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How to scope an AI pilot that survives production
Scope the operating model early: data access, evaluation, escalation, ownership, and release controls.
BlogWhy agentic systems need escalation design
Autonomy without escalation policy turns small errors into operational incidents.
BlogDesigning tool contracts for reliable agent actions
Typed tool interfaces reduce hallucinated actions and make retries safe.
BlogCounterfactual test suites for reasoning workflows
Test scenario variants before launch to detect brittle reasoning logic.
BlogEvidence packets for human approval
Approval flows work when reviewers get concise context, not raw transcripts.
BlogRetrieval freshness SLOs and alerting
Knowledge systems need freshness targets, not just index size metrics.
BlogPermission-aware citation UX patterns
Show evidence safely without leaking restricted content across teams.
BlogTicket triage architectures for AI support teams
Classify, route, and escalate tickets with predictable queue behavior.
BlogSLA escalation graphs for agentic automation
Model SLA risk explicitly and trigger intervention before breaches happen.
BlogModel routing policies for cost and latency control
Route tasks by complexity and risk to balance quality, latency, and budget.
BlogObservability signals that matter for AI systems
Focus on decision quality and escalation behavior, not token counts alone.
BlogRelease gates for prompt and model changes
Treat prompt and model updates like code changes with explicit approvals.
BlogOperating cadences for AI adoption teams
Weekly rituals convert experimentation into accountable delivery.
BlogHandoff patterns from build teams to client operators
Operational ownership transfer should be planned as a product milestone.
BlogThe economics of production AI programs
Estimate value with baseline volume, cycle time, exception rate, adoption curve, and operating cost instead of generic AI claims.
BlogBenchmarks that matter after AI go-live
Track resolution share, reviewer load, exception recovery, unit cost, latency, and quality deltas once the system is live.
KennisbankProduction AI readiness checklist
Readiness checks for data, approvals, observability, and ownership.
KennisbankRetrieval quality basics
Core quality dimensions for source-grounded answer systems.
KennisbankAgent authority boundary template
A practical template for defining what an agent can and cannot do.
KennisbankEscalation packet reference
Recommended fields for high-signal escalation handoffs.
KennisbankCounterfactual test design guide
How to create case variants that expose brittle reasoning patterns.
KennisbankSLA risk routing patterns
Patterns for routing queues based on SLA risk and business impact.
KennisbankTicket queue observability metrics
Queue metrics that matter for AI-supported service operations.
KennisbankModel routing policy template
Define model selection policy by task complexity and risk class.
KennisbankAI incident postmortem structure
A postmortem structure tailored for model and workflow incidents.
KennisbankOperating cadence checklist
Weekly and monthly rituals for keeping AI delivery accountable.
KennisbankClient handoff readiness scorecard
Scorecard for transitioning AI operations to client-side ownership.
KennisbankContent ingestion runbook
Runbook for ingestion jobs, freshness validation, and failure recovery.
KennisbankAI ROI model worksheet
Worksheet for estimating automation value from volume, cycle time, labor mix, quality lift, and operating cost.
KennisbankBenchmark instrumentation checklist
Checklist for proving production AI value through measurable throughput, quality, cost, and risk signals.
TrajectenAgent design
Planning loops, tool contracts, stop conditions, and human supervision for autonomous workflows.
TrajectenReasoning systems
Structured prompting, verifier chains, and decision quality checks for high-stakes outputs.
TrajectenRetrieval platforms
Knowledge ingestion, indexing, permissions, and citation UX for source-grounded AI.
TrajectenProcess automation
Ticketing, queues, escalation routing, SLA orchestration, and workflow observability.
TrajectenPlatform operations
Routing models, cost controls, telemetry, release governance, and incident response patterns.
TrajectenChange management
Adoption playbooks, operating cadences, enablement artifacts, and team handoff routines.
TrajectenAI economics
ROI baselines, adoption economics, cost curves, and benchmark instrumentation for production AI programs.
PlaybooksPilot to production
A staged path from prototype workflow to governed production service.
PlaybooksRetrieval hardening
Improve source quality, freshness, and citation confidence before broad rollout.
PlaybooksSupport automation rollout
Deploy ticket triage and drafting with risk controls and escalation policies.
PlaybooksGovernance by design
Embed approval and release controls directly in delivery workflow.
PlaybooksValue realization operating model
A practical sequence for turning AI delivery into measurable economic outcomes.