Seven principles.
One philosophy.
Most AI projects fail because nobody stopped to ask the right questions. These principles guide everything we build.
Human First, Machine Second
AI should elevate your team, not replace them.
What this means for you
Your people are the product. We build AI that handles the repetitive research, sorting, and formatting so your team can focus on relationships, strategy, and decisions that actually move the business. The human always stays in control.
Proof point
CloneICP finds prospects and scores them 0-100%, but the sales rep decides who to contact and how. The AI does the research; the human owns the relationship.
Agent-Native Architecture
Built so AI agents can do anything humans can.
What this means for you
Most software is built for humans clicking buttons. We build systems that are equally accessible to AI agents: structured inputs, structured outputs, observable behavior. When AI gets smarter, your systems scale automatically.
Proof point
SnowThere: adding a new country does not require new code. It requires a new prompt configuration. The agent pipeline handles any geography.
Discovery Before Deployment
We understand the problem before we touch technology.
What this means for you
70% of AI projects never make it past pilot (RAND Corporation, 2024). The primary reason is not technical failure; it is solving the wrong problem. We invest in understanding your actual workflows before writing a single line of code.
Proof point
SnowThere: Jobs-to-be-Done mapping revealed that quality and trust, not volume, was the real bottleneck. That insight shaped the entire three-agent editorial panel architecture.
Probabilistic Where Possible, Deterministic Where Necessary
Flexible systems for judgment. Rigid systems for safety.
What this means for you
AI is inherently probabilistic: it makes good guesses, not guaranteed answers. We use that flexibility for creative work and judgment calls, but enforce strict deterministic rules for safety, billing, and compliance. You get the best of both worlds.
Proof point
CloneICP: probabilistic semantic search finds fuzzy matches across the web. Deterministic 0-100 scoring with explicit reasoning makes every result comparable and auditable.
Atomic Primitives
Small composable building blocks, not monolithic software.
What this means for you
Monolithic AI systems break when you change one thing. Our systems are built from small, independent operations that snap together like building blocks. This means faster iteration, easier debugging, and the ability to improve one piece without risking the rest.
Proof point
26 atomic primitives power both the Automation Blueprint generator and the content pipeline. Same building blocks, entirely different products.
Designed for Discovery
Your work should be findable by both humans and machines.
What this means for you
We structure everything so your brand gets discovered and cited by AI assistants, search engines, and potential customers alike.
Meaning Engine Optimization
Optimize for meaning, not just keywords.
What this means for you
As AI-powered search replaces traditional search, the companies that invest in clarity, depth, and structured meaning win visibility. We build that into everything.
“AI should work the way humans think, not the way software has always worked.”
Tom Meredith, Co-Founder
See these principles in action.
Every engagement starts with a conversation about your workflows, not a sales pitch.
Book a ConversationOr try a free Automation Blueprint to see how we think.