Routing as Extraction — or Enablement
Now it is messages with money (tokenized energy) and intent.
Twenty years ago a human ops team ran the routing algorithm. Bilateral agreements locked overnight. Traffic profile reviewed in a meeting. Blocklists updated by ticket. The Decision Trace lived in someone's inbox.
Now an agent reads the intent, picks the carrier, signs the value transfer, and writes the trace — in one message, in milliseconds, with no human in the loop. Crypto collapsed routing and settlement into one operation. AI agents collapsed the decider and the executor into one actor.
Telco networks and satellites carry every one of those messages. The substrate that moves voice today moves machine-to-machine value tomorrow — sensor readings paid per scan, compute cycles billed per job, position corrections settled per ping.
The stack this page sits under
— the value layer. What gets economized once machines have identity, payments, and a marketplace.
Intercognitive Protocol
— the protocol layer. How trillions of agents discover each other, negotiate, and settle. The invisible mycelium in the air.
— the maturity model. What it feels like when all three are running and nobody finds it strange.
The telco MEV problem stops being a telco problem and becomes the agent commerce protocol design problem. Same rules — clean reference data, bilateral lockouts first, quality thresholds as blocklists, decision traces as compound intelligence. Different actors. Higher stakes.
The video below is the human-speed version. The rest of this page is the playbook the agent fleet inherits — and the routing layer the stack above depends on.
What if we played positive-sum games and measured Maximal Enablement Value instead of Extraction from an interconnected ecosystem?
The Equilibrium
In the dream scenario the network runs at capacity without overflow. Every destination is priced so the ecosystem sustains — carriers earn enough to invest in quality, customers pay fairly for reliable service, and the routing intelligence compounds with every cycle.
Terminal State — The Target
01
First-choice selection
All traffic for each product type terminates with preferred carrier
02
Zero overflow
No routing to fallback paths — the plan holds under load
03
Quality above threshold
ASR and PDD within SLA bounds for every destination
04
Pricing sustains ecosystem
Maximum customer volume at margins that keep carriers investing
Your move — 5 minutes
Pick the hardest intent your agents route — the one where settlement and quality matter most. Write down what equilibrium looks like for it.
First-choice carrier, zero overflow, quality above threshold, sustainable margin — write each one as a sentence specific to your network (or your agent fleet's). That's move one. The machinery comes second. The picture comes first.
That is move one of the behaviour-equilibrium loop — picture the terminal state. Everything below reverses the requirements that make this state reachable: clean reference data (90% of the battle), routing logic that sequences bilateral commitments before open routes, quality thresholds enforced as blocklists, and decision traces that persist judgment beyond any single call.
The Question: What system generated this behaviour and outcomes, and how would it have to change so that the desired behaviour becomes inevitable?
Canonical exemplar of the behaviour-equilibrium loop pattern. Start with the perfect state of equilibrium. Then reverse-engineer the machinery and integrated know-how that make that state inevitable.
Introduction
As a customer you don't care who engineered the networking equipment that makes the calls possible, you just want to fulfil an intention to speak with someone at an acceptable range of quality and cost.
As the operator running the routing, you carry the inverse — you care about every layer, but only because the customer must not. Your job is to make the engineering disappear behind the intent.
The same routing algorithm can extract or enable. The difference is the north star — what the setpoint serves.
SAME ALGORITHM — DIFFERENT NORTH STAR
↘ Extraction
Optimize for self
Squeeze every basis point from carrier spreads. Win the quarter, lose the network.
↓Quality degrades — carriers cut costs to survive
↓Trust erodes — relationships become transactional
↓Network shrinks — the extractive loop collapses
↗ Enablement
Optimize for ecosystem
Invest in carrier quality, share reference data, honor thresholds that serve both sides.
↑Quality compounds — carriers compete on delivery
↑Trust builds — goodwill compounds over time
↑Network grows — the VVFL turns
A global telco uses its backbone network (Ethereum) to route inbound traffic to its intended destination by handing off (interoperability) to alternative carriers (Alts, L2s & L3s) they trust to deliver at competitive cost and quality of service. The question is whether "trust to deliver" means "cheapest route that clears" or "best route that strengthens the relationship."
A stable cost base is essential for implementing a pricing strategy that balances margins per route vs continued loyalty. But loyalty is the leading indicator. The telcos that squeezed every basis point from carrier spreads won the quarter and lost the network. The ones that invested in carrier quality — sharing reference data, honoring trade agreements, maintaining thresholds that served both sides — built the goodwill that compounded.
From Feeds to Routes
Getting access to siloed data and consistently processing it into clean, accurate data is 90% of the battle. Two input streams converge into one Source of Truth; one Source of Truth fans out to network, billing, and operations.
↓
Sanitize & Standardize Data
Source of Truth
Ranking Algorithm
↻ runs multiple iterations to balance demand against capacity
Formatted Routing Plans → Gateway Switches
↓
Reference Data
Data Integrity is fundamental to making accurate data-driven decisions.
