Integrated Reasoning v2 - Meta-Orchestration

Purpose: Select and orchestrate optimal reasoning pattern(s) for your problem. V2 addresses limitations of v1: adds new patterns, replaces order-dependent decision tree with weighted scoring, includes feedback loops, and fixes confidence aggregation.

Available Reasoning Patterns (9)

Pattern Purpose Best For

Tree of Thoughts (ToT) Find optimal solution through deep exploration Optimization, clear criteria, find THE best

Breadth of Thought (BoT) Map solution space comprehensively Unknown space, need multiple options

Self-Reflecting Chain (SRC) Sequential reasoning with validation Dependent steps, proofs, linear traces

Hypothesis-Elimination (HE) Systematic elimination through evidence Diagnosis, debugging, root cause

Adversarial Reasoning (AR) Stress-test through attack simulation Validation, security, pre-mortems

Dialectical Reasoning (DR) Synthesize opposing valid perspectives Trade-offs, conceptual conflicts

Analogical Transfer (AT) Solve via cross-domain parallels Novel problems, no direct precedent

Rapid Triage Reasoning (RTR) Fast decisions under time pressure Incidents, emergencies, time-boxed choices

Negotiated Decision Framework (NDF) Multi-stakeholder coordination Politics, competing interests, buy-in needed

Pattern Selection: Weighted Multi-Dimensional Scoring

Step 1: Assess Problem Characteristics

Score each dimension (1-5):

Step 1.5: Time Pressure Fast-Path

CRITICAL: If Time Pressure = 5 (emergency/incident):

• Skip full scoring

• Use Rapid Triage Reasoning (RTR) directly

• RTR is optimized for decisions under extreme time constraints

If Time Pressure ≥ 4:

• Consider RTR unless problem is clearly sequential (use SRC) or diagnostic (use HE)

• Apply abbreviated scoring (skip orchestration considerations)

Step 2: Calculate Pattern Affinity Scores

ToT = (Criteria × 0.35) + (SingleAnswer × 0.30) + (SpaceKnown × 0.20) + ((6-Novelty) × 0.15)

BoT = ((6-SpaceKnown) × 0.35) + ((6-SingleAnswer) × 0.30) + ((6-Criteria) × 0.20) + (Novelty × 0.15)

SRC = (Sequential × 0.45) + (Criteria × 0.25) + (SingleAnswer × 0.20) + ((6-OpposingViews) × 0.10)

HE = (Evidence × 0.40) + (SingleAnswer × 0.30) + ((6-Novelty) × 0.20) + ((6-OpposingViews) × 0.10)

AR = (Robustness × 0.40) + (SolutionExists × 0.30) + ((6-Novelty) × 0.15) + (Evidence × 0.15) # NOTE: AR requires SolutionExists ≥ 3, otherwise score = 0

DR = (OpposingViews × 0.50) + (Criteria × 0.20) + ((6-Evidence) × 0.15) + (MIN(SingleAnswer, OpposingViews) × 0.15) # NOTE: V2.1 fix - SingleAnswer no longer penalized when OpposingViews is high

AT = (Novelty × 0.45) + ((6-SpaceKnown) × 0.30) + ((6-Evidence) × 0.15) + ((6-Sequential) × 0.10)

RTR = (TimePressure × 0.50) + (SingleAnswer × 0.25) + (Evidence × 0.15) + ((6-Novelty) × 0.10) # NOTE: RTR auto-selected when TimePressure = 5

NDF = (StakeholderComplexity × 0.45) + (OpposingViews × 0.25) + ((6-Criteria) × 0.15) + ((6-TimePressure) × 0.15) # NOTE: NDF requires StakeholderComplexity ≥ 3 to be considered

Formula Validation Rules (V2.1):

• AR returns 0 if SolutionExists < 3 (nothing to attack)

• RTR auto-triggers when TimePressure = 5 (emergency mode)

• NDF returns 0 if StakeholderComplexity < 3 (single decision-maker)

• If multiple patterns score within 0.3 of each other, use uncertainty propagation (Step 2.5)

Step 2.5: Uncertainty Propagation (V2.1)

When dimension scores are uncertain, propagate uncertainty to pattern selection:

Uncertainty Assessment

For each dimension where you're unsure (±1 point uncertainty):

1. Calculate pattern scores at LOW end (dimension - 1)
2. Calculate pattern scores at HIGH end (dimension + 1)
3. If different pattern wins at each end → Flag as uncertain selection

Handling Uncertain Selections

If same pattern wins both ends: Proceed with confidence If different patterns win:

• Run BOTH patterns in parallel (if time permits)
• OR use the pattern that's more robust to being wrong
• OR gather more information to reduce dimension uncertainty

Uncertainty Discount

Apply -5% to final confidence for each uncertain dimension that affects the winning pattern.

