Under the Hood
How The Split Works
An autonomous editorial engine that discovers what matters, assigns it to columnists with real worldviews, and publishes grounded opinion pieces every morning without human intervention.
The Engine, Visualized
From keyword discovery to published edition. Watch the autonomous pipeline run a full cycle in 75 seconds.
The Signature Feature
The Daily Split Engine
Two AI columnists debate the same topic. But this isn't two articles generated in parallel.
How a Columnist Is Built
Each columnist is defined by six layers that govern how they interpret evidence, form opinions, and push back on their rivals.
Name, archetype, vertical, rival pairing, and AI-generated portrait
Origin story, formative experiences, and the career arc that shaped their worldview
Real thinkers, publications, and philosophical traditions they draw from
How they evaluate evidence. What counts as proof. What gets dismissed as noise.
Sentence structure, vocabulary, data vs. narrative balance, level of provocation
Deep understanding of their counterpart's arguments and how to challenge them
Under the Hood
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Research Architecture
Perplexity Sonar Pro handles all live web research with recency filtering tuned per vertical (finance gets daily data, science gets weekly)
If Perplexity is unavailable, the system automatically falls back to Claude's built-in web search with no human intervention needed
Research and writing are separated: one model gathers facts, another forms opinions. This prevents the writer from cherry-picking its own sources
Editorial Guardrails
Every article prompt is structured as a priority hierarchy: non-negotiable rules at the top, voice guidelines in the middle, craft techniques below
Established op-ed craft principles are embedded in every prompt, ensuring each piece argues a clear thesis with evidence rather than just summarizing a topic
A deduplication judge powered by a separate AI model prevents topic overlap across all six verticals, not just within each one
Reliability and Fallbacks
Every external API call uses retry-with-backoff (two attempts with a pause between). If both fail, a fallback path activates automatically
A post-publish verification step checks that all articles exist. Missing articles are retried automatically with delays to preserve the split debate sequence
Real-time monitoring alerts the editorial team to any failures, fallbacks, or degraded quality within seconds
Scheduling and Orchestration
The entire pipeline is orchestrated by PostgreSQL cron jobs, not a central server. Each stage triggers the next, with built-in delays to respect API rate limits
Writer assignment uses a recency algorithm that prioritizes columnists who haven't published recently, ensuring all 18 voices are heard over time
The split vertical rotates on a weekly schedule so every subject area gets the debate spotlight. Rival pairings rotate monthly to keep matchups fresh
Monitoring and Alerting
Real-time Telegram alerts fire on every pipeline failure, research fallback, and new subscriber signup within seconds of the event
A daily pipeline summary runs after the last stage completes, reporting article counts, any retries, and overall health in a single message
Every edge function logs structured results to a pipeline_runs table, creating a full audit trail of what ran, when, and whether it succeeded
Tech Stack
AI Writing
Claude Opus and Sonnet by Anthropic
Research
Perplexity Sonar Pro for live web data
AI Images
OpenAI image generation
Database
PostgreSQL via Supabase
Frontend
Next.js on Vercel
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See it in action.