For over a month, we've mapped the critical components that make RAG and multi-agent workflows stable, scalable, and debuggable.
This post brings all of them together into a single reference you can keep open while building your next agent system.
1. RAG Ingestion Pipeline
A stable RAG system begins with deterministic ingestion:
• consistent text extraction rules
• normalization
• metadata preservation
• chunk boundaries that match question patterns
• version tracking to prevent drift
Common ingestion issues include formatting variance, repeated content, and missing metadata.
2. Retrieval Drift Map
Retrieval drift happens when:
• embeddings change
• document updates shift chunk boundaries
• ingestion procedures evolve
• search parameters vary between runs
Key fix: deterministic ingestion + version locking + hybrid retrieval.
3. Chunking Strategy
Chunking is question-distribution dependent.
Strong strategies include:
• semantic chunking
• heuristic chunking for config-heavy docs
• controlled overlap
• section-level anchoring
The goal is to preserve meaning + minimize boundary artifacts.
4. Debug Checklist
A good debug checklist catches 80% of RAG failure modes:
• malformed chunks
• missing metadata
• incorrect file encodings
• embedding anomalies
• incorrect retrieval scoring
• hallucinated grounding
• schema drift in outputs
5. Eval Pipeline
Evaluating RAG systems requires:
• a grounded QA dataset
• answer matching
• precision/recall per query type
• hallucination grading
• chunk correctness scoring
• retrieval-first vs reasoning-first evaluations
Eval prevents regressions as the system grows.
6. Metric Types
Metrics include:
• retrieval quality
• grounding accuracy
• consistency
• task completion rate
• correction rate
• deviation from expected schema
• latency and cost
Metrics provide observability into behavior over time.
7. JSON Failure Map
Common JSON issues:
• partial structures
• missing required fields
• mixed arrays/objects
• incorrect types
• non-deterministic ordering
JSON verification nodes fix this early.
8. Agent Failure Map
Agent workflows break due to:
• vague tasks
• circular dependencies
• missing verification
• incomplete tool contracts
• drift in intermediate outputs
Failure maps make these issues visible.
9. Tool Contract Template
Every tool should define:
• input schema
• output schema
• validation rules
• structured error modes
A strong tool contract is one of the biggest predictors of agent reliability.
10. Verification Node Mini-Map
Verification nodes perform:
• structure checks
• grounding checks
• fail-forward/fail-safe decisions
• escalation logic
Verification is the backbone of production agents.
11. End-to-End System Overview
Ingestion
↓
Chunking
↓
Embedding + Indexing
↓
Retrieval (hybrid, versioned)
↓
Agent Planning
↓
Tool Calls + Verification Nodes
↓
Eval Loop
↓
Metrics + Drift Detection
↓
Continuous Improvement
This map shows how RAG + agents integrate into a single, maintainable architecture.
Takeaway
RAG + agent systems don’t scale through prompting.
They scale through architecture, contracts, drift control, and verification.
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