Step 3: Interpret Scores

Scenario Action

One pattern scores >4.0 Use that pattern directly

Top 2 within 0.5 of each other Consider multi-pattern orchestration

Top 3 within 0.3 of each other Apply uncertainty propagation first

All patterns <3.0 Problem may need decomposition first

Top pattern <2.5 None fit well; use Direct Analysis

Direct Analysis (10th Pattern)

When all pattern scores are below 2.5, no specialized methodology is warranted:

Direct Analysis

When to use: All patterns score <2.5 (problem doesn't match any pattern's strengths)

Approach:

1. No special framework needed
2. Just think through the problem directly, step by step
3. Use common sense and straightforward reasoning
4. Appropriate for simple problems that don't need cognitive overhead

Examples:

• Simple factual questions
• Straightforward calculations
• Basic lookups or translations
• Problems with obvious solutions

Confidence: Use intuitive confidence based on problem clarity

• Clear problem + clear answer = high confidence
• Any ambiguity = document it explicitly

Direct Analysis Threshold

Use Direct Analysis (no specialized pattern) when:

• MAX(all pattern scores) < 4.0 AND

• No dimension scored >= 4 AND

• Problem is not time-critical (TimePressure < 4)

Direct Analysis = simple step-by-step reasoning without framework overhead.

Sequential vs Parallel Execution Decision

Use SEQUENTIAL when:

• Pattern B depends on Pattern A's output (e.g., BoT finds options → ToT optimizes)

• Confidence from A affects what to do in B

• Evidence from A eliminates need for B

• One pattern discovers the problem is different than expected

Use PARALLEL when:

• Patterns explore independent dimensions

• No dependency between pattern outputs

• Need ensemble confidence (run same problem through 2 patterns)

• Time allows and you want cross-validation

• Patterns are complementary (e.g., different perspectives on same problem)

Common Chains (Sequential):

BoT → ToT → AR (explore → optimize → validate) HE → SRC → AR (diagnose → trace → validate fix) AT → DR → ToT (analogize → synthesize → optimize) RTR → HE → ToT (triage → root cause → proper fix) NDF → ToT → AR (align stakeholders → optimize → validate) DR → NDF → ToT (resolve concepts → negotiate politics → optimize) AT → BoT → ToT (find analogies → explore adaptations → select best)

Common Parallel Combinations:

BoT || AT (parallel exploration from different angles) ToT || DR (optimize while synthesizing trade-offs) HE branches (test multiple hypotheses simultaneously) AR attack vectors (stress-test from multiple directions at once)

Full Reasoning Chain: Input → Output

Complete end-to-end flow for IR-v2 orchestration:

1. Problem Input └─→ Receive problem statement, constraints, and context

2. Score 11 Dimensions └─→ Sequential Dependencies, Criteria Clarity, Solution Space Known, Single Answer Needed, Evidence Available, Opposing Valid Views, Problem Novelty, Robustness Required, Solution Exists, Time Pressure, Stakeholder Complexity

3. Fast-Path Check └─→ TimePressure = 5? → RTR immediately (skip remaining steps)

4. Pattern Selection └─→ IR-v2 calculates affinity scores for all 9 patterns └─→ Apply validation rules (AR needs solution, NDF needs stakeholders)

5. Direct Analysis Check └─→ All patterns < 2.5? → Use Direct Analysis (no framework)

6. Orchestration Decision └─→ Single pattern > 4.0? → Use that pattern directly └─→ Top 2 within 0.5? → Consider multi-pattern orchestration └─→ Top 3 within 0.3? → Apply uncertainty propagation first └─→ Decide: Sequential or Parallel execution?

