Yashraj Shukla

This is me so far in the journey which started two years ago with one dream to bootstrap a company Top Learning: Speed of execution is your only friend when new data changes your reality every week. Can sense the Sun on the horizon, inflection point is near. God bless the hustle

@paraga your premise was so far ahead in time, yet you think you capitalised on the first mover advantage enough?

Parallel is built for a world where agents are the primary users of the web. Agents can now autonomously pay per API call for web access via Parallel using MPP. parallelmpp.dev

Karpathy's autoresearch loop (write code, train for 10 minutes, check if it improved, keep or discard, repeat) is getting cloned in other verticals to improve models. Bitmind tshipped a deepfake detection toolkit built on the same chassis: point an agent at 60+ image datasets overnight, wake up to 50 iterated experiments and a competition-ready model. Thanks to Karpathy, this sort of autonomous ML research is becoming an essential primitive for frontier AI teams.

using context graphs to find best gift for parent's 28th marriage anniversery. ~10 days left, but too lazy to sit and think. so index'ed transcripts of >50 hours of call recordings with my mom and dad into the context graphs sitting on top of supermemory and graphiti. now i let claude 4.6 query it (enterprise, zero retention plan). for mom, it suggested me to buy the most no brainer thing of all: gold bangles🤦🏻‍♂️ what it recommended me for dad blew my mind - a trekking tent, could not even think of it in a million years, but makes so much sense, he probably mentioned it years ago that he struggled in an overnight camping trip. this technology is surreal

@ChinmayKak @itsOmSarraf_ There are categories to such events, if it’s on a weekday, it’s a marketing event where they try to sell you product offerings. Good ones are mixers/talks and are likely on a weekend, the bar to get into the event also matters. 6/10 events I go end up being pretty relevant.

Hot take, almost all tech events I have attended in blr are completely performative and the crowd is not that great.

@contextkingceo Is it different from zep?

We've raised $6.5M to kill vector databases. Every system today retrieves context the same way: vector search that stores everything as flat embeddings and returns whatever "feels" closest. Similar, sure. Relevant? Almost never. Embeddings can’t tell a Q3 renewal clause from a Q1 termination notice if the language is close enough. A friend of mine asked his AI about a contract last week, and it returned a detailed, perfectly crafted answer pulled from a completely different client’s file. Once you’re dealing with 10M+ documents, these mix-ups happen all the time. VectorDB accuracy goes to shit. We built @hydra_db for exactly this. HydraDB builds an ontology-first context graph over your data, maps relationships between entities, understands the 'why' behind documents, and tracks how information evolves over time. So when you ask about 'Apple,' it knows you mean the company you're serving as a customer. Not the fruit. Even when a vector DB's similarity score says 0.94. More below ⬇️

@amansingh0802 @ThineAI @pratyush_r8 @siddsax @siddsax providing access when? 🥰🙌

What a lovely onboarding by @ThineAI. Thoughtful, poetic, and intentional: the kind of detail that tells you the builders care about the craft. LFG @pratyush_r8, @siddsax & team 🚀

@amuldotexe Translation: start studying deep learning

Hypothesis: If there's one thing you could learn from my 15 year tech journey, it'd be "do the hardest possible technical work earlier in the career so in later years you have more optionality & don't have to pivot in late 30s" those who do the hardest possible technical work earlier have more optionality later I got into analytics & regression modeling but didn't take the next step to go deep into tech, something I should've done and would have been a better fit, I somehow couldn't see the ROI on the same and kept operating from a lower leverage point for complacency / laziness / ADHD whatever abc reason I was lucky the 2 career waves I rode of analytics & product management worked out well in my time, but I still believe my career would've been on a different trajectory had I got into core engineering far earlier I realize we don't control our life & it is what it is, but that was a miss that happened for an inexplicable reason that cost me a lot of time & quality of life

@sunw00agi the whole website is customisable, so many themes, they really took over 10typing fingers and so many other legacy websites

@whynesspower how did u made your dash look like that?

i am really hapyyy, today touched 100+ WPM across all test formats on monkeytype :))

@hrdktwt 120 second test was so hard, you need muscles onlyy

@whynesspower hell yeah, lfgg

@henrythe9ths Mercor, Turing, Handshake and micro1, almost everyone in the staffing agency pivoted. I’d say there are a lot more to come

