The New Consulting Paradigm
Founding engineers, not deck consultants.
The old consulting model: experts produce analysis and recommendations. Deliverables are documents. Implementation is a separate engagement (if it happens at all). Value is measured in insight quality.
This model sells the new with the old paradigm. It treats AI as another topic to analyze rather than a capability to deploy.
The Old Model
| Aspect | Traditional Consulting |
|---|---|
| Output | Decks, reports, recommendations |
| Relationship | Expert → client |
| Value metric | Insight quality |
| Implementation | "That's a separate engagement" |
| Knowledge transfer | Documents, presentations |
| Economic model | Time & materials |
| Success looks like | Client says "great analysis" |
The New Model
| Aspect | Capability Consulting |
|---|---|
| Output | Tools, infrastructure, encoded taste |
| Relationship | Founding engineer → co-builder |
| Value metric | Capability installed |
| Implementation | IS the engagement |
| Knowledge transfer | Working systems, methodology |
| Economic model | Outcome-aligned |
| Success looks like | Client doesn't need us anymore |
What "Founding Engineer" Means
We're more like temporary co-founders than consultants:
- We write code (or the AI equivalent)
- We make product decisions (not just recommend them)
- We're accountable to outcomes (not deliverables)
- We're temporary-permanent (long enough to matter, not forever)
This is different from T&M bodies. Different from strategy consulting. Closer to venture studio or EIR—but for capability, not company building.
Why the Shift Happened
AI changed the economics:
- Building is cheap → The constraint isn't "can we build" but "do we know what to build"
- Tools compound → Building our own tools makes us faster with each engagement
- Taste is the moat → Generic AI is commodity; configured AI is differentiation
- Implementation IS insight → You learn what works by building, not analyzing
The Self-Selection Filter
This model isn't for everyone. Customers either get it or they don't.
Good fit:
- Want to control their destiny
- See this as a moment to reinvent
- Willing to invest in capability infrastructure
- Value working systems over pretty documents
Not a fit:
- Focused on optimization and headcount
- Want to be told what to do
- Need extensive stakeholder buy-in for every decision
- Value comprehensive analysis over shipped capability
Both are valid. We're just not right for everyone.
The Recursive Proof
We practice what we preach. Our internal systems (swerk, this knowledge base, our playbooks) are the same patterns we deploy with customers.
If our tools can't help us help you, they're not good enough. The demonstration is the proof.
Implication
We're not competing with McKinsey. We're not competing with Accenture.
We're offering something different: embedded capability builders who use their own tools to help you build yours. Founding engineers who facilitate reinvention, then leave you with working infrastructure.
The question isn't "which consultancy has the best AI practice?" It's "who can help us build the factory that makes us differentiated?"