7. Pattern Execution └─→ Apply selected pattern(s) using their methodologies └─→ Track confidence and key findings

8. Checkpoint (15 min) └─→ Progress check, pattern fit check, new information check └─→ Re-evaluate and potentially switch patterns if needed

9. Handover (if multi-pattern) └─→ Transfer context via .reasoning/ directory └─→ Preserve insights from completed pattern └─→ Set up next pattern with full context

10. Synthesis (if multi-pattern) └─→ Combine findings from all patterns └─→ Resolve conflicts, identify agreements

11. Confidence Aggregation └─→ Single pattern: use internal confidence └─→ Multi-pattern: apply agreement analysis └─→ Apply uncertainty discounts if applicable

12. Output └─→ Deliver answer with reasoning trail └─→ Document confidence level and key uncertainties └─→ Provide actionable recommendations

Multi-Pattern Orchestration

When to Orchestrate

• Top 2 patterns within 0.5 points AND

• Problem is high-stakes (consequences matter) AND

• Time budget allows (>45 minutes available)

Orchestration Patterns

Sequential Orchestration (most common):

• Use exploration pattern first (BoT, AT)

• Use optimization pattern second (ToT, HE)

• Use validation pattern last (AR, SRC)

Parallel Orchestration (when patterns are complementary):

• Run 2 patterns independently

• Compare conclusions

• Use agreement/disagreement to calibrate confidence

Nested Orchestration (when patterns address different aspects):

• Apply different patterns to different sub-problems

• Synthesize at the end

Orchestration Decision Table

Pattern A High Pattern B High Orchestration

BoT ToT Sequential: BoT (explore) → ToT (optimize top options)

BoT HE Sequential: BoT (generate hypotheses) → HE (eliminate)

ToT AR Sequential: ToT (select) → AR (validate before commit)

ToT SRC Sequential: ToT (decide) → SRC (plan implementation)

DR ToT Sequential: DR (resolve tension) → ToT (optimize within synthesis)

AT ToT Sequential: AT (find analogies) → ToT (evaluate derived solutions)

AT BoT Parallel: Both explore, merge findings

HE SRC Sequential: HE (find cause) → SRC (trace mechanism)

RTR HE Sequential: RTR (immediate triage) → HE (post-incident RCA)

RTR AR Sequential: RTR (quick decision) → AR (post-decision validation)

| NDF | ToT | Sequential: NDF (get buy-in) → ToT (optimize within agreed bounds) | | NDF | DR | Sequential: DR (resolve conceptual tension) → NDF (negotiate stakeholders) | | BoT | NDF | Sequential: BoT (explore options) → NDF (negotiate which to pursue) |

RTR Orchestration Rules:

• RTR is typically a STARTING pattern, not an ending one

• After RTR stabilizes situation, follow up with deeper analysis

• RTR → HE for incident root cause analysis

• RTR → ToT for revisiting decision with more time

NDF Orchestration Rules:

• NDF typically FOLLOWS technical analysis (know options before negotiating)

• BoT → NDF: Explore space, then negotiate which options to pursue

• NDF → ToT: After stakeholder agreement, optimize implementation

• DR → NDF: Resolve conceptual tensions first, then stakeholder tensions

Parallel Execution Integration

When to Parallelize

Parallel execution is appropriate when independent reasoning paths can run concurrently without blocking each other:

Condition Parallelization Strategy

Top 2 patterns within 0.3 of each other Run both patterns in parallel, compare results

BoT natural parallelism 8-10 branches can explore simultaneously

Hypothesis testing (HE) Parallel evidence gathering for multiple hypotheses

Multi-perspective needs (MoA pattern) Different "expert personas" analyze in parallel

Parallel Orchestration Patterns

Pattern Combination Parallel Strategy Merge Approach

BoT || AT Parallel exploration from different angles Merge findings, deduplicate insights

ToT branches Parallel subtree exploration at each level Take best-scoring subtree

HE hypotheses Parallel evidence collection for each hypothesis Aggregate evidence, eliminate losers

AR attacks Parallel threat simulation (different attack vectors) Union of discovered vulnerabilities

Parallel Configuration

parallel_config: max_concurrent_patterns: 3 # Max patterns running simultaneously max_concurrent_branches: 8 # Max branches within a single pattern merge_strategy: "consensus" # "consensus" | "voting" | "aggregation" | "best-of-n" timeout_per_branch_ms: 60000 # 60 second timeout per branch early_termination_threshold: 0.95 # Stop early if confidence exceeds this

Configuration Guidelines:

• Use max_concurrent_patterns: 2 for typical orchestration

• Use max_concurrent_branches: 8 for BoT exploration

• Increase timeout_per_branch_ms for complex sub-problems

• Lower early_termination_threshold (e.g., 0.85) when speed matters more than certainty

Merge Strategies

Strategy When to Use Behavior

Consensus High-stakes, need confidence All must agree → boost confidence by +10%; any disagreement → flag for review

Voting Multiple viable options Majority wins; ties broken by highest individual confidence

Aggregation Complementary findings Synthesize all findings into unified result; no filtering

Best-of-N Competitive exploration Take highest confidence result; discard others

Merge Strategy Selection:

