Branch-Solve-Merge (BSM)
Some problems are too large for a single reasoning chain. Branch-Solve-Merge breaks them into independent sub-tasks, solves each in parallel, then merges the solutions — like a team of specialists who each handle their domain before combining findings into a unified report.
Introduced: Branch-Solve-Merge was published in 2023 by Saha et al., addressing the bottleneck of sequential decomposition. While techniques like Least-to-Most solve sub-problems one after another, BSM identifies sub-tasks that can be solved independently — in parallel. A “Branch” planner decomposes the task, independent “Solve” modules handle each branch, and a “Merge” module synthesizes the results. This achieves both better quality and faster execution on tasks with naturally parallel structure.
Modern LLM Status: BSM’s parallel decomposition pattern maps directly to modern agentic architectures where multiple AI agents work simultaneously on different aspects of a problem. Production systems increasingly use BSM-style patterns for document analysis, code review, and research synthesis where different sections can be analyzed independently before merging findings.
Parallel Over Sequential
Sequential decomposition (solve A, then B, then C) creates bottlenecks — each step waits for the previous one. BSM identifies which sub-tasks are truly independent (no dependencies between them) and processes them simultaneously. The Branch module analyzes the task structure to find these independent components.
Each Solve module works on its branch without needing results from other branches. The Merge module then combines all branch solutions, resolving any conflicts and creating a coherent unified output. This is fundamentally different from chain-style techniques where each step depends on the previous one.
Think of it like a newsroom: instead of one journalist writing an entire investigative report alone, a team of reporters each covers their beat — finance, politics, technology — then an editor merges their findings into a cohesive story.
When sub-tasks are independent, solving them sequentially wastes time. BSM’s insight is that many real-world problems have naturally parallel structure: different paragraphs in a document, different aspects of a review, different sections of an analysis. Identifying and exploiting this parallelism produces faster, often higher-quality results because each branch gets full attention rather than being squeezed into a long sequential chain.
The BSM Process
Four stages from complex task to unified solution
Task Analysis
Examine the problem for naturally independent sub-components. Look for aspects that can be analyzed without depending on each other — different topics, different data sources, different evaluation criteria.
“Analyze this 50-page acquisition proposal” — Financial analysis, legal review, market assessment, and technical due diligence are naturally independent branches.
Branch Planning
Decompose the task into independent branches with clear boundaries. Each branch should have a well-defined scope and deliverable. The key criterion: changing the result of one branch should not affect another.
Branch 1: Financial health analysis. Branch 2: Legal and regulatory compliance. Branch 3: Market position and competitive landscape. Branch 4: Technical infrastructure assessment.
Parallel Solving
Each branch is solved independently using the most appropriate technique for that sub-task. Branches can use different prompting strategies — one might use Chain-of-Thought, another might use structured analysis. The independence is what makes parallelism possible.
Financial branch produces revenue analysis and risk metrics. Legal branch produces compliance checklist and red flags. Market branch produces competitive positioning map. Technical branch produces infrastructure assessment and integration risks.
Merge Synthesis
Combine branch solutions, resolve any conflicts between branches, and produce a unified output. The merge step identifies cross-branch connections that individual branches could not see and creates a coherent final deliverable.
Merge finds that strong financials (Branch 1) conflict with regulatory risks (Branch 2), synthesizing a nuanced recommendation: “Proceed with acquisition contingent on resolving compliance gaps identified in Sections 4.2 and 4.7.”
See the Difference
Why parallel branches outperform sequential analysis
Sequential Analysis
Analyze this 30-page research paper. Cover the methodology, results, limitations, and implications.
The paper presents a study on… [Long sequential analysis that loses detail by the time it reaches implications, with methodology analysis influencing how results are interpreted rather than each being assessed independently]
Branch-Solve-Merge
Branch 1 (Methodology): Rigorous controlled design with N=2,400 participants across 3 conditions.
Branch 2 (Results): Statistically significant findings (p<0.01) with strong effect sizes.
Branch 3 (Limitations): Self-reported measures and Western-centric sample limit generalizability.
Branch 4 (Implications): Directly applicable to clinical settings with minor protocol adaptations.
Strong methodology and significant results, but the Western-centric sample means the clinical implications should be validated across diverse populations before broad adoption. The methodology is sound for the studied population; generalization requires replication.
Natural Language Works Too
While structured frameworks and contextual labels are powerful tools, LLMs are exceptionally good at understanding natural language. As long as your prompt contains the actual contextual information needed to create, answer, or deliver the response you’re looking for — the who, what, why, and constraints — the AI can produce complete and accurate results whether you use a formal framework or plain conversational language. But even in 2026, with the best prompts, verifying AI output is always a necessary step.
