Round 116

Service Boundaries

A product team is splitting a growing software platform into services. The system currently handles authentication, billing, notifications, reporting, and user profile management in a single codebase. Traffic is increasing, a few components need independent scaling, and several teams are starting to work in parallel. The goal is to improve delivery speed and operational resilience without introducing excessive complexity, latency, or data consistency problems. Constraints include a small platform engineering team, limited budget for new infrastructure, existing database schemas that are hard to change, and a requirement to keep downtime minimal during migration. The main tradeoff is whether to optimize for rapid decomposition, strong transactional consistency, simpler operations, or long-term organizational autonomy.

Dashboard

Status

DECIDED

Winner

A · Split the platform into a small number of coarse-grained services organized around major business domains, keeping shared data access patterns where necessary and migrating incrementally behind stable APIs.

Majority

Duration

6635 ms

Topic

Options

A Split the platform into a small number of coarse-grained services organized around major business domains, keeping shared data access patterns where necessary and migrating incrementally behind stable APIs.

1.60 of 3 PPV winner

C Use a hybrid model with a few high-change areas extracted as services while leaving core transactional workflows in the monolith to preserve consistency and reduce operational overhead.

1.40 of 3

B Adopt a modular monolith with strict internal boundaries first, delaying service extraction until modules and ownership are well-defined and operational readiness is higher.

0.00 of 3

D Decompose aggressively into many fine-grained services aligned to individual capabilities, even if it requires building robust orchestration, observability, and service-to-service communication early.

0.00 of 3

E Center the architecture on an event-driven design with asynchronous workflows and eventual consistency, using a message bus to decouple teams and isolate load spikes.

0.00 of 3

Checks

Baselines

PPV no gold answer

Majority no gold answer

Comparison PPV matched majority

k samples8

Agents3

Parsed samples 24 / 24

Quality split agent disagreement

PPV

Top Influences

Gemini 3 Flash Preview · delegate 1.397

GPT 5.4 mini · delegate 1.182

Claude Sonnet 5 · delegate 1.150

Samples

Answer Distribution

Claude Sonnet 5 A: 4 C: 4

GPT 5.4 mini A: 6 C: 2

Gemini 3 Flash Preview C: 8

PPV

Influences

Label	Role	Score
Gemini 3 Flash Preview	delegate	1.397
GPT 5.4 mini	delegate	1.182
Claude Sonnet 5	delegate	1.150

Voting matrix

Constructed Delegation Matrix

To / From	Claude Sonnet 5	GPT 5.4 mini	Gemini 3 Flash Preview
Claude Sonnet 5	0.000	0.150	0.000
GPT 5.4 mini	0.182	0.000	0.000
Gemini 3 Flash Preview	0.182	0.150	0.000
A	0.637	0.700	0.000
B	0.000	0.000	0.000
C	0.000	0.000	1.000
D	0.000	0.000	0.000
E	0.000	0.000	0.000

Embeddings

Sample Embeddings

24 samples

Claude Sonnet 5 GPT 5.4 mini Gemini 3 Flash Preview

Samples

Agent Responses

Claude Sonnet 5 openai_compatible · anthropic/claude-sonnet-5

#0 A · Split the platform into a small number of coarse-grained services organized around major business domains, keeping shared data access patterns where necessary and migrating incrementally behind stable APIs. 1536 dims

The constraints—small team, limited budget, rigid schemas, and minimal downtime—rule out aggressive fine-grained decomposition (D) or a full event-driven overhaul (E), both of which add significant operational complexity. A modular monolith (B) delays needed s...

#1 A · Split the platform into a small number of coarse-grained services organized around major business domains, keeping shared data access patterns where necessary and migrating incrementally behind stable APIs. 1536 dims

The team is small, budget-limited, and needs minimal downtime with hard-to-change schemas—this rules out aggressive fine-grained decomposition (D) and full event-driven asynchronous redesign (E), which both demand significant new infrastructure and operational...

#2 C · Use a hybrid model with a few high-change areas extracted as services while leaving core transactional workflows in the monolith to preserve consistency and reduce operational overhead. 1536 dims

Given the small platform team, limited budget, hard-to-change schemas, and low-downtime requirement, aggressive fine-grained decomposition (D) or a full event-driven overhaul (E) would introduce excessive orchestration, observability, and consistency complexit...

#3 C · Use a hybrid model with a few high-change areas extracted as services while leaving core transactional workflows in the monolith to preserve consistency and reduce operational overhead. 1536 dims

Given a small platform team, limited budget, and hard-to-change schemas, strict data consistency and low operational overhead are more valuable than granularity or full autonomy. Option C addresses this by extracting only high-change areas (like notifications/...

#4 C · Use a hybrid model with a few high-change areas extracted as services while leaving core transactional workflows in the monolith to preserve consistency and reduce operational overhead. 1536 dims

Given a small platform team, limited budget, hard-to-change schemas, and minimal downtime requirements, aggressive fine-grained decomposition or full event-driven eventual consistency would introduce too much operational and consistency risk. The hybrid approa...

#5 A · Split the platform into a small number of coarse-grained services organized around major business domains, keeping shared data access patterns where necessary and migrating incrementally behind stable APIs. 1536 dims

Given the small platform engineering team, limited budget, hard-to-change schemas, and need for minimal downtime, aggressive fine-grained decomposition (D) or a full event-driven overhaul (E) would introduce too much operational complexity too soon. A hybrid a...