If robustness critical → "consensus" If options are mutually exclusive → "voting" If findings are additive → "aggregation" If racing for speed → "best-of-n"

Integration with .reasoning/ Protocol

Parallel execution integrates with the .reasoning/ handover protocol:

.reasoning/ ├── current-context.md # Master context (shared by all branches) ├── parallel-session/ │ ├── config.yaml # Parallel execution configuration │ ├── branch-001/ │ │ ├── approach.md # Pattern being applied │ │ ├── findings.md # Intermediate findings │ │ └── confidence.json # Branch confidence score │ ├── branch-002/ │ │ ├── approach.md │ │ ├── findings.md │ │ └── confidence.json │ └── branch-N/ │ └── ... ├── merge-result.md # Synthesized output from all branches └── handover.md # Final handover (captures all branch insights)

Protocol Rules:

• Each parallel branch writes to its own branch-{id}/ directory

• Branches read shared context but do NOT write to shared files

• Merge phase reads all branches, applies merge strategy

• Handover document captures insights from ALL branches (not just winner)

• Failed branches are preserved for debugging (marked with status: failed )

Branch Handover Template:

Branch {id} Summary

• Pattern Applied: [pattern name]
• Conclusion: [finding]
• Confidence: [X]%
• Key Insights: [unique contributions]
• Disagreements: [where this branch diverged from others]

Feedback Loop: 15-Minute Checkpoint

After 15 minutes of applying selected pattern:

Checkpoint Evaluation

Progress Check

• Have I made meaningful progress toward goal?
• Is my confidence increasing?

Pattern Fit Check

• Am I fighting the methodology?
• Have I discovered new problem characteristics?

New Information

• Has the problem changed?
• Do my characteristic scores need updating?

Decision

If 2+ checks FAIL: → PAUSE: Re-score characteristics → If different pattern scores highest: SWITCH → If same pattern: Continue with awareness

If all checks PASS: → Continue current pattern → Set next checkpoint at 30 min mark

Confidence Aggregation (Fixed)

V1 Problem: Additive confidence boosting was statistically invalid.

V2 Approach: Agreement-based bounded adjustment.

Single Pattern Confidence

Use the pattern's internal confidence score (per its methodology).

Multi-Pattern Confidence

Multi-Pattern Synthesis

Raw Scores

• Pattern A conclusion: [Answer A] at [X]% confidence
• Pattern B conclusion: [Answer B] at [Y]% confidence
• Pattern C conclusion: [Answer C] at [Z]% (if used)

Agreement Analysis

FULL AGREEMENT (same conclusion):

• Final Confidence = MIN(MAX(X, Y, Z) + 5%, 95%)
• Rationale: Independent paths converging increases trust

Confidence Bounds:

• Floor: 10% (never report lower confidence)
• Ceiling: 95% (never report higher confidence)

PARTIAL AGREEMENT (2/3 agree):

• Final Confidence = (AVG of agreeing × 0.7) + (disagreeing × 0.15)
• Must document the disagreement
• Consider: Why does one pattern disagree?

NO AGREEMENT (different conclusions):

• Final Confidence = MIN(X, Y, Z) - 10%
• This is a FEATURE not a bug - disagreement reveals complexity
• Action: Either (a) gather more information, or (b) present trade-offs to stakeholder

Shared Assumption Discount

If patterns share significant assumptions, apply -5% adjustment. (Same LLM, same problem framing, same information = shared blind spots)

Pattern Limitations Reference

Tree of Thoughts (ToT):

• Requires clear evaluation criteria

• Deep recursion may overfit to evaluation function

• Fixed branching can force artificial distinctions

Breadth of Thought (BoT):

• Cannot truly be "exhaustive"

• 8-10 branches may not cover solution space

• Returns multiple options requiring further decision

Self-Reflecting Chain (SRC):

• Limited by weakest step in chain

• Backtracking is costly

• Assumes linear dependency structure

Hypothesis-Elimination (HE):

• Requires discriminating evidence

• Can only find causes in the hypothesis set

• Time-sensitive (may not suit exploration)

Adversarial Reasoning (AR):

• Requires existing solution to attack

• Can be demoralizing if overused

• May miss non-adversarial failure modes

Dialectical Reasoning (DR):

• Requires genuinely opposing valid views

• Synthesis isn't always possible

• Can be slower than just deciding

Analogical Transfer (AT):

• Analogy quality varies widely

• Source domain may mislead

• Requires creativity in finding parallels

Rapid Triage Reasoning (RTR):

• Sacrifices depth for speed

• May miss optimal solution (accepts "good enough")

