
Sairee Chahal
54.5K posts

Sairee Chahal
@Sairee
#UniverseGirl 💜 @SHEROES @MahilaMoney @AppreciateVC employment entrepreneurship capital for women #womensinternet













Live from Code with Claude: we're launching dreaming in Claude Managed Agents as a research preview. Outcomes, multiagent orchestration, and webhooks are now in public beta.



Coinbase is now testing 1 person teams + AI agents and announced laying off 700 employees. Other companies doing this (layoffs + AI): 1. Shopify: No new headcount unless you prove AI can’t do the job. 2. Block: Cutting ~4,000 roles (~40%); Dorsey says AI lets much smaller teams do more. 3. Klarna: Its AI assistant now does work equivalent to about 700 support roles. 4. Duolingo: Went “AI‑first,” telling teams to rebuild workflows around AI before hiring. 5. Salesforce: Paused new engineering hires after AI tools boosted dev productivity ~30%. 6. Amazon: Cutting about 16,000 corporate jobs this year in an efficiency/automation push. 7. Meta: Cutting ~10% of staff and freezing thousands of open roles as it doubles down on AI. 882 jobs per day disappearing in tech. This is the pace right now. And I think that's going to accelerate and move beyond tech. My POV: Every single one of these companies is telling you the same thing: one person with AI can do what used to take a team. They're literally saying it with their org charts. If you're employed, build a 1 person team on the side. If you're laid off, build one today. The tools that made your role redundant are the same tools that let you build your own company. The biggest wave of new startups is going to come from people who got restructured out of exactly these announcements.

AI agents now have phone numbers. Like, real phone numbers. Saperly just launched. The first phone carrier built only for AI agents. Your agent gets its own number. Voice, SMS, routing, compliance, all live in seconds. → Same number every time it calls → Same caller ID across every product → Voice and text on one line → Provisioned in 5 minutes → $5 signup credit, first number free for 30 days For the last 3 years AI agents have been borrowing infrastructure built for humans. Email accounts, browsers, phone numbers leased through legacy telcos. That just changed. This is the first piece of infrastructure I've seen built from scratch for software that calls humans, not the other way around. I share insights like this daily in my free WhatsApp community ↓ go.stayingahead.com/X

Exciting News: We've signed a definitive agreement to join Palo Alto Networks! We started Portkey on a single idea: that AI in production would need a control plane. Not a feature, not a category somewhere on the side of the stack. Infrastructure. A place where governance, observability, security, and routing converge so that enterprises can run AI the way they run any system they actually depend on. Three years later, we route trillions of tokens per month for teams running AI at real scale. The idea became the floor. AI control planes don't win by being clever, they win by becoming standard. The default. The thing nobody questions is in the stack. That's the next chapter. Getting there at the speed the moment requires means joining a company with the depth, reach, and enterprise footprint to make the standard real. Palo Alto Networks is that company for us. Link to blog post: paloaltonetworks.com/blog/2026/04/s…



For the last three years, a startup in Bangalore has been obsessed with a pursuit that typically invites raised eyebrows, naked skepticism, and accusations of stealing from sci-fi: @dognosis is training dogs to detect cancer. And until you've spent time at their facility - a former pomegranate farm in the outskirts of Bangalore - perhaps skepticism is the rational response. But Dognosis isn't betting on some pie-in-the-sky idea or some charming novelty act, they're betting on evolution. @akadogluk and @Itamar_Bitan based their company on the fact that the dog's nose - a product of fifteen millennia of co-evolution with humans - can detect the faint chemical trace of cancer in your breath at a resolution that our machines, algorithms, and laboratory tests have never come close to matching. We've known this fact for decades. We've consistently failed to do anything meaningful with that knowledge. The missing link has been figuring out what the dog's nose knows, and applying it in a standardised, scalable, and clinically validated way. Dognosis is building this missing piece of the equation i.e. the translation layer that allows the dog's nose to speak a language medicine can understand, enabling us to harness an ancient biological intelligence and plug it into our modern medical infrastructure. Maybe you've read the paragraphs above and retained your skepticism. That's fair. But this past Friday, the Journal of Clinical Oncology - the world's most influential cancer journal - opted to make life much harder for the skeptics. On Friday, the JCO published Dognosis' landmark study on breath-based multi-cancer detection - the largest of its kind ever conducted - showing that a team of trained dogs, equipped with sensors and AI, could detect multiple cancers from breath alone at 90%+ accuracy - including at Stage I, when it matters most - for $2 a test. According to Akash, it proved "that everything we’ve known about the dogs is true". Needless to say, it's a genuine milestone for Indian healthcare, health-tech, deep-tech, and, uh, dog-tech, that deserves far more attention than it's gotten so far. To help change that, we were lucky to have Akash stop by the Tigerfeathers editorial desk this past week to unpack the Dognosis journey - helping us understand what they're building, how they're doing it, why it matters, and what comes next. From where we're sitting, Dognosis is an n-of-1 Indian startup with an n-of-1 story that everyone in the Indian tech ecosystem should be aware of. If you've been intrigued by what you've read so far and you're keen to go deeper, dive into our piece here👇 tigerfeathers.in/p/dognosis-unl…

Turbine Products and Industrial Bottleneck The reason turbines are increasingly becoming an industrial bottleneck is because the only turbine technology that is in mass production today is the hyper-car class of turbine technology, imagine the only car your buy was a Lamborghini, a Bugatti, or a McLaren… that’s where the power turbine market is. Nobody is mass producing the Toyota and Honda class of turbine technology. All turbine product specifications currently in mass production are maximally efficient, and maximally thermodynamically performant. The products available in the market are simply not designed for rapidly scalable production. It’s all single crystalline metallurgy, refractory ceramic coatings and laser drilling. Yes, this stuff is hard to make. No it doesn’t need to be this way. Nobody is still mass producing your grandfather’s turbine. As demand balloons, order books swell, prices surge and lead times are now blowing out to 60 months!… That is more than enough time for a new entrant to come in with a basic, low cost, short lead time mass produced offering that enters the market and quickly captures 40% market share, just by keeping product specs simple enough to scale production capacity horizontally with low lead accessible plant equipment. This is an ironic example of the highest tech sectors needing some low tech solutions. If you see things holistically and you genuinely know what you’re looking at, the world looks different and the solutions to the biggest problems are kind of obvious to you, but this type of observation is just not that common. The real bottleneck in the world is that not many people see the world this way. I guess because it’s such a hard won perspective.
