Top 10 in Tech - What to know for Week ending June 5, 2026

SaaS METRIC OF THE WEEK

All of it! ChartMogul has compiled its ("ultimate") SaaS Metrics Cheat Sheet.

SEED

Some more analysis on seed stage deals this week. Pavel Prata looked at the 10 biggest VC funds ($10B+ AUM) across three VC/Tech industry "periods": the pre-pandemic SaaS years (2015-19), the cheap-money boom (2020-22), and the AI era (2023-26). Collective early-stage deals went from 140-150/yr to 370-400/yr. a16z: 16.6 to 48.7 to 75.3 deals/yr. General Catalyst: 15.2 to 31.7 to 61.5. Both absolutely sending it!

ONBOARDING

Railway gets about 10,000+ signups a day! To manage this volume, they killed their generic welcome sequence and went event-triggered. Old open rate: 27%. New: 50-70% in the first 24 hours. The strongest signal: trust center document downloads (SOC 2 reports) - got them about a 50% reply rate when sales reaches out.

BURNER

Here's a cool concept for our tech dictionaries - work-streams that need heat! In the cold-start problem world of early-stage traction, we need the Venn diagram overlaps among build, distribution, and founder capacity. Founders normally sequence them, but the argument is that they should run in parallel. Distribution is the one left cold first - it can run weeks with nothing visible to show. By the time you need it, you've lost months of compounding momentum.

TOKENMANIA

The flipside of the agentic coding surge is the 2026 bill shocks. The WSJ reports Uber already burned through its entire 2026 AI budget (set in late 2025, before any of this actually worked). Amazon pulled an internal leaderboard that was driving too much usage. Salesforce went the other way, and 10x'd its budget. Uber's COO on a podcast: spend is high, specific gains hard to point to. Yeah, we all collectively coulda told you that. But apparently, 94% will keep spending on AI even when it fails.

AI DOCTORS

Exploding Topics surveyed 1,065 Americans on AI health use. 66% have tried AI for a health query. 25% report a "serious problem" after following AI health advice, another 20% report a minor problem. Among those who used AI for mental health or stress, 41.56% reported a serious problem. 82% feel "listened to" by AI vs 74% by human doctors.

AI SKEPTICS

Tomasz Tunguz maps out where the market is actually shorting AI. Median short interest across software, semis, data centers, and hyperscalers is up ~24% in the last quarter - because we all know that shit is expensive - as it's concentrated, these shorts are a bet against companies whose AI exposure still depends on future capital, future demand, or future operating leverage. AI cloud/neoclouds: 16.8% of float, which is up 60% in a year. Dev tools/infra software: 9.5%. Enterprise SaaS/AI apps: 8.9%. Hyperscalers: 1.1%. NVIDIA: 1.2%.

BACKPRESSURE

Another new entry for our Tech Dictionaries - it's a systems-engineering term for downstream refusing more work until the producer cleans their shit up. Lucas Costa argues it's the next frontier for AI-aided dev work. Right now, the human is the backpressure: reviewing, prompting, and copy-pasting feedback between the coding agent and the review bot. The fix is tests, types, benchmarks, review agents, and PR monitors that send bad patches back before they become a human's problem.

POSITIONING

Been through this a bit recently - April Dunford's rule for company/product positioning in the AI era: ignore future competition in your positioning, but NOT in your roadmap. Position against the competitors actually showing up on your prospects' short lists today, not the fast-moving threats you're convinced will arrive. But also build the product that can win the future match-up. Hype the vision for markets and investors. Sell against today's reality.

CASE STUDY

AMAZON - Bloomberg took a deep dive on Andy Jassy (CEO at Amazon): since ChatGPT, Microsoft, and Alphabet have collectively booked $600B more in future business than Amazon. Jassy's response: $50B committed to OpenAI, $13B+$20B option to Anthropic (with Claude now live), $200B AI infrastructure spend this year (they are becoming the Amazon of AI), $25B Mississippi data center cluster, 60,000 layoffs, dozens of projects killed.