classic saas is a toll bridge—build once, every crossing is pure margin 🚧 🤖 native AI is a taxi: each prompt spins the meter 🚕 if fare < fuel (tokens) you stall therefore, track $/1k tokens, LTV/CAC & churn, then lock enterprise lanes before flooring the growth pedal

OpenAI's quiet endgame isn't search, it's the os for autonomous AI agents. here's how i see it: Agent wakes up (infra) -> gets wallet id (identity) --> searches agent internet --> translates any i/o (multimodal) --> executes domain tasks (apps) --> taps human shoulder via

if everyone uses the same AI models on the same data, where's your edge? real alpha: proprietary data aggregation + custom reasoning frameworks. while others prompt Claude, we're querying 39M+ verified company records.

Diligence compression math: - Traditional VC: 21 days average - With generic AI: 5-7 days - Multi-source verified AI: 4 hours source: surveyed multiple funds during samkhya customer calls The 20-day advantage compounds into portfolio alpha.

your morning coffee just got better ☕️ presenting your daily dose of startups that launched new products, raised funding or are just in the news.. click on any trending company and do an automated due-diligence immediately DM if you want to try it out:

ai must be purpose - built and verticalized for workflows

19,000 PE funds outnumber McDonald's locations in the US. $3.9T in dry powder. it sounds like opportunity but is actually the industry's biggest traffic-jam. 30,000 companies stuck in portfolios. 8 years to clear at current rates. all that powder stays dry when you can't

everything everywhere all at once

spoke with 2 CVCs over the past few days. they move slower than pure-play VCs not because they're slow at decision-making but they evaluate deals on 2 dimensions (financial ROI + strategic fit to parent corp). tools built for speed don't work for compliance.

Built an Excel parser to automate financial analysis. Hardest problem? Not OCR. Not table extraction. It's that some CFOs put years in columns, others in rows. When you transpose to normalize, the first column becomes metric names... ...and breaks everything. Financial

Hypothesis: The best investment intelligence tools feel like having a brilliant analyst who never sleeps, always cites sources, and gets excited about edge cases in balance sheets. We're building that for the private markets. If this sounds like your kind of problem, let's

this is good but is geared more towards analyzing the LLM's output than understanding the subject. the incremental marginal utility of cross-comparison and coming up with a good prompt may regress the topic to the mean since each LLM has its own strengths and may cancel out each

most fresh rounds raised are in billions now! are we in a bubble?

ChatGPT is a strong reasoning engine while Claude is a cleaner writing and tone engine.