Re. D / 04 · Owned IP
We rewrote our deal-qualification rules in five different vendor consoles. None of them are ours. Our “sales methodology” is now somebody else’s prompt template.
———————/ VP Revenue
B2B SaaS / €40M ARR
B2B SaaS / €40M ARR
Philosophy
The AI-native company needs an owned intelligence layer.
The old software paradigm put tools at the center and made people carry context between them. The new paradigm puts company intelligence at the center, then lets humans, agents, workflows, and tools orbit it.
02 · Diagnosis
Symptoms · n = 7 · observed in the field
D / 07 = forward-looking
Three years in. Why hasn’t AI compounded?
Six symptoms we hear from operators every week, plus one that’s about to land. The headline’s the same everywhere — spend is up, the org feels busier, none of it compounds. These are the load-bearing reasons why.
SymptomConditionSignal
D / 01
AI pilots that never reach production.
Every quarter ships a new prototype. Almost none of it ends up running the business. The half-life of “promising demo” is a board cycle, then it’s replaced by the next promising demo.
POC → PROD< 8% conversion
D / 02
Context that resets every Monday.
Each conversation starts from zero. The model knows your business about as well on day 400 as on day 1, because nothing about your operation is persisted in a place you control.
SYSTEM MEMORY0 days retained
D / 03
Tool sprawl masquerading as transformation.
Every vendor has shipped an AI feature. You’ve bought most of them. Your team now bounces between forty interfaces that each know one-fortieth of the company — and none of them know each other.
STACK SURFACE47 vendors / 1 strategy
D / 04
Vendor prompts own your business logic.
The actual decision rules — how your company qualifies a lead, scopes a deal, escalates a ticket — increasingly live inside a SaaS provider’s prompt template. You don’t see it. You don’t version it. You can’t leave with it.
OWNED IP0% of decision logic
D / 05
Agents you can’t safely give real access.
The interesting work needs write-access to real systems. Without governed scopes, audit, and approvals, every demo dies the moment legal asks what happens if it goes wrong. So agents stay read-only — and useless.
SCOPEread-only, indefinitely
D / 06
No telemetry. Only anecdotes.
Is it working? Nobody knows. There are no production evals, no drift detection, no per-decision audit. ROI is whatever the loudest stakeholder said at the last all-hands.
EVALS IN PROD0 / unmeasured
D / 07
Every team is about to ship its own agent.
Tool sprawl was the warm-up. The next twelve months will multiply it — every department running its own agents, with its own rules, memory, and decision logic. No shared schemas. No shared evals. The fragmentation you have today, replicated and accelerated — except this time the actors run themselves. The structure of your business gets reshaped by whoever shipped fastest, not by what should be true.
AGENT SPRAWL · INCOMING+1 per team / 0 governance
03 · From the field
Intake transcripts · n = 200+ operators
This isn’t theoretical. It’s what operators tell us, weekly.
We’ve shipped twelve copilots in eighteen months. None of them know each other exists. Every one of them learned our company from scratch — and then forgot.
————————/Head of Operations/Professional services/~120 FTE
Re. D / 05 · Scope
Every agent demo dies the moment legal asks what happens if it goes wrong. So our agents stay read-only, and nothing real ever ships.
————————/ CTO
Fintech / ~80 FTE
Fintech / ~80 FTE
Re. D / 06 · Evals
I can’t tell you if any of our AI initiatives are working. I can tell you what the last all-hands deck said. Those are different things.
———————/ COO
Legal tech / ~250 FTE
Legal tech / ~250 FTE
04 · The inversion
Lat. 40.7128 · Lon. −74.0060
For thirty years, tools were at the center. Now intelligence is.
The current model · "Humans around the edge"
SaaS tools at the center.
Your business logic is scattered across 50+ vendors. Humans copy state between them. Every tool is an island with its own permissions, schema, and politics.
Tools (logic)Humans (couriers)
The Spark model · "Intelligence at the center"
Company intelligence at the core. Tools as instruments.
Memory, goals, decision rules, and schemas live in one owned layer. Agents and workflows orbit it. Humans and tools sit on the outer ring — invoked, not central.
Intelligence (core)Agents / workflowsHumans / tools
06 · Doctrine
More tools.
Use fewer. Make them more agentic.
Why less
Every extra SaaS layer adds intermediation, hidden logic, maintenance burden, permission complexity, and context drift. Each is a place where your company's intelligence leaks out and decays.
Why agentic
The remaining tools should be instruments your intelligence layer can drive end-to-end. Fewer surfaces. More autonomy per surface. Total ownership of the decision logic that runs between them.
07 · Autonomy levels
From assistants → self-driving company systems
Spark builds at level 3 and 4.
Selected
The system runs the work. People review outcomes.
Workflows execute end-to-end against your operating layer. Approvals trigger only when policy says so. Eval suites catch drift in production. This is where Spark spends most of its time.
Spark focus area · L3 → L4
What changes
- — Decisions move from human to system
- — Approvals become exceptions
- — Evals replace manual QA
- — Tools become instruments
12 · Intake
Stop renting your company's intelligence.
Your business is already a codebase. Spark makes it explicit, executable, and owned. Start with the €5,000 Foundation Track — a fixed-scope diagnostic that ends with your Spark Map and a clear next step. With or without us.