How BeforeTomorrow Works

BeforeTomorrow generates world-class presentations by orchestrating 15+ specialized AI agents (Claude Opus 4.6 + Sonnet 4.6 on AWS Bedrock) through a dependency-aware parallel pipeline. Each deck passes a 13-critic quality gate with automated Reflexion repair. The system uses Tree-of-Thoughts planning with 8 narrative structures, producing unique per-slide design compositions — no templates — in 10-15 minutes per artifact.

What is the generation pipeline?

The pipeline follows 6 phases executed by the Council Orchestrator. Each phase uses dependency-aware parallel execution to minimize wall-clock time while maximizing quality.

PhaseAgentsOutput
1. PlanningTree-of-Thoughts Planner (Opus 4.6, 8 branches)Narrative structure + slide budget
2. Research WaveOutline ∥ Domain ∥ Researcher ∥ Storyteller ∥ Investor-Psychology (parallel)Structured intelligence from 5 perspectives
3. Validation WaveBrand ∥ Financial-Auditor ∥ Fact-Checker (parallel)Brand compliance + financial accuracy + fact verification
4. Creative WaveVisual Director ∥ Copy Director ∥ Chart Director (parallel)Per-slide design + professional copy + data visualization
5. Post-ProductionCopy-Editor ∥ Asset-Prompt-Craftsman ∥ Design-Architect (parallel)Polish + asset prompts + unique layouts per slide
6. Quality Gate13 critics + Synthesis Orchestrator + Reflexion repair (up to 2 passes)Final deck — ship only if quality threshold met

What are the key performance numbers?

MetricValue
Total agents per deck15+ ULTRA-grade
Quality critics13 (narrative, design, fact, constitutional, competitive, coherence)
Agent prompt length4,000-7,000 words each
Narrative structures8 (including three-act, pyramid, inductive, problem-solution)
Layout compositions32 canonical entries
Generation time10-15 minutes (was 21 min, optimized via targeted repair)
Cost per deck$3-20 LLM compute (no cap)
Industries supported140+ with domain-specific intelligence
AI modelsClaude Opus 4.6 (creative) + Sonnet 4.6 (extraction)
Data residencyEU (AWS Bedrock cross-region profiles)

What is domain engineering?

Domain engineering means each studio models a real business domain — not just a prompt template. The Slide Studio doesn't ask an LLM to "make slides." It models how a world-class creative agency operates: a research team gathers intelligence, a storyteller crafts narrative, a visual director designs each slide uniquely, a copy director writes at the highest professional level, and critics review everything before delivery.

Each agent has a 4,000-7,000 word ULTRA system prompt defining their role profile, frameworks they own, day-to-day responsibilities, output rubric, anti-patterns, mandatory output contract, and self-verification checklist. This is domain engineering — not prompt engineering.

How does the 13-critic quality gate work?

After the creative pipeline completes, every deck enters a quality gate with 13 specialized critics running in parallel. Critics evaluate narrative coherence, design courage (anti-carbon-copy), competitive differentiation, factual accuracy, constitutional compliance, adversarial edge cases, and more. A Synthesis Orchestrator (Opus 4.6) arbitrates — if quality threshold is met, the deck ships. If not, targeted repair revises only the flagged slides (not the whole deck) and re-runs only the failed critics. Up to 2 repair passes ensure every deck meets the quality bar.

How does real-time fact verification work?

The Fact Checker agent uses a ReAct + CRITIC methodology: it extracts up to 24 claims from research data, verifies each against tier-1 sources (academic, government, industry) via web search, and classifies claims as verified, contradicted, unverified, or skipped. This evidence pack is injected into the LLM evaluation — so fact-checking is grounded in real evidence, not training-data hallucination. Based on Gou et al. 2023 CRITIC (arXiv:2305.11738), this reduces hallucination rates by approximately 30%.

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