Puneet Singh

CEO at XHawk

[Puneet Singh @xhawkCEO]

Everyone is measuring the wrong thing. The biggest impact of AI isn’t that experts become more productive. That's a small outcome in the grand scheme of things.

It’s that millions of ordinary workers gain capabilities that previously required years of specialized learning and education. AI is not just a productivity tool. It’s an amplifier of human capability!

AI isn’t just helping people do their jobs better. It’s helping people do jobs they couldn’t do before.

[sarah guo @saranormous]

cursor, lovable, cognition numbers all a big narrative violation. wasn’t everything in the path of agi labs (especially the #1 fight, coding agents) supposed to die, not accelerate

[Puneet Singh @xhawkCEO]

https://t.co/4MEeYBLidZ

[Puneet Singh @xhawkCEO]

AI but super cool 😎

[Massimo @Rainmaker1973]

Jet-powered Porsche 911 prototype for extreme speed and aerodynamics

[🎞️ labrackprojects / Made with AI]

[Puneet Singh @xhawkCEO]

@businessbarista

[Puneet Singh @xhawkCEO]

Memory is not a second brain. That’s like calling a database company a CRM because it can store data and run logic on top of it.

To be considered a true second-brain platform, a company should own the full stack: ingestion, curation, and query/retrieval. Storing information alone doesn’t make it a brain. IMHO.

[Puneet Singh @xhawkCEO]

What if every company also had a knowledge filesystem: a software factory that captures how work gets done?

[Puneet Singh @xhawkCEO]

@jatingargiitk @ericosiu It’s a naive idea to build on your own. It’s like saying we will build our own database because we need to store data in tables.

[Puneet Singh @xhawkCEO]

Every company will build its own software factory!

[Shopify Engineering @ShopifyEng]

https://t.co/26CiLPZngw

[Puneet Singh @xhawkCEO]

@kieranklaassen Most teams lack discipline. That’s why process becomes increasingly valuable as an organization scales.

[Naval @naval]

New podcast, new format. Three founders join us.

Waste Tokens, Save Time

00:00 Three Frontier Founders

01:27 AI Software Factories

04:15 Waste Tokens, Save Time

05:47 Models Instructing Humans

09:30 Is Pure Software Dead?

12:04 You Don't Get Stuck Anymore

With @rauchg, @maxhodak_, and @bscholl.

[Puneet Singh @xhawkCEO]

@nbaschez All “company brain” products become “Enterprise Search”. Sad Reality. The situation has not changed in the last decade.

[Puneet Singh @xhawkCEO]

@hunvreus My favorite 🤟

[Gokul Rajaram @gokulr]

https://t.co/ndFngnunPX

[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.

[Lenny Rachitsky @lennysan]

My biggest takeaways from @danshipper:

1. The future of work will happen inside Codex or Claude Code. Instead of putting AI into your SaaS tool, you’ll use your SaaS tools inside your favorite AI agents' in-app browser. Dan spends all his time in Codex now—writing documents, managing email, doing research, everything. He's using Google Docs, PostHog, and everything he needs within the agent's in-app browser. The agent can see what he’s doing, and has all of his context, so he and his agent collaborate quickly and super effectively.

2. Automation is a lie—every automation needs a human. Dan's company doubled in size this year despite being incredibly AI-forward. Why? Because in order to make automation work well, you need humans making sure everything keeps working. This is why benchmarks are misleading—they measure AI on problems we’ve already framed and can score, but there’s always a higher frame.

3. PMs will win the AI era. Marcus, a former PM who previously ran Axios’s writing product, joined Every after getting super AI-pilled. Now he runs their product Spiral, and ships faster than anyone on the team. He pairs technical knowledge with spiky product sense, deep user empathy, and an eye for what matters. Dan thinks any PM who gets really AI-native will be incredibly dangerous because the building is done for you—what matters is figuring out what to build and if it’s great.

4. Full-stack designers are becoming superheroes. Designers used to make beautiful interactions that engineers didn’t want to build or couldn’t execute properly. Now designers don’t need to hand things off; they can build it themselves. Designers are naturally creative people, and AI is the perfect tool for them because it lets them bring their vision to life without the traditional bottlenecks.

5. SaaS is not dead. In fact, Dan is bullish on SaaS stocks. When users bring their own AI (via Codex or Claude Code) to use SaaS products, the user—not the SaaS company—pays for tokens. This saves SaaS company’s margins. Since the agents need their own seats, Dan predicts that agents will create massive new demand for SaaS because there will be tons of agents using these products at high volume.

6. Every company will have one “super-agent” inside their Slack that every employee will use. Dan initially thought every employee would have their personal work agent, like a shadow AI org chart, but he’s completely flipped his view. He realized agents need humans who care about them. When someone gets tired of maintaining their personal agent, it becomes useless. The winning model is one forward-deployed engineer or AI-savvy person who maintains a company-wide agent (like Shopify’s River or Viktor), and then it trickles down to more specialized team agents as models improve and become less fiddly.

7. The AI job apocalypse is not happening, but you do need to evolve to stay relevant. Models make yesterday’s human competence cheap. But because everyone uses the same models, it all looks the same if you use it the default way; it becomes commoditized slop. Humans then take that frozen competence and use it to make something new and interesting for their specific situation. The key: “ride the models”—use them for everything you do, try new models when they drop, keep turning over rocks.

8. We will read way more AI-generated writing, and we will like it. Human writing is incredibly important for things that matter, but for internal docs, planning, and email, AI-generated is often better because most people are bad at writing strategy documents.

9. Build software for humans and agents to use together. The current model is building a CLI that an agent uses independently. Instead, you and your agent should be using the app together. This creates new design challenges—agents can make a billion requests in three seconds, so you need approval flows, inboxes that summarize what happened, logs, and easy rollback.

10. Forward-deployed engineers are the new most essential role. The big model companies have teams of people managing their internal agents, and those teams aren’t going away. It’s different from traditional software building, and certain engineers love it. As models get better, this role will evolve—you’ll be managing more agents doing more things.

[Puneet Singh @xhawkCEO]

@shashank_kr @Razorpay https://t.co/1zhdldTw51
Companies interested in building their own Slash versions, please reach out to us! This is the future of software companies.

[Puneet Singh @xhawkCEO]

Why are all big tech companies building software factories?

[Aditya Agarwal @adityaag]

https://t.co/AoyPtuI9jx

[Harley Finkelstein @harleyf]

The best apprenticeship model was always the shop floor.

Now the shop floor has an AI teammate.

@tobi doing tobi things 👌

[Puneet Singh @xhawkCEO]

Great writeup! Throwing data in a store is not helpful for companies. There is so much more to do to make the data useful.

[Ashwin Gopinath @ashwingop]

Claude just made the idea of agent memory real for the community, but I'm sorry without semantics or ontology, it’s again just a glorified knowledge base, nothing like a brain.

Real brains (and Company Brain) use semantics + ontology for role/situation-specific context that humans and agents need. This is the hardest part of creating memories!!!

Final piece in our Company Brain series below👇