#6 C · Use a hybrid model with a few high-change areas extracted as services while leaving core transactional workflows in the monolith to preserve consistency and reduce operational overhead. 1536 dims

Given a small platform team, tight budget, legacy schemas, and minimal downtime requirements, aggressive fine-grained decomposition (D) or full event-driven overhaul (E) would introduce excessive operational complexity too early. A hybrid approach (C) best bal...

#7 A · Split the platform into a small number of coarse-grained services organized around major business domains, keeping shared data access patterns where necessary and migrating incrementally behind stable APIs. 1536 dims

The constraints—small platform team, limited budget, legacy schemas, and minimal downtime—favor a low-risk, incremental approach rather than aggressive decomposition or a full architectural overhaul. Coarse-grained services aligned to business domains reduce o...

GPT 5.4 mini openai_compatible · openai/gpt-5.4-mini

The scenario emphasizes balancing faster delivery and independent scaling with limited staffing, budget, and migration risk, so an approach that avoids excessive service sprawl is best. A small number of coarse-grained services lets teams split work and scale ...

#1 C · Use a hybrid model with a few high-change areas extracted as services while leaving core transactional workflows in the monolith to preserve consistency and reduce operational overhead. 1536 dims

The team needs better scaling and parallel development, but the constraints strongly favor minimizing operational complexity, preserving existing databases, and migrating with low downtime. A few components need independent scaling, so extracting only the high...

#2 A · Split the platform into a small number of coarse-grained services organized around major business domains, keeping shared data access patterns where necessary and migrating incrementally behind stable APIs. 1536 dims

The best choice is the one that balances decomposition with low operational and migration risk. Given the small platform team, limited budget, hard-to-change databases, and need for minimal downtime, a coarse-grained incremental split around major business dom...

#3 A · Split the platform into a small number of coarse-grained services organized around major business domains, keeping shared data access patterns where necessary and migrating incrementally behind stable APIs. 1536 dims

Given the need to improve scalability and parallel team delivery while keeping complexity, latency, and consistency risks manageable, a coarse-grained decomposition is the best fit. It allows incremental migration behind stable APIs, minimizes downtime, and av...

#4 A · Split the platform into a small number of coarse-grained services organized around major business domains, keeping shared data access patterns where necessary and migrating incrementally behind stable APIs. 1536 dims

The best fit is to split into a few coarse-grained services, because the team needs better scaling and parallel delivery without creating too much operational burden or data consistency risk. This approach also matches the constraints of limited platform capac...

#5 C · Use a hybrid model with a few high-change areas extracted as services while leaving core transactional workflows in the monolith to preserve consistency and reduce operational overhead. 1536 dims

The constraints point to minimizing operational and migration risk while still enabling some independent scaling and team parallelism. A few coarse-grained services or a hybrid extraction would be too slow to relieve current pressure, while aggressive fine-gra...

#6 A · Split the platform into a small number of coarse-grained services organized around major business domains, keeping shared data access patterns where necessary and migrating incrementally behind stable APIs. 1536 dims

The team needs a balance of scalability, team parallelism, and low operational risk under tight budget and limited platform support, so a coarse-grained, incremental split is the safest fit. It preserves simpler operations and minimizes migration downtime whil...

The constraints point toward minimizing operational complexity and migration risk while still enabling some independent scaling and parallel team work. A coarse-grained split into a few domain services lets the team move incrementally behind stable APIs, reuse...

Gemini 3 Flash Preview openai_compatible · google/gemini-3-flash-preview

#0 C · Use a hybrid model with a few high-change areas extracted as services while leaving core transactional workflows in the monolith to preserve consistency and reduce operational overhead. 1536 dims

The team faces constraints of a small engineering staff and a limited budget, making aggressive decomposition or complex event-driven architectures too operationally demanding. A hybrid model (Option C) balances the need for independent scaling in high-traffic...

The system faces constraints of a small engineering team and limited infrastructure budget, making aggressive microservices or complex event-driven architectures (Options D and E) premature and risky. Option B focuses on internal refactoring but may not addres...

Given the constraints of a small engineering team, limited infrastructure budget, and hard-to-change schemas, the priority is to balance delivery speed with operational safety. A hybrid model allows the team to gain independent scalability for high-traffic com...

The team must balance the need for independent scaling and parallel work against constraints like a small platform team and difficult-to-change database schemas. Option (C) offers a pragmatic middle ground by extracting high-change, high-scale components (like...

The constraints of a small engineering team and a limited infrastructure budget suggest that aggressive microservices (D) or complex event-driven rewrites (E) would introduce excessive operational overhead. Given that several teams are already starting paralle...

The team faces constraints of a small engineering staff and a limited budget, making aggressive decomposition or complex event-driven architectures too operationally intensive. Option (C) balances the need for independent scaling and parallel development by ex...

The scenario balances a need for independent scaling and parallel team development against constraints of limited infrastructure budget, a small platform team, and difficult-to-change database schemas. Option (C) provides the most pragmatic approach by migrati...

#7 C · Use a hybrid model with a few high-change areas extracted as services while leaving core transactional workflows in the monolith to preserve consistency and reduce operational overhead. 1536 dims

The team must balance the need for independent scaling and parallel development against constraints like a small platform team, limited budget, and complex database schemas. A hybrid approach allows the team to target specific high-growth areas (like notificat...

Timings

Stages

Sampling6183 ms

Embedding447 ms

Signals4 ms

PPV1 ms

Errors

Agent and Round Errors

No errors recorded.