AI Model Strategy for OpenCode

A small team of models beats constant switching. This page lays out exactly which model handles which job — for building apps and for running a portfolio of 100 Astro blogs and lead-generation sites — plus the workflows, rules, and workload math behind the assignments.

3
Core models in the team
4
Steps in the app workflow
6
Steps in the content pipeline
100
Sites served by one theme
The core idea: assign models by the cost of being wrong, not by prestige. Expensive reasoning goes where a mistake is expensive. Cheap models go where correctness is easy to verify.
Jump to Building Apps Jump to Site Portfolio

Two Game Plans, One Principle

The two jobs — building apps and running a 100-site portfolio — need different lineups, but the same discipline: the right model for the risk level of the task.

🏗️ Building Apps in OpenCode

  • Claude Opus 5.5 leads architecture and audits — high cost of being wrong.
  • GPT-6 is the primary developer — implements features, tests, debugs.
  • MiMo 2.6 handles cheap, clearly scoped work — Pro for components, Flash for formatting.

🌐 Running 100 Astro Sites

  • Claude Opus 5.5 owns the master theme and major redesigns only.
  • GPT-6 owns hard development, research, articles, and audits.
  • MiMo 2.6 does the bulk of routine site and content work.

Building Apps: The Team

Six roles, three models. OpenCode supports different models for different agents, so these roles can be configured once instead of switched by hand every time.

JobPreferred modelWhen to use it
Lead architectClaude Opus 5.5Plan architecture, uncover dependencies, challenge technical assumptions
Primary developerGPT-6 (coding-capable OAuth model)Implement features, edit files, write tests, debug
Second-opinion reviewerClaude Opus 5.5Audit completed features, identify flaws and security issues
Budget developerMiMo 2.6 ProStraightforward components, repetitive coding, well-defined changes
Cheap utility workMiMo 2.6 FlashFormatting, documentation, simple refactors
Complex bug investigatorGPT-6 High reasoning, if availableTrace difficult failures and propose targeted fixes
Note on benchmarks: current independent coding results support Opus as a strong architect choice, but benchmarks vary by coding environment and do not guarantee performance on your projects. Assign by cost of being wrong, then benchmark against your own work.

Building Apps: The Workflow

1 · Opus 5.5 Plan
→
2 · GPT-6 Build
→
3 · Opus 5.5 Audit
→
4 · MiMo 2.6 Pro Cleanup
1

Plan Claude Opus 5.5

Research, architecture, edge cases, acceptance criteria.

2

Build GPT-6

Implement one feature at a time, run tests.

3

Audit Claude Opus 5.5

Review correctness, security, and missing requirements.

4

Cleanup MiMo 2.6 Pro

Documentation, small fixes, routine components.

Where to start on your next app: put Opus 5.5 in OpenCode's Plan mode, then hand the approved plan to GPT-6 in Build mode. That is the combination to test first.

Golden Rules

Rule 1 Independent judgment

The model that writes the code should not be the only model deciding whether it is correct.

Rule 2 Evidence over assumptions

No model should substitute its own assumptions for research or actual testing.

Rule 3 Verify cheap work

Use MiMo for work where correctness is easy to verify. Cheap generation is not cheap if it creates hours of rework.

Rule 4 No prestige assignments

Do not pay for Opus-level reasoning to generate every blog post — and never let a budget model redesign the master theme.

Portfolio: The Four Priorities

1 · Consistency

Every site follows the same Astro theme, component rules, and technical standards.

2 · Search performance

Sites are structured to earn search visibility, including traditional search and AI-powered search experiences.

3 · Content quality

Articles are accurate, useful, distinctive, and appropriate for their niche.

4 · Scalability

You can build and maintain 100 sites without spending a fortune on model usage or constantly repairing things.

Theme as Product, Sites as Instances

One major architectural decision prevents more drift than simply choosing a better model: treat the Astro theme as a product and each website as an instance of that product. Models should not be independently designing 100 websites — they should be configuring and populating one well-maintained system.

🏛️ Master Astro Theme Opus 5.5 GPT-6 Layouts, components, design tokens, navigation patterns, SEO defaults, schema generation, canonical URLs, sitemaps, page templates, performance standards
↓ configured and populated by ↓
Site AConfig + content
Site BConfig + content
Site CConfig + content
…eventually 100 sites
↓ fed by ↓
📝 Shared SEO & Content Pipeline GPT-6 MiMo 2.6 Research → Brief → Draft → Verify → Publish → Monitor

What each site supplies

  • Brand configuration
  • Location and business information
  • Service data
  • Content

What the master theme owns

  • Shared, versioned theme components — not 100 independently modified copies
  • Astro content collections for structured content and schema validation
  • Separate GitHub repositories and Cloudflare deployments per site still work fine

Portfolio: Model Assignments

Roles to start with in OpenCode, then benchmark against your actual sites.

