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Jeremy Petersen
Dan Shapiro (Glowforge) has a crisp maturity model for AI-assisted software development—“from Spicy Autocomplete to the Dark Factory.” https://lnkd.in/gg8trzTs His (zero-indexed) levels: Level 0: Spicy Autocomplete Level 1: Coding Intern Level 2: Junior Developer Level 3: Developer Level 4: Engineering Team Level 5: Dark Software Factory My comment: Most teams are chasing the Level 2 “pairing” productivity bump. But we need to think bigger. The real competitive moat shows up in Levels 3–4: evals/tests, policy guardrails, traceability, and a review model that doesn’t turn humans into the bottleneck. Crazy times!
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Payal Jhamta
From Hype to Impact: Designing AI for Measurable Outcomes AI without measurement is just hype. In enterprise settings, what matters is translating potential into real business metrics - efficiency, revenue, satisfaction, retention. CrossML Pvt Ltd, we don’t build AI for impressing. We build AI for impact. Here’s how we make measurable outcomes part of the engineering DNA: 🔹 Define Clear Objectives First Every AI project starts with specific, quantifiable goals: reduce average resolution time by X%, boost conversions by Y%, decrease errors by Z%. Without those, you can’t tell if your AI is working or just consuming resources. 🔹 Start With MVPs That Measure We deliver Minimum Viable AI prototypes - small, focused, measurable. We test early, collect data, validate hypotheses. So we fail fast or succeed early, but always with learnings in hand. 🔹 Build & Monitor Everything Every model, pipeline, user interaction is tracked: response times, accuracy, latency, user satisfaction, drift, error rates. We build dashboards to see where things are going off track, so adjustments are data-driven. 🔹 Feedback Loops + Human in the Loop Real-world AI doesn't live in isolation. We embed human oversight for edge cases and high-impact decisions. We collect feedback from users, fix misfires, and continuously refine. 🔹 Governance, Reliability & Compliance from Ground Up Bias, privacy, security, explainability are not afterthoughts. We integrate these from Day One so uncertainty and risk don’t erode trust or performance. 🔹 Scale What Delivers, Adapt What Doesn’t We don’t throw everything into production. We replicate and scale successful pilots. For underperforming features, we iterate or pivot, keeping resource use efficient while optimizing for business impact. If you’re a CTO, VP Engineering, or AI Lead navigating between the excitement of AI possibilities and the need for real outcomes, you can connect with us to build an effective AI solution. Building AI is easy; building AI that moves the needle is where the challenge (and reward) lies. #EnterpriseAI #ROI #AIOutcomes #CrossML #DataDriven #AIEngineering #PerformanceMetrics
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Virendra Singh
Jensen Huang just called OpenClaw "the most important release of software, probably ever." When it comes from the man who defined the GPU era, then people listen ( after discounting the vested interest obviously :) While people focus on his quote, we should understand that the real story is adoption speed of Openclaw: it took 3 weeks to reach Linux's 30-year milestone. That's not growth, but an explosion. OpenClaw isn't a tool. It's the operating system for agents that do work. When NVIDIA's CEO calls a project THE thing, every CTO adds it to their roadmap. ByteDance, Alibaba, Tencent are integrating OpenClaw —not for GitHub stars, but because they're terrified of falling behind. On March 6, 2026, nearly 1,000 people queued outside Tencent's Shenzhen headquarters for free, on-the-spot installation of OpenClaw AI. That shows the desperation to be in-step with the technology. In many orgs, OpenClaw is already in production. JPMorgan handles fraud detection with it, Walmart wired it into loan approvals. These are real systems with real money and stakes. The Agenci AI market is fragmented: LangGraph, CrewAI, AutoGen, LangChain, Semantic Kernel, smolagents, PydanticAI. Seven frameworks fighting. But the outcome is obvious. Whoever controls the execution layer controls the decade ahead. The builders who shipped agents in 2024 when LLMs were not ready for it, they already know the significance of these events in 2026 . Which side of this are you on?
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