Wholesale vs Retail Strategy
Quality of Service SLAs
Network Bandwidth Capacity
Customer Records
Bilateral Trade Deals
Time of Day
Regulations
Network Data
Inter-carrier Destination Costs
Call Records
Aggregated Network Traffic
International Cost Base
Inter-carrier Destination Pricing
Arbitrage in Practice — The French Mobile Story
During the early 2000s many telco operators had not updated their systems to monitor or create routing decisions for international calls to mobile phones because this required collaboration and co-ordination across many departments and systems that had weak interfaces for transforming and exchanging critical data.
Adding to the complexity, a definitive standard for a world number plan does not exist. To operate effectively each of the following systems must share common reference data taken from a single source of truth: Switches, Mediation, Pricing, Billing.
Arbitrage opportunities arise against a telco when its reference data is outdated or not aligned across business critical systems. As an example: French mobile numbers begin +336 or +337 but in the early 2000s many international carriers had not updated their routing tables to reflect this. Therefore operators based in France could route national mobile terminating calls over their international backbone to another country and pass on to a carrier still charging fixed-line rates — exploiting the reference data gap.
Performance Metrics
Use traffic profiling and growth projections to plan where to invest in infrastructure.
Traffic Profiling
Capacity Planning
Quality of Service
Trade Deals
How the Routing Runs
The equilibrium named at the top of this page is the destination. The rules below are the path the algorithm takes to get there. Each iteration of the routing logic moves the network closer to the picture — first-choice selection, no overflow, quality above threshold, pricing that sustains the ecosystem.
Rules
Sequence of logic to deliver routing plans that optimise enablement value — network quality, carrier sustainability, and customer experience — against available capacity.
Minimize overflow from first-choice selection
Use supplier's most valuable routes first, then exclude
Backbone routing by customer type
No circular looping
Blocked destination suppliers excluded
Bilateral trade agreements locked first
Dial code destination matching
Dial code cost blending
Routing Logic
P1
Projected minutes by routing case code per hour — growth trend, historical trend, global events, pricing effects, time of day
P2
Load blended rate profile for each routing case by mapping offering price, code overlap for each time of day
Phase 2 — Iterative Routing Loop
→ If a provider reaches safe outbound capacity: remove from options, add to ignore list, advance next option
Pricing for Network Strength
Automate routing case decisions to fulfil intentions and enable maximal value across a network of solution providers.
Goal: price so the network strengthens — demand balanced with capability to deliver at sustainable margins.
Predict cost base with a factor of safety to account for traffic overflow. Establish the extremes of what the market will pay by analysing carrier price sheets. Review objectives of each provider relationship in the big picture, their relative demand for minutes to destination.
Same Pattern, Three Domains
Telecom routing and crypto intents follow the same architecture.
INTENT → ROUTE → INFRASTRUCTURE → SETTLE → FEEDBACK
Telecom
What moves:
Voice / Data
Who routes:
Carrier switches
Who settles:
CDR billing
MEV: Routing algorithm that lifts carrier quality
Crypto
What moves:
Value
Who routes:
Solvers / Bridges
Who settles:
Blockchain
MEV: Solver with best execution for the user
DePIN
What moves:
Both
Who routes:
Edge AI
Who settles:
Oracles + Chain
MEV: Routing intelligence shared across the network
The pattern: User expresses intent. System finds optimal path. The routing intelligence either extracts from the network or enables it. The north star determines which. When standards rise, every participant's capacity to deliver rises with them — a rising tide lifts all boats.
Telco Bridges to Crypto
A crypto wallet is just like a phone — you don't care about the network, you just want your intentions fulfilled at acceptable cost and quality.
Telecom Term
Crypto Equivalent
Routing Case
Intent specification
Carrier selection
Solver competition
Quality of Service
Slippage tolerance
CDR settlement
On-chain settlement
Reference data
Price oracles
Why this matters for DePIN: When devices become economic actors, they emit intents (data, compute, bandwidth) that need routing. The telecom MEV playbook — reference data integrity, capacity planning, quality thresholds — becomes the DePIN protocol design.
See Crypto MEV for the blockchain-native expression of this pattern.
Decision Traces
The routing algorithm was a decision-making system. The most valuable output wasn't the routes — it was the traces showing WHY routes were chosen. Every exception, override, and precedent encoded judgment that no rule book captured. When a carrier got blocklisted for a destination, the trace recorded the QoS failure, the threshold breached, the alternative selected. That trace became queryable precedent for the next routing decision.
A problem solved is a problem forgotten. Telcos that fixed a routing arbitrage and moved on got exploited again when reference data drifted. The ones that persisted the decision trace — context, options considered, outcome measured — built compound intelligence. Rules tell you what SHOULD happen. Decision traces capture what DID happen and WHY. That gap is where enterprises bleed margin.
