teleo-codex/maps/analytical-toolkit.md

Analytical Toolkit — How Agents Reason

The shared reasoning framework all agents use when analyzing industries, companies, and proposals. Each tool is a concept (in foundations/ or core/) that agents combine when thinking through problems. This map teaches agents WHICH concepts to reach for and WHEN.

Important: This is internal reasoning infrastructure. When talking to contributors and experts, use natural language. Ask "where do you think healthcare is heading in 10 years?" not "what's the attractor state?" Ask "what makes this company hard to compete with?" not "evaluate the chain-link system." The framework shapes how agents think — not how they talk.

Industry Analysis

When analyzing any industry, work through these questions:

1. Where must this industry go? — Given what people actually need and what technology now makes possible, what does this industry look like in 10-20 years?

   • industries are need-satisfaction systems and the attractor state is the configuration that most efficiently satisfies underlying human needs given available technology
   • human needs are finite universal and stable across millennia making them the invariant constraints from which industry attractor states can be derived
   • first principles industry analysis reasons from human needs and physical constraints treating everything between inputs and need satisfaction as convention subject to disruption

2. How much pressure has built up? — Are incumbents extracting rents? Is available technology going unused? How fragile is the current structure?

   • what matters in industry transitions is the slope not the trigger because self-organized criticality means accumulated fragility determines the avalanche while the specific disruption event is irrelevant
   • proxy inertia is the most reliable predictor of incumbent failure because current profitability rationally discourages pursuit of viable futures
   • knowledge embodiment lag means technology is available decades before organizations learn to use it optimally creating a productivity paradox

3. Who's building the future and how? — What companies are disrupting, through what mechanism, on what timeline?

   • good management causes disruption because rational resource allocation systematically favors sustaining innovation over disruptive opportunities
   • disruptors redefine quality rather than competing on the incumbents definition of good
   • value in industry transitions accrues to bottleneck positions in the emerging architecture not to pioneers or to the largest incumbents
   • when profits disappear at one layer of a value chain they emerge at an adjacent layer through the conservation of attractive profits

4. What's driving the change and when does it hit? — Is this technology-driven, a knowledge reorganization, or regulatory? Each has different timing.

   • three attractor types -- technology-driven knowledge-reorganization and regulatory-catalyzed -- have different investability and timing profiles
   • pioneers prove concepts but fast followers with better capital allocation capture most long-term value in industry transitions
   • industry transitions produce speculative overshoot because correct identification of the attractor state attracts capital faster than the knowledge embodiment lag can absorb it

Company Analysis

When evaluating whether a specific company is building toward the future:

1. Is their advantage a system or a feature? — Can a competitor copy one piece, or do they need to replicate everything at once?

   • Devoteds competitive stack is a five-layer chain-link system where Orinoco Devoted Medical the health plan culture and the virtuous performance cycle must all be replicated simultaneously
   • Rumelt: chain-link systems get stuck at low-effectiveness equilibria but create durable advantage once all links improve

2. Where do they sit between physical and digital? — Pure software scales but commoditizes. Pure physical is defensible but linear. The sweet spot converts physical into digital.

   • the atoms-to-bits spectrum positions industries between defensible-but-linear and scalable-but-commoditizable with the sweet spot where physical data generation feeds software that scales independently

3. What keeps competitors out over time? — Moats erode unless actively deepened.

   • ownership alignment turns network effects from extractive to generative
   • competitive advantage must be actively deepened through isolating mechanisms because advantage that is not reinforced erodes

Mechanism Evaluation

When evaluating governance or coordination mechanisms:

1. Does it set rules or dictate outcomes? — Good mechanisms create the conditions for good decisions. Bad mechanisms try to engineer specific results.

   • designing coordination rules is categorically different from designing coordination outcomes as nine intellectual traditions independently confirm
   • Ostrom proved communities self-govern shared resources when eight design principles are met without requiring state control or privatization

2. What happens when someone tries to game it? — Every mechanism gets tested. The question is whether gaming attempts make the system stronger or weaker.

   • futarchy is manipulation-resistant because attack attempts create profitable opportunities for defenders
   • speculative markets aggregate information through incentive and selection effects not wisdom of crowds

3. Does it improve with more people or degrade? — Some systems get smarter as they grow. Others get noisier.

   • partial connectivity produces better collective intelligence than full connectivity on complex problems because it preserves diversity

Cross-Domain Synthesis

The highest-value reasoning happens when concepts from different domains connect:

• Critical systems (foundations/critical-systems/) — the physics of WHY transitions happen
• Cultural dynamics (foundations/cultural-dynamics/) — HOW ideas spread and coordinate action
• Teleological economics (foundations/teleological-economics/) — WHERE industries must go
• Collective intelligence (foundations/collective-intelligence/) — WHAT we're building and why it works

When multiple domains converge on the same conclusion, confidence increases. When they diverge, that's a tension worth investigating.