Tag: context engineering

  • Beyond the ‘AI-Centric Imperative’: The Orchestration-Native Enterprise

    Beyond the ‘AI-Centric Imperative’: The Orchestration-Native Enterprise

    ← From AI-Centric to Orchestration-Native | PART 8 / 8 If you’ve stayed with this series, you’ve traveled a fair distance: Let’s end by zooming out. There’s a growing consensus – from McKinsey and others – that the next era of software will be AI-centric: agents, copilots, and embedded intelligence reshaping products and workflows. That’s true,…

  • Proof Under Pressure: How Orchestration Handles Real-World Disruption

    Proof Under Pressure: How Orchestration Handles Real-World Disruption

    ← From AI-Centric to Orchestration-Native | PART 7 / 8 It’s one thing to talk about architecture, metrics, and roadmaps in calm conditions. It’s another thing to ask a harder, more honest question: What happens when the world really goes sideways? That’s the real test of any ‘AI-centric’ or ‘orchestration-native’ vision. In this article, we’ll…

  • What Changes When You Become Orchestration-Native

    What Changes When You Become Orchestration-Native

    ← From AI-Centric to Orchestration-Native | PART 6 / 8 Up to this point, we’ve stayed mostly in the world of architecture, economics, and metrics: But technology is only half the story. The real test of an orchestration-native enterprise is what it does to the day-to-day reality of work: This article is about that human side:…

  • Adoption Without Disruption: A Practical Path to Orchestration

    Adoption Without Disruption: A Practical Path to Orchestration

    ← From AI-Centric to Orchestration-Native | PART 5 / 8 By now, we’ve painted a pretty ambitious picture: If you’re an executive or transformation leader, you might be nodding along – and still thinking: “This all sounds great. But how do we actually get there without a giant, risky transformation project?” That concern is rational.…

  • From Dashboards to Decisions: New Metrics for an Orchestrated Enterprise

    From Dashboards to Decisions: New Metrics for an Orchestrated Enterprise

    ← From AI-Centric to Orchestration-Native | PART 4 / 8 If you’ve been following this series, we’ve made three moves so far: That naturally raises a harder question: If we change how decisions are made, how should we measure whether the system is actually getting better? Most enterprises are still instrumented for an older era…

  • The Economics of Intelligence: How to Stop AI from Becoming a Cost Spike

    The Economics of Intelligence: How to Stop AI from Becoming a Cost Spike

    ← From AI-Centric to Orchestration-Native | PART 3 / 8 In the first two articles, we made a simple argument: That all sounds promising. But if you’re a CFO, COO, or P&L owner, there’s another question sitting underneath all of this: Will this actually make us more efficient – or just more expensive? Recent analysis…

  • What an Orchestration-Native System Actually Looks Like (in Plain Language)

    What an Orchestration-Native System Actually Looks Like (in Plain Language)

    ← From AI-Centric to Orchestration-Native | PART 2 / 8 In the first article, we argued that “AI-centric” is only a half-step. Adding copilots and assistants into individual tools is helpful, but it doesn’t solve the hardest problem large enterprises face: coordination. Sales, supply, logistics, finance, and operations all get “smarter” – but who keeps them…

  • i5 Context Engineering

    i5 Context Engineering

    i5’s dynamic system design turns context into computation. In i5, context engineering is the practice of embedding dynamic, structured, and evolving information into the simulation engine to generate richer, more adaptive scenarios that respond to real-world shifts. Unlike narrow prompt tuning, i5 context engineering spans: In i5, everything starts from “context.” Traditional systems WAIT for…