Co-authored by Matt Shapiro, VP of Investments and Tommy Vailas, Director of Partnerships
Final week we spent just a few days within the Bay Space assembly with founders and companion corporations and attending SaaStr Annual. We got here again energized, barely overwhelmed, and satisfied the tempo of change in software program is accelerating sooner than most individuals respect.
From a York IE lens, six themes stood out.
1. The Bay Space AI market is concurrently rational and irrational
The favored narrative outdoors Silicon Valley is that everybody within the Bay is blindly throwing cash at AI. That’s directionally true on the very prime of the market, however incomplete.
One stat got here up repeatedly: roughly 59% of all VC {dollars} deployed within the final 12 months went into simply three corporations. That focus says quite a bit concerning the present dynamic. Mega-funds are prepared to massively overpay to keep away from lacking the following category-defining platform, and FOMO has grow to be a reputable portfolio development technique on the prime of the market.
Beneath that, although, there was much more skepticism than folks assume. The buyers we met had been deeply analytical about distribution, sturdiness, gross margins, infrastructure prices, and whether or not merchandise had been fixing actual workflow ache versus simply demoing effectively. The concept that “all Bay Space funds assume the identical” merely isn’t true.
2. East Coast vs. West Coast company-building continues to be wildly totally different
The mentality hole between coasts is as large as ever. The West Coast runs on “go massive or go house” — success means a multi-billion greenback consequence, typically $10B+, and something much less is a bust. That tradition, pushed by VCs enjoying the ability legislation, drives founders towards horizontal purposes in huge, hyper-competitive markets. One investor we met flat-out mentioned he’d reasonably take a zero than a $200M exit.
The East Coast stays extra pragmatic. Extra founders constructing vertical options, deliberately elevating much less capital, and a $200–500M consequence continues to be broadly celebrated as an actual win. Each fashions work — however they produce very totally different corporations.
3. The “AI isn’t ok but” crowd goes to get left behind
This was the clearest takeaway of the journey.
There’s nonetheless a big cohort of operators and buyers dismissing AI as a result of it hallucinates, misses nuance, or can’t totally automate a workflow end-to-end. In the meantime, operators on the bottom are already redesigning whole corporations round it.
Jason Lemkin made the purpose sharper in his opening keynote: cease constructing what you should purchase. Within the AI period, the winners gained’t be the groups that construct probably the most — they’ll be the groups that deploy the quickest and extract probably the most worth from the instruments they undertake.
The perfect illustration of this got here from Eleanor Dorfman’s session on how Anthropic rebuilt its personal income org. The headline wasn’t that Anthropic makes use of Claude internally — it’s how deeply embedded it already is throughout your entire GTM movement:
- 54% of latest enterprise logos in 2026 got here by a self-serve enterprise movement
- First-draft proposal turnaround dropped from 45 minutes to 4 minutes
- AEs gained again 10–15 hours per week by automated prep and workflow orchestration
- Claude is threaded by Salesforce, Gong, Gmail, Slack, Ironclad, Snowflake, and Intercom — none of which obtained retired
The larger perception wasn’t “AI replaces salespeople.” It was Dorfman’s framing that gross sales leaders are quickly changing into techniques thinkers over deal strategists. The very best-leverage GTM groups are constructing inside working techniques the place AI acts as connective tissue throughout the stack, and the place the very best reps’ patterns get encoded as Expertise so the ground rises throughout your entire org.
Equally refreshing was Anthropic’s honesty about what AI hasn’t solved: forecasting accuracy nonetheless struggles (Dorfman mentioned her personal quantity was off 40% final week), advanced enterprise offers nonetheless want people, no legacy instruments have been retired, and productiveness KPIs are nonetheless being found out.
4. AI-native working leverage is changing into actual
Workforce compression was a recurring aspect dialog. The SaaStr crew itself mentioned compressing parts of occasion operations from ~23 FTE-equivalents right down to nearer to three utilizing AI brokers and automation.
However they had been equally adamant concerning the human layer. Paradoxically, a number of the most seen operational failures on the convention had been deeply human ones — lunch logistics being the operating joke. That duality issues. AI is driving actual leverage, however people nonetheless personal belief, coordination, relationships, and edge-case judgment. The long run isn’t “AI-only corporations.” It’s smaller, higher-output groups augmented by AI techniques.
This additionally strengthened a degree we’ve been making internally: the actual differentiator isn’t who buys AI — it’s the technical expertise that may really deploy it. Agent upkeep is dear and persistently underestimated.
5. GTM software program is coming into one other platform shift
The “AI CRM” narrative got here up all over the place. At present’s GTM stack — CRM, sequencing, enrichment, name intelligence, routing, help, forecasting, proposal era, enablement — is brutally fragmented, and everybody agrees the workflow is damaged.
What’s much less clear is whether or not a brand new AI-native system of document emerges, or whether or not incumbents like Salesforce keep dominant whereas AI layers sit on prime. Proper now most corporations are selecting augmentation over substitute. Anthropic itself doubled down on Salesforce reasonably than changing it. That’s a sign price listening to.
6. The tempo of firm creation is changing into absurd
We noticed repeated examples of corporations hitting scale at speeds we’ve by no means seen earlier than. The one which caught with us was Higgsfield AI — an organization most individuals nonetheless haven’t heard of — reportedly at ~$300M ARR in roughly 10 months. The founder was candid that the expansion journey was equal components controversy and experimentation.
The Monaco crew, recent off a Sequence B from Benchmark, was flying banner planes round San Mateo for “solely” $15K. Whether or not each story like this proves sturdy is irrelevant. The rate of experimentation, product iteration, and firm formation is not like something the software program ecosystem has skilled earlier than.
What’s subsequent for vertical AI
The most important factor we left fascinated by: software program isn’t simply being digitized anymore — it’s being operationalized in a different way from the bottom up.
The winners over the following decade gained’t merely be the businesses with the very best fashions. They’ll be those that encode organizational data quickest, construct distribution benefits earliest, combine AI deeply into workflows, keep operational fundamentals whereas shifting rapidly, and use AI to lift the ground throughout your entire group.
At York IE, the journey strengthened why we stay enthusiastic about vertical AI and workflow-specific software program. The chance isn’t in basis fashions — it’s in serving to actual companies function sooner, leaner, and smarter inside extremely particular industries and workflows.
We’re nonetheless early.
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