mental models that they were in the internet economy to the AI economy ...

[Akshay Chalana @Ac2zoom]

@Picogrid @SVDG_official Congrats!

[Afshine Emrani MD FACC @afshineemrani]

1/5
I'm a cardiologist. I have spent twenty years watching cholesterol destroy arteries, trigger heart attacks, and kill people I care about.
Today, Eli Lilly presented data that may begin to end that era.
VERVE-102. A single infusion. One dose. It uses base editing to permanently turn off the PCSK9 gene in your liver.
Presented today at the European Atherosclerosis Society Congress:
88% reduction in PCSK9.
62% reduction in LDL cholesterol.
Sustained up to 18 months.
No treatment-related serious adverse events.
One infusion. Not daily pills you forget to take. Not monthly injections. One dose — and your cholesterol may stay low for the rest of your life.

[Akshay Chalana @Ac2zoom]

@ArmaanS69767050 @itsware_ Congrats on the launch!

[Joe Harris @_joe_harris_]

By this time next year, Meta and OpenAI will both have leading embodied AI models.

But neither will have robots in production

[Lukas Ziegler @lukas_m_ziegler]

JUST IN: Two-year-old British startup Humanoid has just signed a deal to deploy 1,000+ humanoid robots into Schaeffler's live manufacturing operations.

One of the largest humanoid rollouts ever announced.

But buried in the contract is an even bigger number.

As part of the deal, @SchaefflerGroup becomes Humanoid's preferred actuator supplier, covering 50%+ of Humanoid's joint actuator demand through 2031.

The contract specifies a "seven-digit number of actuators."

That's at least ONE MILLION actuators.

Do the maths on that and Humanoid is implicitly committing to shipping around 100,000 robots across all its clients over the next five years.

Phase one kicks off December 2026 across two Schaeffler sites in Germany.

@TheHumanoidAI was founded in 2024, unveiled its robot in September 2025 after just a SEVEN month development cycle. It's operating on $50M in founder-led capital with 200 engineers from Apple, Tesla, Google, Boston Dynamics and NVIDIA

By the way, the Schaeffler angle gets even more interesting. The German giant is now engaged with roughly 45 humanoid robotics players worldwide, simultaneously the most aggressive industrial buyer of humanoids AND a preferred component supplier to the robots it's purchasing.

As one writer put it perfectly: Schaeffler is becoming the NVIDIA of humanoid robotics.

Congrats @ArtSokolov! 🦾

Read more here: https://t.co/3WA6quSD8X

~~

♻️ Join the weekly robotics newsletter, and never miss any news → https://t.co/GoA3ZuwoPB

[Joe Harris @_joe_harris_]

robotics needs better talent, not just ideas or capital

get good at any of these and become the person every robotics team is trying to hire:

autonomy stack:
– state estimation, planning, controls or the in‑house stack nobody else can touch

sim & test infrastructure:
– lossless logs, reproducible sims, rl loops (nvidia isaac sim, gazebo, mujoco)

fleet ops & deployment:
– ota updates, connectivity, getting data off robots in the field (greengrass, alloy, formant, or duct tape)

data, debugging & replay:
– figuring out why the robot did what it did, logs, time‑series, post‑mission analysis (mostly homegrown, rerun/foxglove, alloy)

embedded & edge systems:
– getting all of this to run on jetson / rb5 / weird industrial pcs

safety, compliance & verification:
– kill switches, test harnesses, ethics boards, fda submissions, and the standards work nobody wants to do

data engine & labelling:
– building the labelling, eval, and feedback loops that keep the robot from drifting into chaos

go to market & raas:
– pricing, contracts, usage‑based billing, customer success for robots‑as‑a‑service

if you’re trying to jump into robotics (or want to work with us), my dms are open 🦾

[Karan Goel @krandiash]

42 is a great number to be on any list in my book

All of these companies are amazing

[Sumedh Sontakke @SOTA_kke]

💯. From my experience:
1. the tail of problems in robotics is extremely long and fat
2. We don’t yet have models capable of solving most tasks with 99.9* SRs. While action chunking is THE innovation that has fueled this recent robotics explosion, we are due for another similar breakthrough
3. Robot FMs are not yet great at compositionality of motions (can’t combine motion A and B in a contextual way)
4. Robot hardware is not mature enough yet (when you pick up a box off the ground imagine the sensations you experience. The box digging into your knees, your nails trying to get underneath the box). The sensors for this kind of manipulation do not exist. Collecting this kind of data is a nightmare - the teleoperator cannot feel what the robot feels so collection is slow and imprecise
5. No one knows what kind of data is helpful for robotics (no one knew that for LLMs, but we used what we had). Such “free data” doesn’t exist for robots
6. Each deployment is different and due to lack of compositionality, data collection and model training often needs to start from scratch for every deployment

[Akshay Chalana @Ac2zoom]

With the Uber GO-GET announcement, I think they’re going to start moving towards buying Expedia and OpenTable.

[Akshay Chalana @Ac2zoom]

@amruthagujjar Very excited to read!

[Amrutha Gujjar @amruthagujjar]

Over the past three years, we have been building and closely studying a new class of software: agentic products.

These systems are not simple interfaces on top of models. They are composed systems that plan, take actions, maintain state, and operate across tools and environments. Designing them requires new abstractions, new architectures, and a different way of thinking about software boundaries.

The Design of Agentic Products is a deep dive into how these systems actually work.

We cover first principles, core system patterns, orchestration and memory, and what production-grade implementations look like. We also break down real use cases to show where these systems succeed and where they fail.

If you are building or thinking about building with agents, this is meant to be a practical reference, not a high-level overview.

Coming soon!

[Marc Benioff @Benioff]

I’m locked on, @DavidSacks! We’re hiring 1,000 new grads & interns right now to ride the AI exponential. You are right they said AI would kill entry-level jobs. Meanwhile these grads & interns are building it — powering Agentforce & Headless360 at Salesforce. 🚀 New grads: Drop your resume to @salesforcejobs or [email protected]
#FutureForce #AI

[Amrutha Gujjar @amruthagujjar]

Humans are a lot like LLMs

[Akshay Chalana @Ac2zoom]

Claude Cowork has been transformational for my work, but I don’t think a new app will be the control surface for everything I want to do. I think the primary agent interface that we’ll all be using in a year will be Chrome and Siri. Can’t wait for MCP and agentic loops there.

[Anand Kannappan @anandnk24]

People are misreading the SpaceX/Cursor deal as an M&A story. It’s actually a bet on what the real bottleneck in frontier coding models is.

xAI has struggled to close the gap with Claude Code and Codex. Cursor sits on the best corpus of developer traces in the world. The deal lets Cursor train Composer on Colossus while xAI runs the same recipe on Grok. Both sides find out, at the same time, whether Cursor's data is actually the difference.

The option structure reflects that uncertainty. If the training work ports over, SpaceX buys Cursor and owns the pipeline. If it doesn’t, they pay $10B for the experiment and walk. Either outcome, Grok ends up stronger than it would have been, and xAI gets an answer to a question it couldn’t answer internally.

The part worth holding onto: a pre-IPO company just priced a live experiment to figure out whether real developer traces are the scarce input in coding agents. $10B is what they’re paying to run it. $60B is what the answer is worth if it comes back yes.