ResponsibilityPrimary modelSecondary / budget model
Master Astro theme architectureOpus 5.5GPT-6
New site setup from templateMiMo 2.6 ProGPT-6
Complex Astro / React developmentGPT-6Opus 5.5
Technical SEO architectureOpus 5.5GPT-6
Keyword and topic research strategyGPT-6MiMo 2.6 Pro
Content briefs and outlinesMiMo 2.6 ProGPT-6
Long-form SEO articlesGPT-6MiMo 2.6 Pro
Local service and landing pagesMiMo 2.6 ProGPT-6
Content fact-checking and editorial reviewGPT-6 with external sourcesOpus 5.5
Technical SEO audits and difficult fixesGPT-6Opus 5.5
Routine content updates and metadataMiMo 2.6 Flash / ProGPT-6
Monthly SEO performance analysisGPT-6MiMo 2.6 Pro
Major site redesign or template upgradeOpus 5.5GPT-6

Search, Answer Engines, and AI Visibility

AreaWhat the system should do
Technical SEOCrawlability, indexability, canonical tags, redirects, sitemaps, performance
On-page SEOSearch intent, headings, titles, internal links, relevant entities
Local SEOService-area relevance, legitimate business details, location-specific content
Answer Engine Optimization (AEO)Answer real user questions directly and accurately
Generative Engine Optimization (GEO) / AI searchOriginal, credible, well-structured information that AI systems can cite
Structured dataValid, applicable Schema.org markup matching visible content
Content freshnessUpdate outdated information based on evidence and performance
Conversion SEOTurn qualified visitors into leads, subscribers, or customers
Good news from Google: traditional SEO fundamentals remain relevant to AI Overviews and AI Mode. There is no special AI-search schema required to appear in those experiences — so no money goes to speculative AI SEO tricks. Concentrate on strong topical coverage, original information, answer quality, crawlability, and genuine authority.

Automating Ongoing Content

This is where MiMo earns its keep. Automation should create drafts and surface evidence — not blindly publish everything.

1 · Research
→
2 · Brief
→
3 · Draft
→
4 · Review
→
5 · Publish
→
6 · Monitor
1

Research

GPT-6

Search intent, competitors, sources, content gaps.

2

Content brief

MiMo 2.6 Pro

Outline, audience, questions, internal-link opportunities.

3

Draft

MiMo 2.6 Pro or GPT-6

Write to a defined brief and brand voice.

4

Editorial review

GPT-6

Check accuracy, originality, unsupported claims, and usefulness.

5

Publish

Automated Astro pipeline

Validate frontmatter, links, schema, and build.

6

Monitor

MiMo 2.6 + GPT-6

Analyze Search Console trends and prioritize updates.

Two guardrails: Google warns that mass-producing low-value, unoriginal pages can constitute scaled content abuse, regardless of whether AI or humans created them. And for medical, legal, and financial content, require additional qualified review before publishing consequential claims.

Three Reusable Skills

Rather than unique instructions for every website, build three shared OpenCode skills. They share standards but keep separate responsibilities, which makes them easier to improve and test.

🏗️ Astro Site Builder

Creates and updates websites while enforcing the master theme, design system, SEO standards, and deployment rules.

MiMo routine site creation   GPT-6 exceptions

📝 SEO & Content Engine

Researches keywords and search intent, creates content briefs, produces articles, checks claims, handles internal linking, and prepares publishing-ready content.

📊 Portfolio SEO Auditor

Reviews Search Console data, detects technical problems, identifies declining pages and content opportunities, and prioritizes work across the entire portfolio.

Workload Split

Where the model usage should end up after testing: most routine work on MiMo, important content and SEO decisions on GPT-6, Opus reserved for architecture and hard audits.

Illustrative workload distribution

MiMo 2.6
60%
routine work
GPT-6
30%
important calls
Claude Opus 5.5
10%
architecture

Illustrative target, not measured token usage or cost.

Who holds the primary role across the 13 portfolio jobs

GPT-6
6 of 13 jobs
46%
MiMo 2.6
4 of 13 jobs
31%
Claude Opus 5.5
3 of 13 jobs
23%

Counted from the model assignments table above. Opus holds few jobs but the expensive ones: theme architecture, technical SEO architecture, and major redesigns.

Bottom Line

The biggest recommendation: before building dozens more sites, invest in locking down the master Astro theme and the automated quality checks. A flaw in one site is inconvenient. A flaw replicated across 100 sites is expensive.
The flip side: fix one problem in a properly shared system, and you potentially improve all 100 sites. Make that shared system the foundation of the entire website portfolio.
For app building: start with Opus 5.5 in OpenCode's Plan mode, hand the approved plan to GPT-6 in Build mode, and never let the writer of the code be its only judge.

Guidance in this page references Google for Developers documentation on AI features in Search and scaled content abuse. · Google Search Central documentation