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Chad Collins

817 articles published

How to Use Copilot Agents and New IDE Integrations to Automate Dev Workflows and Measure ROI

AI Coding & Developer Tools5 days ago59Views0Likes0Comments
What Happened GitHub and adjacent IDE vendors released several updates that change how teams automate developer workflows, perform code review, and measure agent usage: Copilot usage metrics now include activity for the dedicated VS Code Agents window with new aggregate and user-level fields (daily_active_vscode_agent_users, totals_by_vscode_agent, used_vscode_agent, per-user totals), subject to policy and role…

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How Recent AI Research Should Reframe Production Roadmaps — Practical Takeaways for Engineering and Product Leaders

AI Research & Papers5 days ago51Views0Likes0Comments
What Happened A large batch of research from labs and arXiv covers practical advances across agent architecture, robustness and calibration, domain-specific applications (medical imaging, ultrasound guidance, speech), multilingual systems, and security/forensics. Highlights include: Device-to-market success: AI‑GUIDE couples custom AI with handheld ultrasound for pre‑hospital vascular access and reached transfer to a startup after…

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Retrieval, RAG & Search — September 11, 2026

Retrieval, RAG & Search5 days ago104Views0Likes0Comments
What Happened Recent engineering work shows how an agentic optimizer can safely and repeatedly tune a search backend (Elasticsearch) when paired with a disciplined harness: treat agent proposals as noisy, verify wins with staged benchmarks, and enforce strict guardrails and ownership before production changes. The approach uses a proposer–verifier–referee loop, exploration/exploitation/benchmark task types, machine‑readable verdicts,…

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Upgrade-Proofing Your Data Science Stack: What scikit-learn 1.9.1 and Python 3.15 Support Mean for Python/R Ecosystems

Data Science, Python & R5 days ago51Views0Likes0Comments
What Happened scikit-learn 1.9.1 was released with several bug fixes and is the first scikit-learn release to add official support for Python 3.15. The release is available via pip and conda-forge for easy upgrades and testing in existing environments [1]. Install via pip: pip install -U scikit-learn [1]. Install via conda-forge:…

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Build Reliable, Secure Agentic AI: Patterns for Plugins, Multi‑Agent Orchestration and Production Observability

Agents & Agentic AI5 days ago52Views0Likes0Comments
What Happened Agent frameworks and agentic tooling continue maturing around three practical needs: safe tool/plugin integration, scalable multi‑agent orchestration, and production observability/operational controls. Recent releases emphasize reproducible plugin evaluation, richer session modes (headless/cloud/IDE), explicit concurrency and timeout controls, and many correctness fixes for state and resume semantics. Claude Code’s v2.1.269 release is a concrete example:…

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Upgrade to JupyterHub 6.0: lower operational risk with Prometheus metrics, finer permissions and unix‑socket support

AI Application Development5 days ago35Views0Likes0Comments
What Happened JupyterHub 6.0 was released with several operational and API changes intended for production deployments. Key items: Requires Python 3.10 for the hub process and admin tooling; operators must update images and CI accordingly [1]. Small database schema upgrade — back up your database before upgrading (breaking changes expected to…

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Cut AI Inference Cost and Silent Failures: Benchmark Models by Outcome and Instrument Agent Runtimes

AI Infrastructure, GPUs & Deployment5 days ago59Views0Likes0Comments
What Happened Three practical developments converge on how organizations build and run production AI today. AWS published a production‑grade approach for instrumenting and diagnosing swarm‑style multi‑agent systems using Amazon Bedrock AgentCore plus two monitoring layers: AgentCore Evaluations (LLM‑as‑judge continuous scoring) and an AWS DevOps Agent that builds topology graphs and returns high‑confidence remediation…

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How Recent Open-Source Inference Tooling (llama.cpp & vLLM) Lowers Cost and Increases Control for Production AI

Open-Source Models & Communities5 days ago46Views0Likes0Comments
What Happened Over the last development cycle the open-source inference ecosystem saw concentrated improvements across low‑level kernels, cross‑platform builds, and serving primitives that materially affect production deployments: llama.cpp/ggml received a substantial fusion refactor and protection modes to unify fusion logic, add per‑fusion diagnostics and a regression baseline, and fix a fusion bug that…

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How Sparse Recurrent AI Architectures Could Reduce LLM Reasoning Costs in Enterprise Platforms

Research5 days ago40Views0Likes0Comments
What Happened Pathway developed BDH, or Dragon Hatchling, a post-transformer architecture designed to reason in latent space rather than by generating long textual chains of thought. Instead of activating a dense transformer stack across large context windows, BDH uses a sparse graph of neuron-like “particles” with local persistent state, Hebbian-style attention, and recurrent computation where…

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AI Adoption Is Moving From Models to Managed Workflows, Privacy Controls and Security Architecture

Industry News5 days ago34Views0Likes0Comments
What Happened Several technology updates over the last day point to the same operating reality for businesses: AI, cloud platforms, developer tools, identity systems and consumer interfaces are converging, but the risk surface is expanding just as quickly. AI assistants are creating new privacy failures. Meta said it will change AI chatbot suggestion…

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