Coreledger Tech

Kelvin Musodza
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From reimagining fixed-income markets to engineering the next generation of AI-powered developer tools, Coreledger Tech explores the intersection of technology, automation, and human-AI collaboration. Hosted by the Coreledger team, each episode dives into real-world projects, lessons learned, and the practical side of building systems that scale, from our early fintech innovations to our current work in context engineering. Whether you’re a developer, entrepreneur, or tech enthusiast, join us for insights, experiments, and conversations that bridge code, creativity, and impact.

  1. AI’s Hidden Costs: Mastering Context to Avoid Bill Shock and Risky Hallucinations

    9月10日

    AI’s Hidden Costs: Mastering Context to Avoid Bill Shock and Risky Hallucinations

    When AI forgets what matters, it can cost you everything. From the developer blindsided by a $10,000 token bill, to the infamous “Replit Incident” where an AI wiped over 1,200 production records in seconds, these aren’t edge cases, they’re warnings. Bigger context windows were supposed to fix the problem, but instead, models like GPT-5 still drift, compress away critical details, and send costs spiraling. In this episode, we expose the hidden economics of AI’s “memory,” why more isn’t always better, and how ⁠Coreledger’s Contextus⁠ platform rewrites the rules, delivering scoped, risk-aware context that slashes costs and keeps AI on task.

    15 分鐘
  2. Context Engineering: AI’s Hidden Challenge

    9月9日

    Context Engineering: AI’s Hidden Challenge

    The bigger the AI’s “memory,” the bigger the risks, hallucinations, bad decisions, and bills that break budgets. This quick explainer unpacks why more context isn’t always better, and how Coreledger’s ⁠Contextus platform⁠ turns chaos into clarity, feeding your AI only what’s relevant, cutting costs by up to 40%, and keeping it from going off the rails.

    7 分鐘
  3. Beyond Prompting: Why Context Engineering Is the Real Key to AI Performance

    9月8日

    Beyond Prompting: Why Context Engineering Is the Real Key to AI Performance

    It’s not the prompt, it’s the ⁠context⁠. Behind every hallucination, misstep, or spiraling AI bill is a deeper problem: models drowning in irrelevant information. In this episode, we go inside real user stories, from the developer whose AI assistant forgot a critical deployment step, to the analyst who watched costs double overnight, showing how context overload sabotages accuracy and drives costs sky-high. Then, we reveal how context engineering flips the script, turning messy inputs into lean, relevant, high-impact context that lets AI work smarter, not harder.

    7 分鐘
  4. The Explainer: Context Engineering

    9月5日 · 附贈內容

    The Explainer: Context Engineering

    Ever wonder why your AI forgets instructions, merges steps, or blows through budget? The answer isn’t just in prompting, it’s in the context you feed it. This quick explainer shows how ⁠context engineering⁠ solves real user pain points, from runaway costs to accuracy breakdowns, with smarter, leaner inputs that keep models on task.

    7 分鐘
  5. Decoding Big Tech’s AI Gambit: The $10K Developer Dilemma

    9月4日

    Decoding Big Tech’s AI Gambit: The $10K Developer Dilemma

    The AI gold rush is here, but for enterprise teams, the price tag is starting to bite. Developers are quietly racking up $10,000+ a month in token spend, as agentic workflows and sprawling context windows drive costs into uncharted territory. In this episode, we pull back the curtain on Big Tech’s market bets, the hidden economics of LLM adoption, and why smarter context, not bigger models, may decide who wins.

    20 分鐘
  6. The New Reality for AI: Why Developers Are Burning $10K a Month

    9月3日 · 附贈內容

    The New Reality for AI: Why Developers Are Burning $10K a Month

    Every token has a price. As AI models grow bigger and more “capable,” developer bills are exploding, sometimes topping $10,000 a month per seat. In this short breakdown, we expose the hidden cost of oversized context windows, why “just make it bigger” isn’t the answer, and how ⁠context engineering⁠ can slash spend without sacrificing quality.

    8 分鐘

  7. 8月21日

    Coreledger’s Last Deal on Wall Street: The Gift, the Pivot, and the Future of Human–AI Collaboration

    We built for the heartbeat of Wall Street/Bay Street, matching engines that moved orders in microseconds, AI models that spotted settlement failures before they happened, and pipelines tuned for the chaos of bond markets. Then, the rules changed. In this episode, we tell the story of why we walked away from finance’s frontlines, why we chose to give our technology away for free, and how that gift clears the runway for our boldest venture yet; Contextus, a platform designed to help humans and AI think in sync. This is more than a pivot. It’s the end of one era, and the deliberate beginning of another. Season Finale!!

    17 分鐘

  8. 8月20日

    Coreledger’s Gift to Wall Street: Closing One Chapter, Opening Another

    We built for the fast lane of Wall Street, AI models predicting settlement risks, a fast matching engine fine-tuned for bonds, and tools to cut through the chaos of trading desks. Now, we’re handing them over. Free. Open source. Why? Because the future we’re chasing is bigger than finance. Coreledger is pivoting from market-making machines to building platforms that help humans and AI think together. This is our gift to the street, and our first step into a new era with Contextus. Season Finale!

    6 分鐘
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簡介

From reimagining fixed-income markets to engineering the next generation of AI-powered developer tools, Coreledger Tech explores the intersection of technology, automation, and human-AI collaboration. Hosted by the Coreledger team, each episode dives into real-world projects, lessons learned, and the practical side of building systems that scale, from our early fintech innovations to our current work in context engineering. Whether you’re a developer, entrepreneur, or tech enthusiast, join us for insights, experiments, and conversations that bridge code, creativity, and impact.

資訊

  • 創作者
    Kelvin Musodza
  • 活躍年代
    2025年
  • 集數
    16
  • 年齡分級
    兒少適宜
  • 版權
    © Kelvin Musodza
  • 節目網站
    Coreledger Tech