Co-authored by Matt Shapiro, VP of Investments and Tommy Vailas, Director of Partnerships
Final week we spent a couple of days within the Bay Space assembly with founders and associate companies and attending SaaStr Annual. We got here again energized, barely overwhelmed, and satisfied the tempo of change in software program is accelerating quicker 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 high 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 firms. That focus says rather a lot concerning the present dynamic. Mega-funds are keen to massively overpay to keep away from lacking the following category-defining platform, and FOMO has turn out to be a legit portfolio building technique on the high 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 properly. The concept that “all Bay Space funds suppose the identical” merely isn’t true.
2. East Coast vs. West Coast company-building remains to be wildly totally different
The mentality hole between coasts is as broad as ever. The West Coast runs on “go large or go residence” — success means a multi-billion greenback final result, typically $10B+, and something much less is a bust. That tradition, pushed by VCs taking part in the facility regulation, drives founders towards horizontal functions in huge, hyper-competitive markets. One investor we met flat-out mentioned he’d relatively 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 final result remains to be extensively celebrated as an actual win. Each fashions work — however they produce very totally different firms.
3. The “AI isn’t adequate 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 total firms round it.
Jason Lemkin made the purpose sharper in his opening keynote: cease constructing what you should buy. 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 complete GTM movement:
- 54% of latest enterprise logos in 2026 got here by means of 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 means of automated prep and workflow orchestration
- Claude is threaded by means of Salesforce, Gong, Gmail, Slack, Ironclad, Snowflake, and Intercom — none of which acquired retired
The larger perception wasn’t “AI replaces salespeople.” It was Dorfman’s framing that gross sales leaders are quickly changing into methods thinkers over deal strategists. The best-leverage GTM groups are constructing inside working methods the place AI acts as connective tissue throughout the stack, and the place the most effective reps’ patterns get encoded as Expertise so the ground rises throughout your complete 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), complicated enterprise offers nonetheless want people, no legacy instruments have been retired, and productiveness KPIs are nonetheless being discovered.
4. AI-native working leverage is changing into actual
Staff compression was a recurring facet dialog. The SaaStr staff 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. Satirically, a few of the most seen operational failures on the convention had been deeply human ones — lunch logistics being the working 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 firms.” It’s smaller, higher-output groups augmented by AI methods.
This additionally strengthened some extent we’ve been making internally: the true differentiator isn’t who buys AI — it’s the technical expertise that may truly deploy it. Agent upkeep is pricey and persistently underestimated.
5. GTM software program is coming into one other platform shift
The “AI CRM” narrative got here up in all places. At this time’s GTM stack — CRM, sequencing, enrichment, name intelligence, routing, help, forecasting, proposal technology, 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 file emerges, or whether or not incumbents like Salesforce keep dominant whereas AI layers sit on high. Proper now most firms are selecting augmentation over substitute. Anthropic itself doubled down on Salesforce relatively than changing it. That’s a sign value taking note of.
6. The tempo of firm creation is changing into absurd
We noticed repeated examples of firms 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 elements controversy and experimentation.
The Monaco staff, 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 inappropriate. The speed of experimentation, product iteration, and firm formation is in contrast to something the software program ecosystem has skilled earlier than.
What’s subsequent for vertical AI
The most important factor we left fascinated about: software program isn’t simply being digitized anymore — it’s being operationalized otherwise from the bottom up.
The winners over the following decade gained’t merely be the businesses with the most effective fashions. They’ll be those that encode organizational information 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 complete 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 quicker, leaner, and smarter inside extremely particular industries and workflows.
We’re nonetheless early.
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