Parallel Agent Execution
Concurrently executes independent agents or pipeline steps using async orchestration to reduce end-to-end latency without compromising state integrity.
Typed Execution Context
Replaces implicit dictionary-based state passing with a structured, versioned, and strongly typed object to ensure contract safety across pipeline steps.
Active-Week Selective Intelligence
The merge limits full intelligence generation to active or explicitly requested weeks and uses deterministic fallback for non-active historical weeks.
Cache-Aside Week Intelligence Builder
The merge introduces a cache-aside path for week intelligence so dormant weeks are materialized only when the UI requests them.
Deterministic Brief Degradation
The merge introduces deterministic brief fallback when there is insufficient comparison context or intelligence is intentionally disabled for the week.
DTO-Backed UI Contract
The merge formalizes a response DTO so the UI reads a controlled output contract rather than arbitrary orchestration state.
Dirty-Check Gated Lazy Recompute
The merge adds a deterministic dirtiness guard so week intelligence is recomputed only when stable training signals change or on-demand rebuild is forced.
Intelligence Snapshot Projection Boundary
The merge introduces a distinct derived model that aggregates agent and service outputs into a stable UI-facing intelligence snapshot.
Language-Keyed Intelligence Cache
The merge uses `(week_start, language)` as the intelligence cache key so multilingual outputs are reused safely.
Persisted Chart Artifact Pipeline
The merge converts visualization outputs into serialized image artefacts that can be persisted, reloaded, and rendered without live figure state.
Scope-Aware Visualization Context
The merge adds explicit visualization scope so agents and rendering logic know whether they are producing week-scoped or full-run charts.
Snapshot ID-Based Partial Enrichment
The merge preserves weekly snapshot identity so later intelligence and chart enrichment can target a stable persisted record.
Week-Scoped Repository Reconstruction
The merge reconstructs intelligence and visualization contexts from repository-backed week state instead of relying only on newly uploaded runs.
Pipeline Intelligence Snapshot
Produce a canonical intelligence artifact at the end of a pipeline to consolidate distributed agent outputs into a single system state.
Architecture Workflow Loop
Embed a continuous architecture audit and refactor loop inside the delivery workflow to prevent structural drift during rapid experimentation.
Context Injection
Collect relevant state from system stores and inject it into prompts as structured context to enable data-aware responses without fine-tuning.
Deterministic Guardrail
Use a non-LLM, rule-based agent to enforce safety constraints with predictable, explainable outcomes.
Auto-Injection of History
When current session state is empty, automatically backfill chat context with recent stored history to preserve continuity.
Graceful Fallback
Wrap LLM calls with error handling that returns safe defaults so the system stays usable when generation fails.
Dual-Path Routing
Classify user intent into a small set of routes and dispatch to specialized handlers to optimize responses for different request types.
Heuristic-Driven Arbitration
Use a control point to adjust LLM-produced outputs based on deterministic safety signals from other components.
Implicit Tool State Mutation
Accumulate complex outputs by having a tool call mutate agent state during generation, then read the final result from that state.
Orchestrator-Managed Pipeline
Use a central orchestrator to run a fixed, dependency-ordered sequence of agents so analysis steps remain consistent and traceable.
Prompt-as-Code Separation
Store prompts outside agent code and load them at runtime to improve maintainability and enable language variants.
Structured Output via Schema
Define a formal schema for agent outputs and validate LLM responses against it to keep results machine-readable and reliable.
LLM Provider Abstraction Boundary
Introduce a provider-agnostic interface so agents can switch LLM backends without rewriting orchestration logic.
Prompt–Schema Contracts as First-Class Architecture
Treat prompts, schemas, and structure locks as architectural contracts that constrain outputs and reduce drift.
Stabilise the Core Loop Before Adding Modalities
Defer multimodal features until the text-based agent loop and contracts are stable, to avoid compounding uncertainty.
Derived Documentation from Evidence
Treat docs as derived state by regenerating AS_BUILT and DELTA_BACKLOG from executable evidence to prevent drift.