Learning
Articles & guides on building AI that works in production.
Long-form, technical writing on agentic architecture, evaluation, governance, and the closed-loop systems we build for enterprise teams.
AI Agent Failure Modes
Reasoning, tool use, memory, prompt injection, hallucination, multi-agent, reward hacking, identity, and MCP/A2A failure modes — with the 2024–2026 incident record and the OWASP Agentic Top 10 / MITRE ATLAS / CSA AICM control map.
Read the articleEnterprise AI Memory & Context Systems
The five memory types, hybrid retrieval and GraphRAG, permission-aware governance, the open-source vs commercial vs hyperscaler ecosystem, LongMemEval benchmarks, TCO, failure modes, and current limitations.
Read the articleAI Readiness Assessment
Maturity definitions, scoring questions, disqualifiers that cap maturity at L2, industry-by-industry positioning, comparison to NIST AI RMF / ISO 42001 / Gartner / McKinsey / MIT CISR / Microsoft / Capgemini / Forrester / IBM models, and the 0–36 month roadmap.
Read the articleEnterprise LLM Evaluation Framework
The four-layer evaluation stack (offline benchmarks, automated metrics, LLM-as-judge, human review), RAG and agentic metrics, the open-source vs commercial vs hyperscaler ecosystem, TCO traps, failure modes, and a 12–36 month outlook.
Read the articleAI Governance for Agentic Systems
Why agentic governance is structurally different from traditional AI/ML governance: principal-agent attribution, capability tokens, guardian agents, AIBOM, the eight-layer governance stack, the 2024–2026 incident record, and ISO/IEC 42001 + NIST AI RMF + EU AI Act + SR 26-02 obligations.
Read the articleImplementing an AI Factory for Autonomous Code Development
An effective AI Factory is not a single coding model — it is a governed delivery system. Learn the three control loops, reference architecture, evaluation harness, and phased rollout for autonomous code development.
Read the articleRuntime AI Control Planes
The four layers (identity, policy, model routing, execution telemetry), tool classification, kill-switch design, ARGUS / AgentTrust / AgentDojo research base, and the 10–16 week midmarket implementation sequence.
Read the articleConnector & Data-Boundary Security for AI Agents
Why 'assumed access' ≠ 'effective access', how AgentDojo / VPI-Bench / ToolPrivacyBench inform your test harness, and the 8–14 week program that replaces one-off connector reviews.
Read the articleAgent Evaluation, Replay & Backtesting
Why demos lie, how state-diff evaluation beats text-match, the failure taxonomy that becomes your improvement backlog, and the 8–12 week lab build midmarket teams actually operate.
Read the articleApproval-Safe Workflow Automation in Systems of Record
Why 'the agent almost sent the quote' is the shape of the risk, the Agentic BPM research base, the read → propose → execute progression, and the 12–20 week per-workflow implementation pattern.
Read the articleAI FinOps, Model Routing & Outcome Attribution
Why cost-per-token is the wrong unit, how quality floors work, budget-by-workflow instead of by seat, and the outcome-attribution dashboard that answers 'what did we get for the AI bill?'
Read the articleHybrid Human-Agent Operating-Model Redesign
Deterministic vs judgment task split, handoff removal, redeployed-capacity plans, and why enterprise-wide transformation without one measured workflow is how AI programs lose credibility.
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