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4 runs2 prompts
4 runs
2 runs · same prompt

Incident management process

A B2B payments platform in New York (260 engineers in 28 teams, 2,100 customers, $4B processed a month, a 99.95% SLA with service credits) runs about 180 services on Kubernetes across two AWS regions, with a shared PostgreSQL cluster for the ledger. In the last 12 months: 31 customer-impacting incidents, median time to detect 22 minutes (customers detected 40% of them first), median time to mitigate 3 h 10 min, $1.3M paid in SLA credits, two incidents in which nobody was sure who was in charge for over an hour, and a CEO email about "outages we hear about from clients". On-call exists in 12 of the 28 teams, unpaid, fed by alerts from six different tools — 3,400 alerts a month, 85% of them noise; there is no severity scale, status-page updates are written by whoever is around, and postmortems happen for some incidents, in various formats, with action items that are rarely tracked (11 of 64 closed). A SOC 2 Type II audit in eight months will test incident response. Engineers push back against "carrying a pager for other teams' code". Define the incident management process: severity levels and what each one triggers; roles (incident commander, communications, scribe, subject-matter responders) and how they are staffed 24x7 across 28 teams; the on-call structure, rotations, compensation and the rules for alert quality; detection and escalation paths; internal and customer communications (status page, account managers, regulators when required) with their timings; postmortems (when mandatory, format, blameless review, ownership and tracking of actions); the metrics and reviews that show whether it works; and how it is introduced across the teams without waiting for the audit.

Compare runs →
study 5x3completed
d7442a5f
opus5gpt5.6-solqwen3.8-maxgrok4.6deepseek-v4-pro
Collaboration
5 agents
4 total rounds
5 voters
Duration
18 min 25 s
Collaboration
Cost · USD
$6.46
Collaboration
+ $6.49 analysis
Selected proposal
opus5
4/5 votes · 35 steps
Open report →
Configuration & execution details · 1 analysis

Models & parameters

opus5 · anthropic/claude-opus-5adaptive thinking, effort high
gpt5.6-sol · openai/gpt-5.6-solreasoning effort high
qwen3.8-max · alibaba/qwen3.8-maxthinking on, budget 16.0k tokens
grok4.6 · xai/grok-4.6reasoning effort high
deepseek-v4-pro · deepseek/deepseek-v4-prothinking on, effort high
Run ID
d7442a5f-fd3b-438a-8816-91f4625f2492
Configuration ID
97fce665f0005a7b
Made with
executor 0.1.5
Rounds
1 initial + 3 refinement rounds
Collaboration tokens
907.6k in · 269.2k out
Latest analysis tokens
724.3k in · 114.8k out
Selected agent
opus5_refine_1
anthropic/claude-opus-5
cheap 3x2completed
ca115d77
claudeHaiku4.5deepseek-flashqwen3.8-flash
Collaboration
3 agents
3 total rounds
3 voters
Duration
7 min 45 s
Collaboration
Cost · USD
$0.31
Collaboration
+ $2.26 analysis
Selected proposal
deepseek-flash
2/3 votes · 24 steps
Open report →
Configuration & execution details · 1 analysis

Models & parameters

claudeHaiku4.5 · anthropic/claude-haiku-4-5extended thinking, 16.0k tokens · temp 1
deepseek-flash · deepseek/deepseek-flashthinking on, effort high
qwen3.8-flash · alibaba/qwen3.8-flashthinking on, budget 16.0k tokens
Run ID
ca115d77-0be6-47f1-a517-8ac1272dcad1
Configuration ID
81954235c60893fe
Made with
executor 0.1.2
Rounds
1 initial + 2 refinement rounds
Collaboration tokens
162.9k in · 112.1k out
Latest analysis tokens
252.3k in · 40.0k out
Selected agent
deepseek-flash_refine_2
deepseek/deepseek-flash
2 runs · same prompt

E-commerce monolith migration

A mid-size European fashion retailer runs its e-commerce on a 10-year-old monolith: Java 8 / Spring, about 2 million lines, one PostgreSQL database of 1.2 TB with 350 tables and heavy use of stored procedures and cross-module joins. It serves 8 countries, 3 currencies and 4 languages, with about 40,000 orders a day and peaks of 12x during sales. The monolith contains: the storefront (server-rendered, plus a separate mobile app hitting the same endpoints), catalogue and search (a Lucene index rebuilt nightly), pricing and promotions (the most complex module, 200,000 lines, with country-specific rules nobody fully understands), cart and checkout with three payment providers, order management, inventory synchronised every 15 minutes with the warehouse system via file exchange, customer accounts and loyalty, returns, and a back-office used by 300 staff. Deployments happen every two weeks as a single artefact with a 30-minute maintenance window; test coverage is 25% and mostly unit tests. Five teams of 8 developers, each organised around a business area but all committing to the same repository. Plan the migration to independently deployable services over 12 months with no feature freeze, no unplanned downtime and the ability to roll back every step, preserving the peak-season capacity (sales in January and July must not be put at risk).

Compare runs →
cheap 3x2completed
d3142150
claudeHaiku4.5deepseek-flashqwen3.8-flash
Collaboration
3 agents
3 total rounds
3 voters
Duration
8 min 0 s
Collaboration
Cost · USD
$0.30
Collaboration
+ $0.094 analysis
Selected proposal
claudeHaiku4.5
2/3 votes · 20 steps
Open report →
Configuration & execution details · 2 analyses

Models & parameters

claudeHaiku4.5 · anthropic/claude-haiku-4-5extended thinking, 15.0k tokens · temp 1
deepseek-flash · deepseek/deepseek-flashthinking on, effort low
qwen3.8-flash · alibaba/qwen3.8-flashthinking on, budget 4.0k tokens
Run ID
d3142150-bc02-4660-9022-aebab8777750
Configuration ID
41556a0e429b9f9f
Made with
version not recorded
Rounds
1 initial + 2 refinement rounds
Collaboration tokens
144.5k in · 106.6k out
Latest analysis tokens
113.8k in · 30.5k out
Selected agent
claudeHaiku4.5_refine_1
anthropic/claude-haiku-4-5
Unnamed runcompleted
b5143655
claudeHaiku4.5gpt-5.6-terragrok-4.6deepseek-v4-proqwen3.8-max
Collaboration
5 agents
5 total rounds
5 voters
Duration
18 min 6 s
Collaboration
Cost · USD
$2.22
Collaboration
+ $0.83 analysis
Selected proposal
grok-4.6
4/5 votes · 22 steps
Open report →
Configuration & execution details · 1 analysis

Models & parameters

claudeHaiku4.5 · anthropic/claude-haiku-4-5extended thinking, 15.0k tokens · temp 1
gpt-5.6-terra · openai/gpt-5.6-terrareasoning effort medium
grok-4.6 · xai/grok-4.6reasoning effort medium
deepseek-v4-pro · deepseek/deepseek-v4-prothinking on (model default)
qwen3.8-max · alibaba/qwen3.8-maxthinking on, budget 16.0k tokens
Run ID
b5143655-673f-4a5d-b8e9-cdb899e5c234
Configuration ID
Not recorded
Made with
version not recorded
Rounds
1 initial + 4 refinement rounds
Collaboration tokens
693.3k in · 235.9k out
Latest analysis tokens
305.9k in · 37.2k out
Selected agent
grok-4.6_refine_3
xai/grok-4.6