Ankit Kumar

Been building Uncubed.me for a month now, it helps founders go from idea → users in hours. Still figuring out marketing... Here’s a quick demo 👇 My Vision: AI taking founders from idea to users in hours not months. #buildinpublic #SaaS #ai

@shivambhadani_ tech people are too busy fixing the stuff marketers are writing threads about

When I scroll through X, I observe that very less people here are obsessed with tech and engineering. Most of are seems to be marketing accounts only posting about SaaS, Vibecoding, Agent etc.

@hamptonism this looks like duolingo got a phd in linear algebra

im scared chat.

@signulll openai bout to get judgeGPT’d by 12 people who still think “chatgpt” means google with extra steps

i would be HORRIFIED to have my fate decided by 12 randomly selected americans whose strongest shared skill is unsuccessfully ignoring jury summons lmao. good luck to openai.

@kimmonismus months behind? thats just a firmware update away

The US moat is melting, Demis Hassabis, the CEO of Google DeepMind told CNBC. "China's artificial intelligence models may be just "a matter of months" behind U.S. and Western capabilities. Chinese AI models are closer to U.S. and Western capabilities "than maybe we thought one or two years ago." The only thing China still lacks is the ability to explore its own breakthroughs, such as Transformer architecture. For now.

@signulll fighting for a “good job” in an economy built on bad ones is the funniest dystopia ever

isn’t it fascinating that people are fighting for “good jobs”?

@Adriksh maybe the real hack was ignoring every buzzword and still ending up running the buzzword machines

Be Linus Torvalds > writes an OS as a hobby accidentally changes computing forever > picks C because abstractions lie works close to hardware, trusts nothing blindly > builds Linux, lets the world fight over it > creates Git out of spite for bad tools > says exactly what he thinks, no PR filter > ignores trends, frameworks, hype cycles > lives quietly, codes when it matters > doesn’t sell courses, doesn’t sell motivation > still relevant decades later because fundamentals don’t age Did Linus solve tech by not playing the tech game at all?

@theJayAlto so just 2 weeks of hyperfixation and i can quit my job got it

i have a theory that it takes two weeks of obsession to reach the top 10% of a field, two months to reach the top 1%, two years to reach the top 0.1%, and two decades to reach the top 0.01%.

@gokulr vertical ai founders about to learn the hard way that slope > moat

VERTICAL AI CHALLENGE Vertical AI Founders: You've spent 2+ years building your agents, training your model on your customers' data, embedding into workflows, creating a powerful GTM motion, all the best practices. You've beaten back challengers and are the #1 or #2 player in your vertical. I'm sorry, you cannot relax. In fact, you need to massively up your game. Turns out you are facing an existential challenge: long-horizon agents (eg: Claude Code). Agents that are not trained on a specific domain, but can reliably work for hours or days on end in pursuit of a goal, self-correct, and actually do stuff. I'm sure many Vertical AI founders will say: "Oh, we are not worried. We are the system of record for decision traces. We train on enterprise-specific context. That's why these horizontal agents can never catch up with this." You might well be right. But, but, but ... you cannot afford to bury your head in the sand. These long-horizon agents will get better very, very quickly. You need to understand precisely how good they are at the exact jobs you've built your agents on. You cannot wait for someone else to do this. For example, if you're a legal AI company with an agent that automates contract review, you must compare how good your specialized agent is versus a general-purpose long-horizon agent that's simply given the contract and asked to perform the same review. My challenge to you: Assign a strong engineer on your team to focus 100% on using long-horizon agents (with minimal context, other than just the contract in the example above) to compete with your custom-trained agents. Benchmark how the long-horizon agents perform vs your agent. Rinse and repeat it every few months. Like with most other things worth measuring, what matters is the rate of improvement (the "slope" vs the Y-intercept). If the long-horizon agent is 30% as good as your vertical agent on Day 1, but 50% as good on Day 60, and 70% as good on Day 120, you need to reassess your product strategy. AGI is coming for everyone. Long-horizon agents are the closest we have to AGI, and as a Vertical AI company, you need to figure out how you compete and survive. Game on.

@0xDesigner people out here treating AI copilots like a calculator when it's literally a genie with version control

how tf are you not obsessed with vibe coding. like how could you just wake up and think “i have the ability to verbally ask for any piece of software today and it will just magically appear” and then just shrug and go on about your day. idgi.

@Codie_Sanchez same, it's like my weekly reality check and ego destruction session in one chart

I look at this weekly.

@almonk somehow every mac dev hits that point where they rebuild xcode’s tabs but sexier

made something I wanted for a while: a high performance custom tab/splits library in swift for native Mac apps. with support for drag/drop, CoreAnimation accelerated transitions, and more. spent a lot of time on the polish of this thing to feel snappy, but fun.

@TheGeorgePu quiet money > loud panels

The most successful people I know aren't on Forbes. You've never heard of them. They don't want attention. They're just building. Meanwhile we study the ones doing CNBC interviews and Davos panels. Those are performances. Not blueprints.

@0xgaut peak 2026 productivity is letting the ai code, design, argue with itself and hoping one of them ships something before monday

Can I code? No Can I design? No But I have 15 agents running in the background with 10 different claude code instances on my screen and I have no clue what half of them are doing

@ChShersh waiting for the CTO to say “we’re Claude native now” like it’s a real architecture shift

2016: Move everything to Cloud 2026: Move everything to Claude

@chatgpt21 devs bout to go from coding to prompt engineering full time once that thing hits max speed

When Codex 5.2 XHigh is fast it’s going to change software so much.

@HSVSphere bluetooth was clearly designed by someone who never used a mouse mid-fight in apex

Man, I hate cables. However, I hate the main solution to wireless, which is Bluetooth, even more. Why can't I poll more than 144hz??? Why do I even need to poll, why can't the device poll me??? It's fine for wireless keyboards and such, but it stinks for mice. Don't even get me started on bidirectional audio profiles (HFP) on Bluetooth 🫠

@SahilBloom fun is the cheat code they forgot to mention in business school

The ultimate long-term competitive advantage is having fun. You can never bet against the person who just seems to have fun doing the work.

@Helios_Movement guess aristotle never tried a standing desk startup pitch

"Sitting makes you retarded". -Aristotle

@emollick fake it till the compile succeeds

When my students were creating initial demos with Claude Code & Antigravity, the AI would often spontaneously decide to do Wizard of Oz demos. The AI would build an interface, but not underlying logic. Code would (live!) run the interface behind the scenes to make it look working

@aymanalabdul nothing humbles a team faster than realizing “better product” didnt mean “more people know you exist”

Overlooked reason for why companies stall: Neglecting RPE (revenue per employee) One of my clients came to me with 2.8% year-over-year growth When I looked at their P&L for the previous 3 years, all I saw was their engineering and design hires continuing to increase Their hypothesis: Better product = more customers aka ”this is just how SaaS works” - it takes a long time and then eventually takes off But when I looked at their analytics: • Nothing out of three years of shipping had moved the needle • They spent almost nothing on top of funnel and almost everything on bottom funnel • They improved the product for existing customers, but forgot to go out and attract new ones In other words: their hypothesis flopped So we completely flipped the P&L. Shifted investment to acquisition Their results? In 2025, they grew 81% YoY That’s 2.8 → 81% with the exact same product We simply revisited and analyzed the RPE and where the investment was being allocated The lesson here is simple: Track your RPE weekly It’s the clearest litmus test to know whether you’re hiring to scale revenue or discover it