Two days.
One conversation.
A single-track program for founders, investors and infrastructure leaders building the AI-native services economy.
Found
How to identify the right market, workflow, wedge and business model for an AI-native services company.
Build
The infrastructure, architecture and technical systems required to deliver work through AI.
Scale
How AI-native service companies turn delivery into a repeatable, high-margin operating system.
Fund
How investors evaluate, fund and value a new class of outcome companies.
Building the
outcome company
Define →Build →Prove →Price
Scaling the
outcome economy
Operate →Defend →Fund →Scale
Founder / Investor dinner
The summit opens the night before. A seated dinner pairing AI-native founders with the investors underwriting the category — the unique networking item that kicks off the two days that follow.
Building the outcome company
Day One establishes the category and gets inside the mechanics of building a company where AI increasingly delivers the outcome.
Coffee, partner discovery and founder/investor networking.
The future of software is outcomes
Why the next shift in AI may not be better software, but companies that sell completed work instead of tools.
Don't build an AI wrapper. Own the workflow.
How founders choose a workflow worth owning, build domain credibility and avoid becoming another thin layer on top of foundation models.
The domain expert is the cofounder
Why the strongest AINS companies pair deep industry knowledge with applied AI capability.
Partner discovery and networking.
The AI-native stack
What must be rebuilt when intelligence becomes part of the core operating architecture.
When AI becomes the runtime
What happens when intelligence moves from a feature into the core decision-making and workflow layer.
The last human mile
Where should humans remain in the loop — and where should they disappear?
Lunch and curated discovery.
Mirage PMF: are you an AI company — or a services firm with better software?
How to distinguish real AI leverage from revenue growth still dependent on human labor.
The metric that matters: how much of the work is AI actually doing?
What founders, operators and investors should measure beyond ARR.
The death of the seat
How do you price when software does the work?
What would you build if labor were no longer the constraint?
Founders and investors explore which service industries become possible when software can own substantially more of the work.
Networking and partner discovery.
Scaling the
outcome economy
Day Two moves from formation to scale — how AI-native service companies operate, improve, defend, finance and expand.
When the workflow becomes the company
Why delivery is no longer a support function — it becomes the product and operating system.
The living system
How to build AI-native systems that improve with every completed job.
Evals are the new QA
How do you trust a system whose output is not deterministic?
Who owns the context layer?
The battle for memory, data, orchestration and real-time intelligence inside the outcome stack.
Every job should make the next job better
How completed work becomes proprietary data, better models, stronger workflows and a compounding advantage.
What makes an AINS company venture-backable?
Revenue is not enough. What investors need to see in AI leverage, margins, productization and defensibility.
Software margins. Services markets. What is an AINS company worth?
Can AINS achieve software-like margins — and should it receive software-like multiples?
Build it or buy the humans?
When does acquiring a legacy services business accelerate an AI-native company — and when does it quietly destroy the model?
Which $100B service market falls first?
Founders and investors make the case for the industries most likely to be rebuilt around AI-native service delivery.
From tools to outcomes
A concise closing statement defining the next generation of AI-native service companies.