The Kind of AI Expert We Try Not to Over-Rely On
A specific category of frequently-quoted AI commentator deserves more scrutiny than the quote volume alone would suggest.
The Editorial Test We Apply Before Running Any AI Statistic
A simple internal checklist for whether a cited AI statistic is solid enough to run without further qualification.
The Accelerator Alumni Network That Matters More Than the Program Itself
Founders increasingly report that peer connections from their accelerator cohort outlasted and outweighed the formal program content.
The Venture Firms Explicitly Avoiding AI Right Now, and Why
Not every venture firm is chasing AI deals. A minority are explicitly avoiding the category, and their stated reasoning is worth hearing out.
What a Unicorn’s Actual Employee Count Reveals That Its Valuation Doesn’t
Comparing valuation to headcount reveals very different capital efficiency stories among companies that share the same billion-dollar label.
The Founders Who Turned Down a Bigger Round on Purpose
A small but notable pattern: founders raising less than they could have, deliberately, to preserve control and optionality.
Accelerators Are Starting to Take Larger Equity Stakes for AI-Specific Cohorts
Some AI-focused accelerator programs now ask for meaningfully more equity than the traditional accelerator model, and founders are debating whether it’s worth it.
The Venture Capital Term Sheet Clause Founders Increasingly Push Back On
Founder-favorable market conditions in some categories have made a specific investor protection clause a more common negotiating flashpoint.
Why ‘Unicorn’ Stopped Being a Useful Word for Some Investors
As billion-dollar valuations have become more common in AI, some investors have quietly stopped treating the unicorn label as meaningful at all.
The Startup Funding Round Structure Designed to Avoid a Down Round Label
Some flat or declining-value raises get structured specifically to avoid the reputational hit of a publicly labeled down round.