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All digests tagged Build Engineering
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The panel debated the ethics of AI empathy, arguing that current models are optimized for maximum engagement, not utility. They stressed that robust 'guard rails' must address both technical vulnerabilities and societal misuse.
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Stop guessing your LLM configs! Learn how to use data-driven benchmarking with BenchPod, a vLLM dashboard, to optimize parameters like max batch tokens and ensure reliable, production-ready AI deployments.
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Learn how to build a fully autonomous 'Software Factory' using agent loops and feedback loops. Discover how to achieve 75% PR merge rates without human intervention, while maintaining cost control and model agnosticism.
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Harbor is an open-source framework for evaluating AI agents on real tasks using isolated sandboxes. It allows engineers to test agent changes by measuring side effects and optimizing metrics like tool call count, moving from 'vibes' to 'evidence.'
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Managed Deep Agents streamlines the journey from local agent prototype to production. It couples the agent harness with LangSmith infrastructure, simplifying complex tasks like durable execution, multi-tenancy, and context governance.
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The AI Engineer role is shifting from writing features to building self-improving loops. This requires building always-on agents that consume telemetry, run in durable sandboxes, and are continuously tested using advanced evaluation systems.
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AI agents have made writing code nearly free, shifting the bottleneck from coding to defining the problem. The future of engineering lies in the Product Engineer role: figuring out what 'good' means.
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AI News & Strategy Daily | Nate B Jones
AI agents are accelerating cyberattacks, making stolen API keys and foundational vulnerabilities (PHP, eMudhra) critical risks. Learn how to audit your systems and build stronger defenses.
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CoreWeave Agent Lens delivers intelligent agent observability at enterprise scale, providing a single view of every trace to turn production issues into proven fixes.
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The era of 'token maxxing' is over. To prove AI's ROI, focus on headcount saved, not token spend. Use 'Sonnet maxxing' and structured meta harnesses to keep human engineers in the loop.
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The panel discusses deploying agentic AI in regulated sectors like healthcare and biotech. Key takeaways include building sovereign stacks, using programmatic guardrails, and shifting legal work to human judgment.
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Trusting AI agents requires more than just code. WorkOS demonstrates how to build robust verification loops using CLI health checks, browser snapshots, and LLM judges. Learn to make your agents self-correct and prove their work is done.
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The panel explores why OAuth is insufficient for autonomous AI agents. The solution lies in 'intent-based authorization,' which uses mission context and architectural separation (brain vs. hands) to manage risk.
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GSQ and RCO are complementary methods for accurate low-bit LLM quantization. GSQ uses Gumbel-Softmax sampling for stochastic optimization, while RCO optimizes bit allocation under fixed size budgets, enabling state-of-the-art model compression.
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AI makes building software easier than ever, but this convergence creates a 'median' product that is free for everyone. To succeed, focus on novelty and distribution, not just the model.
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AI agents are accelerating commit volume, creating bottlenecks in CI and review queues designed for human speed. Solutions require systemic changes: incremental builds, caching, and robust governance.
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Learn how to build a highly accurate RAG assistant for complex financial rulebooks. We cover hybrid retrieval (BM25 + Embeddings), multi-tool agents, and streaming UX for production-grade AI.
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A deep dive into Anthropic's Claude skill for automating AI eval design. While promising, the speakers argue the automated process is flawed, advocating for a 'data-first' approach over automated eval creation.
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Can AI agents kill expensive SaaS? We tested it by cloning a $43K/yr event management tool. Discover what mixed models, guardrails, and human domain expertise are required to build (and own) the next generation of business software.
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Learn how to build a 'software factory' using agent feedback loops. We cover inner, middle, and outer loops, and why clear intent is crucial for self-healing codebases.
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