Mohit Soni

423 posts

Mohit Soni

Mohit Soni

@mohitsoni

New York, NY Beigetreten Şubat 2009
241 Folgt306 Follower
Henry Shi
Henry Shi@henrythe9ths·
I recently exited my $150MM+ annual revenue startup that's raised $200MM in venture funding and discovered something shocking. The way 99% of founders build companies is fundamentally broken. There are 4 funding models, but ONE new model works best in today’s AI era. The traditional models are failing founders: • Venture Capital: Founders often end up with less than 10% ownership and often walk away with nothing personally, even if the company is worth "billions" on paper • Bootstrapping: Founders have to make large personal financial sacrifices and 80% fail within 18 months • Boot-scaling: Founders drain runway and bet everything on a scaling event that fails 72% of the time. However, a small group of smart founders are using a new funding model to build AI-native companies. These founders are reaching $4-6M ARR in a matter of months, and they own 90%-100% of the company. Some are even building $3-5M ARR businesses with zero employees using this exact funding model. So, after talking to 100+ founders, I created an in-depth 10-page guide sharing: • Head-to-head comparison of all four funding models with EXACT metrics • Founder ownership percentages, dilution, and liquidity timelines for each model • How AI has changed what's possible ($3-5M ARR with zero employees) • Expected revenue growth, profitability timelines, and liquidity events • Your probability of success with each funding model (both as a founder and investor) • The psychological reality nobody talks about (what it actually FEELS like) • The shocking difference in founder stress levels and happiness Want the complete breakdown and analysis? • Like and share this post • Comment "Funding" • Follow me so I can DM you
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Henry Shi
Henry Shi@henrythe9ths·
There's a shocking fact about AI that nobody tells you: You can catch up to the public AI research frontier in just 2 weeks. Yes, really. I've built a $150M annual revenue startup over the last 8 years and If I were to start a company today, I’d drop everything and go all-in on AI. But like many busy software builders, I felt lost—overwhelmed by the noisy, crowded and fast-moving modern AI landscape. And I wasn’t alone. So I spent my entire holiday diving deep into AI research—reading 30+ papers, watching hours of lectures, analyzing trends, and catching up to the research frontier. ✨ Here’s what I learned: - You don’t need months (or years) to catch up. - You don’t need a PhD or decades of ML experience. - You need fewer than 20 papers and 2 weeks to understand the major breakthroughs shaping AI today. It's because the technology is extremely nascent and most techniques that came before are no longer relevant: - ChatGPT is barely 2 years old and Transformers are only 7 years old. - Most game-changing discoveries happened within the last 4 years, driven by a few breakthrough ideas, scaling laws, and efficient matrix multiplication. The biggest secret? Many groundbreaking AI papers with thousands of citations are surprisingly simple and applied, like adding "let's think step by step" to the prompt, or simply asking the LLM over and over again to improve its answer (Self-Refine). I realized there are tons of founders and builders in the same boat—wanting to dive deeper into AI but unsure where to start. I've created an essential AI Guide that helped me catch up, in just 2 weeks, to the frontier of public AI research to figure out where the next opportunities and gaps were: - Curated list of only the most important papers - Simple explanations of key concepts - Clear pathway to understanding the frontier of modern AI It’s perfect for: - Founders expanding into AI - Builders wanting to innovate at the frontier of AI - Investors looking to separate the signal from the noise 👇 Want the full guide? - Like and Share this post - Comment "AI Guide" - I'll send you the complete guide (ps, I’m also teaming up with @VishalVasishth, co-founder of @obviousvc with @ev (focused on large-scale societal impact companies like Twitter, Medium, Beyond Meat), to host a small meetup to discuss what's working and needs to be solved in the AI stack in SF. Message me if you're interested)
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Mohit Soni
Mohit Soni@mohitsoni·
@kenwheeler Do you have any recommendations for floor mopping robots?
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patagucci perf papi
patagucci perf papi@kenwheeler·
I’m about to buy a roomba for the sole purpose of taking my wife’s passive aggressive vacuuming away
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highscalability
highscalability@highscal·
How Uber Manages a Million Writes Per Second Using Mesos and Cassandra Across Multiple… goo.gl/fb/ffYvuq
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Vinod Kone
Vinod Kone@vinodkone·
Twitter comes out with its mesos numbers. 250k containers. 30k nodes. #MesosCon
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D2iQ
D2iQ@D2iQ·
Thank you for the #Mesos 1.0 cupcakes @kubernetesio! They are delicious!
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Sunil Shah
Sunil Shah@ssk2·
An introduction to the incubating Apache Myriad project to run Hadoop on Mesos with @mohitsoni from @mesosphere!
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D2iQ
D2iQ@D2iQ·
#DCOS is #opensource! Download it today at dcos.io and see why it's the best way to run containers.
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DC/OS
DC/OS@dcos·
Let's do it! dcos.io #dcos
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D2iQ
D2iQ@D2iQ·
We raised a Series C round, announced a new product called Velocity, and took Marathon to 1.0. Learn more here: mesosphere.com/blog/2016/03/2…
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