This is the context graph thesis applied to infrastructure. Link decision traces to each other and you get a graph that scales judgment without scaling headcount. Wayne Smith coaches this in rugby — review HOW the decision was made, not IF it was right. Todd Simkin runs the same loop in trading: prior → action → actual → update prior. The decision journal is the instrument.
Your move — 10 minutes — capture your first trace
Pick last week's hardest routing decision — yours, or one your agents made on your behalf. The one that took a meeting, an override, or a gut call.
Write three sentences: the context loaded, the options considered, the outcome you measured.
Link forward: name the next decision that will reference this one. That link turns three sentences into a graph node.
Three sentences plus a link — that's a Decision Trace. Repeat ten times and you have a queryable precedent graph. The pattern recurs wherever pipelines rot: "deals with no activity for fourteen days," "tickets with no update for seven days," "carriers below threshold for three cycles," "agent intents with no settlement trace for N blocks." Same blocklist logic, different domain, different speed. Telco routing solved this twenty years ago — agent commerce is solving it again at machine speed.
Context
- Culture — The north star is set by culture, not by the algorithm
- Identity — Without anchored identity, the algorithm optimizes for whoever sets the setpoint
- From Hierarchy to Intelligence — When routing is automated, culture is the human's job at the edge
- Navigation System — The abstract pattern: Value (reference data), Belief (routing logic), Control (capacity planning)
- The North Star — Reference data is the north star of routing — when it drifts, arbitrage exploits you
- VVFL — Enablement is what makes the feedback loop virtuous instead of extractive
- Goodwill — The carrier relationships that compound when routing serves the network
- Standards — A rising tide: when standards improve, every participant's capacity rises
- Positive-Sum Games — Rules that reward contribution, not capture
- Essential Algorithm — The meta-pattern: every business IS its routing algorithm
- Routing Algorithm — The universal pattern: same optimization from person to marketplace
- Routes — Fork/Obstacle/Sign/Bridge: carrier selection is Fork, QoS threshold is Sign, decision trace is Bridge
- Manufacturing Routing — Same routing problem at a different layer: work centers instead of carriers, throughput instead of ASR
- Information Arbitrage — The principle (SSOT)
- Crypto MEV — Blockchain expression
- Telecom Data Model — Entity relationships
- Intent and Interop — Crypto intents
- DePIN Tech — Infrastructure layer
- Economy of Things — The value layer that runs on this routing substrate — machine identity, payments, marketplace, time
- Intercognitive Protocol — The protocol layer for physical AI; the invisible mycelium in the air that the substrate carries
- Phygital Mycelium — The maturity model — what it feels like when the routing layer, protocol layer, and value layer all run and nobody finds it strange
Links
- Blockchain Intents
- Telco Trade Deals
- Route Optimisation
- Call Routing Optimisation
- Massive Profits are Hidden in Your Data
Run This Against Your Own Routing
Copy. Paste into an AI assistant with access to your systems. Read the answer with a routing engineer in the room.
Human-speed audit — your routing pipeline
Audit my routing pipeline against the telco MEV pattern.
For each system that touches reference data (switches, mediation,
pricing, billing — or your equivalent), tell me:
1. Does it read from one shared Source of Truth, or its own copy?
2. When the source drifts, what is the first signal — and who sees it?
3. List every destination/route/SKU where the quality threshold is
enforced as a blocklist, not just a warning.
4. For each blocked entry, is there a Decision Trace recording the
threshold breached and the alternative selected — or just a flag?
Highlight the gaps. The gaps are arbitrage exposure. Rank them by
the cost of being wrong for one quarter.
Machine-speed audit — your agent fleet
Audit how my agent fleet routes value against the telco MEV pattern.
For each intent type the agents route (payments, data, compute,
positioning, content delivery), tell me:
1. Do all agents read from one shared Source of Truth for prices,
carrier quality, and reachability — or each agent its own cache?
2. Does the agent sign a Decision Trace with every value transfer
(context loaded, options considered, threshold checked, outcome)
— or just settle the transaction?
3. Which intents have a quality threshold enforced as a hard
blocklist that an agent cannot override on its own?
4. When carrier quality drops mid-flight, what is the agent's
fallback — and is the fallback decision itself traced?
Highlight the gaps. At machine speed, an untraced gap costs a
thousand decisions before a human sees it.
Questions
What if the most valuable output of a routing algorithm is not the margin it captures but the network quality it enables?
- When reference data drifts out of sync across switches, billing, and pricing, what's the first signal that arbitrage is being exploited against you — and does your decision trace catch it?
- The extraction-vs-enablement diagram has the same algorithm, different north star. What changes in the routing logic itself when you optimize for ecosystem quality instead of margin per route?
- If 90% of the battle is clean data, what would it mean to share that clean data with your carriers instead of hoarding it as competitive advantage?
- The Three Flows maps telecom to crypto to DePIN — at which layer does the enablement thesis break down, and what does the gap reveal about where extraction still wins?