• Requires follow-up analysis for important decisions

• Not suitable when time is actually available

Negotiated Decision Framework (NDF):

• Requires multiple genuine stakeholders

• Time-intensive (relationship building takes time)

• May produce suboptimal technical solutions for political acceptance

• Doesn't help when one party has absolute authority

Quick Selection Guide

"I need to find the BEST option among known choices" → Tree of Thoughts

"I need to explore ALL possible approaches" → Breadth of Thought

"I need to trace through a logical chain step by step" → Self-Reflecting Chain

"I need to find THE CAUSE of something" → Hypothesis-Elimination

"I need to VALIDATE a solution before committing" → Adversarial Reasoning

"I'm stuck between two valid but opposing approaches" → Dialectical Reasoning

"This problem is novel - no one has solved it in my domain" → Analogical Transfer

"I need to decide RIGHT NOW (minutes, not hours)" → Rapid Triage Reasoning

"Multiple stakeholders with competing interests must agree" → Negotiated Decision Framework

"I'm not sure which to use" → Score the dimensions (Step 1)

--- Parallelism Quick-Reference ---

"Top 2 patterns scored within 0.3" → Run both in parallel, merge with "consensus" or "voting"

"Need to explore many options fast" → Use BoT with max_concurrent_branches: 8

"Testing multiple hypotheses" → HE with parallel evidence gathering

"Need diverse perspectives on same problem" → MoA pattern: parallel expert personas

"Running parallel but need to merge" → consensus (high-stakes) | voting (exclusive) | aggregation (additive) | best-of-n (speed)

Example Application

Problem: "Design our company's approach to AI governance"

Characteristic Scoring

Dimension Score Reasoning

Sequential Dependencies 2 Not really step-by-step

Criteria Clarity 3 Some criteria, but subjective

Solution Space Known 2 Emerging field, options unclear

Single Answer Needed 4 Need one policy

Evidence Available 2 Few precedents to learn from

Opposing Valid Views 5 Big tension: innovation vs caution

Problem Novelty 5 Very new challenge

Robustness Required 4 High stakes, need validation

Solution Exists 1 No candidate solution yet

Time Pressure 2 Strategic decision, not urgent

Pattern Affinity Scores

• ToT: (3×.35)+(4×.30)+(2×.20)+(1×.15) = 2.80

• BoT: (4×.35)+(2×.30)+(3×.20)+(5×.15) = 3.35

• SRC: (2×.45)+(3×.25)+(4×.20)+(1×.10) = 2.55

• HE: (2×.40)+(4×.30)+(1×.20)+(1×.10) = 2.30

• AR: 0 (SolutionExists=1 < 3, nothing to attack yet)

• DR: (5×.50)+(3×.20)+(4×.15)+(4×.15) = 4.30

• AT: (5×.45)+(4×.30)+(4×.15)+(4×.10) = 4.45 ← Highest

• RTR: (2×.50)+(4×.25)+(2×.15)+(1×.10) = 2.40

Recommendation

Primary: Analogical Transfer (4.45) - Look at how other governance challenges were solved Secondary: Dialectical Reasoning (3.80) - Innovation vs caution tension needs synthesis

Orchestration: AT → DR → AR

• Use AT to find analogous governance frameworks (environmental, financial, medical)

• Use DR to synthesize the innovation/caution tension

• Use AR to stress-test the proposed governance approach

Version History

V2.1 (Current):

• Added RTR (Rapid Triage Reasoning) for time-critical decisions

• Added NDF (Negotiated Decision Framework) for multi-stakeholder coordination

• Total: 9 reasoning patterns (up from 7 in V2.0)

• Added 3 new dimensions: SolutionExists, TimePressure, StakeholderComplexity

• Fixed AR formula: now requires SolutionExists ≥ 3

• Fixed DR formula: SingleAnswer no longer penalized when OpposingViews high

• Added uncertainty propagation for close pattern scores

• Added Time Pressure fast-path (auto-selects RTR when TimePressure=5)

• Added NDF validation (requires StakeholderComplexity ≥ 3)

• Enhanced orchestration table with RTR and NDF combinations

V2.0:

• Added 4 new patterns: HE, AR, DR, AT

• Replaced decision tree with weighted multi-dimensional scoring

• Added 15-minute feedback checkpoint

• Fixed confidence aggregation (no more invalid additive boosting)

• Added orchestration decision table

• Added pattern limitations reference

V1.0 (Deprecated):

• 3 patterns: ToT, BoT, SRC

• Order-dependent decision tree

• No feedback loop

• Invalid confidence aggregation