The Scarcity Reset
Execution is now abundant. Intent is the bottleneck.
What Agents Actually Change
The conventional wisdom says AI will automate tasks. That's true, but it misses the deeper shift.
We're not moving from "humans do work" to "agents do work." We're moving from "who executes decides" to "who decides executes."
For most of economic history, the person who did the work held the power. The craftsman controlled quality. The analyst controlled insight. The strategist controlled direction. Execution and judgment were bundled in the same hands.
Agents unbundle them.
When an agent can draft the strategy document, build the financial model, generate the code, and coordinate the team—what remains for humans? Not the work. What remains is the decision about what should be done, and why.
Execution becomes abundant. Intent becomes the bottleneck.
Optimisation Is Not Strategy
Here's where most AI strategies stall: they treat agents as optimisation engines and forget that optimisation requires an objective function.
An agent can maximise revenue. It can minimise cost. It can optimise for customer satisfaction, employee retention, or market share. But which of these matters, and in what proportion, and at what trade-off—that's not optimisation. That's strategy.
- Optimisation: "How do we maximise X given constraints?"
- Strategy: "Why is X worth maximising? What are we willing to not maximise instead?"
Agents are extraordinary at the first question. They fail at the second. Not because they're insufficiently advanced, but because strategy requires something agents cannot possess: a stake in the outcome.
Where Truths Come In
A Truth is an explicit statement about what must hold. Not what might be nice—what must be true.
Example:
Truth: "Every invoice must correspond to delivered work."
An agent cannot generate an invoice without validating delivery. It can propose the invoice, but the system verifies the Truth before the invoice becomes actionable.
This isn't a constraint that slows agents down. It's what allows them to run faster—because now they know what's expected, and the system can verify they're meeting expectations.
Truths serve three functions:
- Direction: What success looks like.
- Guardrails: What cannot be compromised.
- Verification: How the system confirms correctness.
When Truths are explicit, agents execute with confidence. When Truths are vague, agents drift.
Guardrails Enable Speed
Guardrails get a bad rap. People imagine them as walls that keep agents from doing useful things.
They're the opposite: guardrails are what make autonomous execution possible.
A high-speed train doesn't move slower because of tracks. It moves faster because the tracks define where it can go.
Guardrails are the tracks for agents. They define the operational boundaries within which agents can operate at speed. That clarity is what allows the system to run without constant human supervision.
Effective guardrails are:
- Explicit: Written as rules, not assumptions.
- Enforceable: The system can verify compliance.
- Auditable: Every trigger creates a trace.
- Overridable: Humans can intervene when needed.
The Economics
When intent is clear:
- Agents execute toward defined outcomes
- Guardrails prevent drift
- Every execution improves the system
- Value compounds
When intent is vague:
- Agents optimise for proxies
- Drift accumulates silently
- Every execution may make things worse
- Value erodes
The difference isn't the agents. It's the intent.
This is why Converge exists. In a world where execution is abundant, the scarce resource is the clarity to know what to execute and why.
Make intent explicit. Stop agent drift.