Expert insights on enterprise integration, AI, and business process management from the KONDEVS team.
Prototyping AI agents is the easy part. Keeping them running reliably in production? That's where most teams hit a wall. We've seen this pattern play out across cloud native environments: a team builds an impressive AI agent proof-of-concept, leadership gets excited, and then the hard questions star
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Enterprise IT leaders face an unprecedented challenge: managing six overlapping innovation waves simultaneously instead of sequential updates. The organizations that thrive won't be those optimizing one area at a time—they'll be the ones intentionally adapting to parallel technology shifts all at on
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AI coding agents have evolved dramatically in just 12 months—from experimental "vibe coding" to autonomous swarms. But with greater capability comes greater cost and security risks. Here's what you need to understand about the current state of the game. At QCon London, Birgitta Böckeler from Thought
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AI isn’t failing — but many enterprises are failing to turn investment into measurable ROI. Across industries, organizations have poured billions into artificial intelligence, expecting transformative gains. Yet, for most, the return on AI investment (ROAI) remains elusive. Why? The real issue isn’t
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Would you trust an AI to run key workflows without human supervision? Across industries, the drive to harness autonomous AI is gathering speed in 2024. From construction sites to office desks, these agentic tools promise to remove repetitive, tedious work—allowing teams to focus on higher-value task
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Is your infrastructure AI-ready, or are invisible bottlenecks holding your automation back? As AI-driven development transforms how we work, real progress is being stifled—not by code, but by everything that happens after you hit 'git push.' Manual coordination, scattered policies, and tribal knowle
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AI is often seen as a disruptor, but there’s a growing consensus among industry leaders that it’s just as much a job creator—particularly for professionals who can design, implement, and sustain the underlying architecture. As highlighted by Jon McNeill, the increasing adoption of AI depends on robu
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When we talk about AI risks, most leaders think of three main challenges: opacity (not knowing how decisions are made), complacency (trusting AI too much), and accuracy (AI gets things wrong). But a new study highlights a fourth—and potentially more subtle—problem: “persuasion bombing.” Researchers
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AI coding assistants are incredibly powerful, but too often they default to generic, out-of-context patterns pulled from their vast training data. The result? Developers find themselves stuck in a cycle—generate code, realize it doesn’t fit, edit and repeat. Over time, this “Frustration Loop” can ac
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Ever wondered what keeps industrial processes running smoothly—and safely—behind the scenes? The answer lies in expertly engineered process piping systems, guided by stringent standards like those from ASME. ### Introduction Process piping is the unsung backbone of modern industry, ensuring the safe
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The latest DORA report on AI-assisted software development highlights a powerful truth: AI doesn’t automatically boost software delivery performance—instead, it amplifies what’s already there. For high-performing engineering teams, AI is a force multiplier, accelerating productivity and innovation.
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Digital transformation isn’t just a technology journey—it’s a human one, governed by the unique “physics” of people, organizations, and partners sharing the same orbit. While strategy can be updated and partners changed, talent is the true force holding the system together—or quietly pulling it apar
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