Red-team thinking for robustness testing and edge case discovery. Use when you need to stress-test solutions, find vulnerabilities, anticipate failures, or challenge assumptions. Ideal for security review, system design validation, decision stress-testing, and pre-mortem analysis. Example: "We've designed an auth system" → Attack it from 10 angles before shipping.
Cross-domain reasoning for novel problems through structured analogy. Use when facing unprecedented problems where the best approach is finding similar solved problems in other domains. Unlike BoT (explores options), AT finds parallels. Example: "Design a new marketplace" → What can we learn from malls, stock exchanges, auctions, dating apps?
Rigorous A/B/C testing framework for empirically evaluating reasoning patterns. Use when you need data-driven pattern selection, want to quantify trade-offs between patterns, or need to validate claims about which cognitive methodology performs best. Enables scientific measurement of quality, cost, and time trade-offs across ToT, BoT, SRC, HE, AR, DR, AT, RTR, and NDF patterns.
Thesis-antithesis-synthesis reasoning for navigating genuine trade-offs and conflicting requirements. Use when opposing forces are both valid, binary choices are false, or stakeholder conflicts need resolution. Unlike ToT (picks winner), DR synthesizes opposites. Example: "Centralized vs decentralized architecture" → Neither is "right"; find synthesis that captures benefits of both.
Systematic elimination reasoning for diagnosis and debugging. Use when you need to identify THE cause among many possibilities through evidence-based elimination. Ideal for production incidents, bug diagnosis, root cause analysis, and differential diagnosis. Unlike BoT (which explores), HE eliminates. Example: "Server is slow" → Generate 10 hypotheses, design discriminating tests, eliminate 9, confirm 1.
Enhanced meta-orchestration for selecting and combining reasoning patterns. Now includes 9 methodologies (ToT, BoT, SRC, HE, AR, DR, AT, RTR, NDF) with weighted multi-dimensional selection, feedback loops, uncertainty propagation, and validated confidence aggregation. Use when facing complex problems requiring optimal reasoning strategy selection.
Multi-stakeholder coordination for decisions involving competing interests, different value systems, or organizational politics. Use when multiple parties must agree, when power dynamics affect decisions, or when consensus is required but perspectives diverge. Unlike DR (resolves conceptual tensions), NDF resolves stakeholder tensions.
Parallel execution patterns for cognitive reasoning tasks. Use when independent sub-problems can be solved simultaneously, multiple solution approaches need exploration, ensemble confidence is required, or time permits depth without sequential constraints. Integrates with ToT, BoT, HE, and AT for accelerated reasoning with fan-out/fan-in, MCTS-style search, and MoA aggregation patterns.