AI governance

Tier‑0 Knowledge Layer for Agentic Engineering

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Playbook
agentic engineeringproduction AI agentsAI reliability

You move from impressive pilots to audit-survivable, production-grade agentic systems with measurable “done,” enforceable controls, and a tested kill-switch and recovery plan. TL;DR Convert every agent request into 8–12 word, binary pass/fail acceptance criteria before building anything. Classify embeddings/KG/telemetry as Tier‑0 and gate production on immutable logs, SoD, segmentation, and restore drills. Decouple control/data/model/experience planes … Read more

Agentic Engineering: Sovereign AI Multi-Geo Residency

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Playbook
multi-agent orchestrationenterprise AI agentsproduction AI agents

You move from “we stood up an agent” to “we can prove it’s safe, compliant, and improving”—with enforceable controls, testable acceptance, and audit-ready telemetry. TL;DR Convert stakeholder intent into 8–12 word, binary pass/fail criteria and wire them into automated evals. Embed governance in the prompt/context + tool pipeline (PII detection, masking, policy checks, structured telemetry) … Read more

Agentic Engineering: Policy-First LLM Routing Manual

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Playbook
AI reliabilityAI governanceagentic engineering

You move from “prompt-based trust” to provable, auditable enforcement where every LLM/tool action is policy-decided, traceable, and fail-closed for regulated data. TL;DR Decompose each use case into 8–12 word binary acceptance criteria and wire them into eval gates. Put a deterministic pre-call policy gate in front of every LLM/provider call and every tool invocation—no exceptions. … Read more

Minimum Viable AgentOps for Agentic Engineering SLAs

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Playbook
token budgetingenterprise AI agentsproduction AI agents

You’ll ship agentic workflows that are economically repeatable and operationally governable—without defaulting to expensive autonomy, unbounded tool access, or prompt-only “safety.” TL;DR Implement dual-mode execution: use a constrained single-shot path for low-risk tasks and reserve an autonomous harness for multi-step work. Route by risk (blast radius + tool scope + change type) so cheaper models … Read more

Agentic Engineering: AI Chain-of-Authority Model

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Playbook
AI reliabilitymulti-agent orchestrationAI agents

You move agentic workflows into production with provable accountability—who authorized what, what data was touched, and what side effects occurred—without slowing the business into approval gridlock. TL;DR Implement “No Delegator, No Action,” require scope IDs on every tool call, and tier actions by blast radius with approvals. It works because enforcement happens at the tool … Read more

What Is Agentic Engineering? The Discipline Enterprises Need in 2026

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Field Manual
AI observabilitymulti-agent orchestrationAI agents

Adopt agentic engineering as a discipline and your organization moves from demo-grade agents to production-grade systems with named decision boundaries across reasoning, execution, governance, operations, and economics. TL;DR Agentic engineering is the discipline of running AI agents as production systems — bounded autonomy, named decision boundaries, runtime governance. Once a system can plan, call tools, … Read more

Agentic Engineering: Build vs Buy Knowledge Layer Rubric

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Field Manual
AI reliabilityAI observabilityAI agents

You can ship agentic AI into production with predictable unit economics, audit-ready governance, and the ability to swap models/vendors without rewriting pipelines. TL;DR Adopt a Decoupled Planes architecture (Control/Data/Model/Experience) so models can change without moving data or reworking governance. Implement Hybrid Retrieval (metadata gate → vectors → rerank → full logging) to improve precision while … Read more

Composable AI Data Governance for Agentic Engineering

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Field Manual
enterprise AI agentsAI governanceagentic engineering

Adopt this model and your teams can ship agentic systems faster by placing controls at the right decision boundaries instead of forcing every use case through the same manual governance path. TL;DR Use a composable control stack: governed zones for structural segregation, policy-bound data products for reusable AI inputs, and runtime enforcement at retrieval, memory, … Read more

Production AI Agent Architecture Field Manual

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Field Manual
AgentOpstoken budgetingAI reliability

Teams that adopt this architecture move from opaque prompt experiments to production-grade workflows — with explicit decision boundaries, bounded autonomy, and measurable rollback paths. The patterns below echo Anthropic’s Building Effective Agents (Dec 2024), Google’s SRE Workbook practices on bounded systems and failure budgets, and a hard operational reality: most agent failures in production are … Read more

Composable AI Data Governance for Agentic Engineering

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Field Manual
AI complianceAI agentsAI reliability

Readers will be able to assign the right governance pattern to each agentic AI use case, place controls at the correct decision boundary, and reduce compliance risk without defaulting to a one-pattern-fits-all architecture. TL;DR Classify every AI use case by risk before design approval, then select a primary governance pattern using the default rule: high-risk … Read more