Branch-Solve-Merge in Action
See how parallel branches produce comprehensive, balanced analysis
“Synthesize findings from these five research papers on remote work productivity.”
Branch 1 (Paper A): Found 12% productivity increase in knowledge workers; attributed to reduced commute stress and flexible scheduling.
Branch 2 (Paper B): Found 8% decrease in collaborative tasks; attributed to communication friction and timezone misalignment.
Branch 3 (Paper C): Found no significant change overall but noted strong individual variation based on home environment quality.
Branch 4 (Papers D&E): Both found hybrid models (3 days office, 2 remote) outperformed fully remote and fully in-office configurations.
Merge: The literature converges on a nuanced finding: remote work boosts individual-focused productivity but can hinder collaboration. Hybrid models appear to capture benefits of both. The key moderating variable is home environment quality, which explains much of the individual variation across studies. Always verify these findings against the original source papers before citing them.
“Review this pull request across our authentication module, database layer, and API endpoints.”
Branch 1 (Auth Module): Token validation logic is correct. Session handling follows OWASP guidelines. One concern: refresh token rotation not implemented for the new OAuth flow.
Branch 2 (Database Layer): Migration scripts are clean. Indexes added for new query patterns. Potential N+1 query in the user permissions lookup (line 247).
Branch 3 (API Endpoints): Rate limiting properly configured. Input validation comprehensive. Missing error handling for the edge case where token expires mid-request.
Merge: The PR is structurally sound with good security practices. Three items need attention before approval: (1) Add refresh token rotation in auth module, (2) Fix the N+1 query in permissions lookup, (3) Add token-expiry error handling in API layer. Items 1 and 3 are related — the missing token rotation could trigger the unhandled expiry case. Recommend verifying all findings against the actual code before merging.
“Evaluate whether we should expand into the European market this quarter.”
Branch 1 (Financial): Current cash reserves support expansion. Projected ROI of 18-24% within 18 months based on comparable market entries. Currency risk is moderate with EUR/USD volatility.
Branch 2 (Market): European SaaS market growing at 22% YoY. Two direct competitors already established but focused on enterprise segment, leaving SMB underserved. Demand signals strong from inbound European leads (340 in Q4).
Branch 3 (Operational): GDPR compliance requires 6-8 weeks of engineering work. EU data residency needs new infrastructure in Frankfurt or Dublin. Support coverage gap: no team in European timezones currently.
Merge: Financial and market conditions favor expansion, but operational readiness is the bottleneck. Recommendation: Begin GDPR compliance and infrastructure setup this quarter, target market entry next quarter. The SMB gap identified in the market analysis aligns well with our product positioning. Note: All market data and projections should be verified against current industry reports before making final decisions.
When to Use Branch-Solve-Merge
Best for tasks with naturally independent sub-components
Perfect For
Problems where different dimensions, sections, or aspects can be analyzed without depending on each other’s results.
Reports, papers, or contracts where each section can be reviewed independently before synthesizing a unified assessment.
Assessments that span multiple criteria — financial, technical, legal, operational — where each dimension deserves dedicated attention.
When parallel execution can reduce total processing time — multiple API calls running simultaneously rather than sequentially.
Skip It When
When each step genuinely depends on the previous step’s output — BSM requires independence between branches to work correctly.
Questions that can be answered directly without decomposition — the branching overhead adds complexity without benefit.
If the output of Branch A is needed as input for Branch B, the branches are not truly independent and should use sequential techniques instead.
Use Cases
Where Branch-Solve-Merge delivers the most value
Document Summarization
Branch by section or chapter, summarize each independently, then merge into a comprehensive executive summary that captures the full document’s scope.
Code Review
Branch by module or file, review each for bugs, security issues, and style independently, then merge findings into a prioritized review summary.
Research Synthesis
Branch by source or study, extract key findings from each independently, then merge to identify consensus, contradictions, and gaps across the literature.
Business Due Diligence
Branch by dimension — financial, legal, market, operational — evaluate each independently, then merge into a unified risk-reward assessment.
Content Moderation
Branch by policy category (hate speech, misinformation, spam, NSFW), evaluate content against each policy independently, then merge for a final moderation decision.
Competitive Analysis
Branch by competitor, analyze each independently across consistent criteria, then merge to reveal relative positioning and strategic opportunities.
Where BSM Fits
BSM bridges sequential decomposition and multi-agent orchestration
Not every problem has obvious parallel structure. Look for independent dimensions: different topics, different time periods, different stakeholders, different metrics. If changing the result of one branch doesn’t affect another, they’re truly independent and BSM will help. When in doubt, ask: “Could two different people work on these parts simultaneously without needing to coordinate?”
Related Techniques
Explore complementary decomposition approaches
Branch Your Reasoning
Apply parallel decomposition to your own complex tasks or explore other techniques in the Praxis Library.