He grew a company 35x in one year to $250M+ at 25. He’s the same kid who came to the US from Tehran at 10 without knowing a word of English. This is the untold story of Ali Ansari and micro1, which just cracked the top 10 on the Lean AI Leaderboard with $250M+ revenue and 80 employees. If you are building a lean AI company or want to sell to the top AI labs, read on for the full playbook. Ali built 2 companies before college. At Berkeley, he launched a software dev agency and started hiring international engineers. The interviews alone were eating 30–40 hours/week, so he built a tool to automate them, using GPT (one of the first AI recruiters in 2022). That insight eventually became micro1. For 2 years, it grew steadily with two business lines (an AI interviewer SaaS and an engineering marketplace) with happy customers. Then a data vendor approached Ali with an unusual request: hire 700 engineers to train AI models. That one conversation changed micro1’s trajectory. Ali realized they had accidentally built what every major AI lab desperately needed: a system to find, vet, and manage domain experts at scale across industries, at volume and fast. He then made a decision most founders would never have the nerve to make: He killed both working businesses and bet the entire company on going direct to the labs, with no safety net or guarantee that it would work. But the bet paid off, resulting in 35x growth, as they went from $7M ARR to ~$250M in one year. None of it came easy, and this level of growth became possible only after Ali solved the hardest problem in this space: How to sell to AI labs where buyers are deeply technical and part of tight communities where reputation travels fast. So I spent 10+ hours going deep into the decisions behind how micro1 built, sold, and scaled within the AI ecosystem and turned it into an actionable playbook for founders who want to sell to researchers. Inside, you'll get: • The 3-stage sales sequence Ali uses to close research deals like OpenAI and xAI • How he got into Stanford research circles with zero connections (and how that helped him close deals) • The proof of concept strategy: The dos and don’ts when researchers are evaluating you • How Elon Musk accidentally handed micro1 their biggest sales breakthrough • The net expansion playbook for enterprises and Fortune 500 companies (and what is converting fastest) • The full AI stack that powers micro1's recruiting engine • The incentive philosophy Ali rebuilds individually for every core team member every quarter Originally, I put this together as a resource for founders I work with directly. But the ideas and insights are too valuable not to share, so I'm giving it away publicly. Founders who crack AI sales at this hyperscale usually keep it close, but Ali shared every piece of it. So if you are building a business around frontier AI and research, grab this right away. It will save you months of costly relationship mistakes (Link in the first comment). Ali and team, welcome to the Leaderboard!

@harshraj_dev I agree 100% It’s a bit artificial to find co-founders this way

@whynesspower Still, I would highly recommend finding somebody who m you know prior or work with.

10+ matches in 5 hours. New match every hour Thankyou YC 🙌

@mgrvjn Yeah among the noise of non-technical dreamers and unemployed students trying to take their shot at startups, it’s a bit difficult to navigate, but found a couple of good folks there as well.

@whynesspower I got so many matches, I opted out because it became difficult to manage and nothing worthwhile came out of it

@Rishabh8Singh @ycombinator You? Please enlighten

Who's gonna tell him @ycombinator

@Ruchicodess The machine from Krish to predict the future

@whynesspower what are you building?

@spiceb1ts Nice idea man! surely

@whynesspower So you have read it a long time back. That's good, you can reread it though. Will give you a completely new perspective.

Every time we go out to drink tea, we take copies of Thiel’s “zero to one” and finish a chapter. This asks for starting a reading club? Good hobby to pickup

@icantcodefyi Just came back, went to the high street

@whynesspower chai pine chaloge?

Requesting a benchmark rank list of all the benchmarks, so that I know which one is what, before anyone claims to be the next biggest AI app builder 😭🙏

@amnxnet I scroll X for five minutes and find another AI slop builder with their new launch video or reporting $100 billion in recurring revenue. Is the VC community absolutely blind to their mega glorified monopoly ideology

This is one of the best launch videos I’ve ever seen…

@spiceb1ts haha, that was one of the most hilarous jokes I read as an 8th grader. now when i think about it, it was indeed a good book

@whynesspower See everyone will have their “three books”, for me one of these 3 includes “Hitchhikers Guide to Galaxy (series)”. And I would say it’s more than a fiction, it will also give you many perspectives & philosophical things and 42.