Hey everyone, I’m Shubham.
I’m building BisonTech, a defence-tech startup.
BisonTech started with one belief: the future of defence will belong to teams that can see faster, think faster, and act with better intelligence in any environment.
This is the beginning of the BisonTech journey.
Connect with my journey as we build the next era of defence intelligence.
BisonTech is coming...
All these motherfucking AI tech assholes never shut the fuck up about open-source this model… open-source that model…
But where the fuck you supposed to run that heavy-ass shit?
On our goddamn asses?
@elonmusk@bot Humanity finally built AI agents capable of running the world, and somehow we’re still using them to order domains and play video games from the couch
Open-sourcing my old project: GitTime
If you’re a student who builds projects in bursts and forgets to commit regularly, this tool is for you!
It simulates a realistic, multi-day developer workflow across your repositories with custom activity patterns, working hours, and AI-generated commit messages.
It’s 100% open source (Next.js 14, TypeScript, Tailwind, MongoDB). Feel free to fork it, use it for your projects, or submit your first PR!
🔗 Link to GitHub in the reply below 👇
cc @Hiteshdotcom@kirat_tw@piyushgarg_dev@kunalstwt@waitin4agi_@levelsio@achinamayya@Ishansharma7390
Why @ycombinator, why?
How much longer do I have to wait? Please select my application.
Give me one chance, and I’ll build one of the greatest companies with you.
But people forget that AI has only been around for a few years, and in the next few years, the gap between AI and humans could become as vast as the gap between humans and monkeys today.
Quick observation on why AI has exploded at work, but has been slow to disrupt consumer apps:
At work, AI follows patterns and gets rid of drudgery (good!)
At home, AI follows patterns but it generates slop (bad!)
This is why AI has taken off at work, but not so much for consumer apps and experiences (social, entertainment, dating, etc)
Much of work is drudgery - filling out forms, following processes, writing updates, reviewing boilerplate code, etc. - and AI does a great job compressing this down the boring steps so that humans can focus on the high-leverage steps. The boring/routine work is not hard, but they often take a lot of steps and you have to stitch together a lot of data. You follow patterns. AI is good at following patterns too.
Consumer attention, on the other hand, is hard to win over because people crave novelty, seek parasocial relationships, and are so cognizant of AI slop. A video of an attractive person talking loses its ability to generate parasocial relationships. In domains like social media, video, etc where authenticity is paramount, a distorted AI sign in the background can ruin the entire thing. Novelty is generated by surfing the cultural wave with something new and unique - AI slop often pattern matches to the past, after all, it’s the past that’s in the data set, and as a result, new/unique is hard
This is a form of “adversarial creativity” - and it exists in business as well. When you think about inherently adversarial activities in business - like sales and marketing, where novel messaging, competitive move+countermove dominate - AI has received the most scrutiny for generating slop. No one wants the same sounding AI generated cold emails. No one wants to use AI slop software. You have to go outside the model in order to really land a message.
Perhaps this is the ultimate human-in-the-loop problem, because to do something fresh and unique requires adversarial creativity. Or maybe with enough advancements around being able to observe and react in real-time, future AI models will be able to say something novel by taking into account the X timeline from the past 24 hours.