- Tactical Tips by DECODE
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- 🚀 The bar for raising a 95th percentile seed round has gotten 3x higher
🚀 The bar for raising a 95th percentile seed round has gotten 3x higher
3 trends, 2 theses and 1 tool
Welcome back to ‘Tactical Tips’ by Jerel and Shuo at DECODE, the largest founder community co-hosted across Berkeley and Stanford.
We've updated our rhythm to bring you higher-signal content. We’ll be landing in your inbox twice a month, alternating between one of our founders’ top questions on how to build, sell and operate 10x better, and trends on what’s new and next in startups and tech to keep you ahead of the curve.
Today, we’ll be covering trends in startup valuations, thesis for AI usage, drivers of fund performance, and more.
And ... we’ve curated a YouTube playlist featuring our best founders, operators and investors.
🔥 Inside this issue:
✅ 3 trends in startups/tech/venture
✅ 2 theses on what’s next
✅ 1 tool to love
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3 trends in startups/tech/venture
📈 The bar for raising a 95th percentile seed round has gotten 3x higher
Carta analyzed the ~6,500 seed rounds raised by US startups between 2022 and 2026 and found that valuations have skyrocketed over the last 4 years:

Since investors only get their money back if the startups they invest in “exit” (IPO or sell) at a higher share price than what an investor invested at, more investors are understandably starting to question whether these seed valuation levels are healthy and sustainable.
🤖 Fewer people using more AI is becoming more expensive than more people using less AI
People used to think that AI could cut headcount and therefore costs. However, more companies are now coming to the opposite realization: they’re spending more money despite employing fewer people.
How? Because AI isn’t cheap to run. Fewer people using more AI is actually more expensive than more people using less AI.
Some people have been drawing the analogy that using old-school software is like going to see the movies, while using AI is like going to see live theatre. The latter may be a better experience, but costs a lot more.
💰 Market timing is the biggest driver of VC fund performance
Per the latest data from StepStone Group’s analysis of over 1,000 US VC funds over 23 vintage years, 80% of venture returns are driven by just 22–30% of vintages*. (*Vintage = the year in which a fund began, so a fund that made its first investment in 2026 is a 2026 vintage year fund.) In fact, over the 23 vintage years analyzed, 80% of returns came from just 5-7 vintage years and 95% of returns come from 6-10 vintage years.
The high-performing fund vintages? The ones that deployed capital after market corrections; not unlike public market investors who could “buy low” and then “sell high”.
This resurfaces the age-old debate: are the best investors truly talented … or were they just lucky (and, specifically, lucky in terms of when they started writing checks)? It’s nearly impossible to “time the market,” of course, so the only thing General Partners (AKA venture capitalists) and Limited Partners (AKA investors in venture funds) can do is invest consistently, even when market conditions are bad.
2 theses on what’s next
🤖 There will be a new bullet point in every job description
As people continue to outsource tasks and workflows to AI agents, there will be a new addendum at the end of everyone’s job titles: “agent manager”.
If you’re in sales, you will now also be a “sales agent manager.” If you’re a coder, you will now also be a “coding agent manager.” Even if you’re in a C-suite leadership role, you will now also expected to manage AI agents who are quietly doing a part of your job while you’re sleeping.
We just hosted KC, OpenAI’s Chief People Officer, for a Jeffersonian dinner, where we discussed this. More notes are coming soon!
🤔 The best startups build software that’s accountable
As NVIDIA CEO Jensen Huang previously said, the financial markets "got it wrong" about AI killing SaaS: So far, agents aren’t replacing software; they’re using it, and then letting humans step in as the “neck to choke” if things go wrong.
The next era of companies won’t just do work (or churn out AI slop); they’ll be accountable for the outcome.
1 tool we love
🎓 AI-powered financial modeling co-pilot
Filot takes financial modeling work that used to take humans hundreds of hours and does it in seconds. It even learns each firm’s unique style guide (more details here).
Filot is now serving some of the largest funds in the world, including Tiger Global, Ares and Two Sigma among others. They also just announced major partnerships with data platforms including TresVista (more details here).
Bonus: 1 toolkit to sell 10x better
GTM Atlas, by Attio
GTM Atlas is a free resource every operator should read. Curated by Attio, the AI CRM, and written by GTM leaders from Lovable, Granola, and Vercel, you'll get:
ICP, outbound, and retention frameworks from operators who've built them
The qualification signals that actually predict conversion
Conversion plays that don't rely on a pitch deck
Mapped by operators. Curated by Attio.
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