AI can enhance decision-making by providing systematic analysis and challenging assumptions, but it cannot replace human judgment for complex choices involving uncertainty and competing values. A stru…
Loop engineering is emerging as a critical discipline for building production-ready AI agents, comparable to data structures in traditional software development. The article outlines a roadmap for mas…
Neo4j's MCP server can now be run locally with Docker, bypassing the need for GitHub Codespaces and their free-tier limits. A docker-compose setup launches both Neo4j and the MCP server, enabling deve…
Anthropic's new Claude Sonnet 5 outperformed its flagship Opus 4.8 in tests conducted by a user, challenging expectations for midsize models. The results highlight the rapid advancement of AI model ca…
A technical guide demonstrates how to build a human-in-the-loop feedback RAG system that captures team corrections and retrieves them into LLM prompts. The pipeline covers modeling corrections as stru…
A new article explains that encoder and decoder models like BERT and GPT share the same underlying architecture, with the key difference being which tokens each model is allowed to attend to during pr…
LangChain's Deep Agents framework provides each AI agent with a filesystem, but developers must choose where that filesystem resides—in memory, on disk, or in durable storage—a decision that significa…
A 2025 randomized controlled trial by METR found that experienced developers using AI tools were about 19% slower, despite expecting a 24% speedup. In contrast, a team at fortiss built the Punctilious…
Anthropic's Claude Agent SDK introduces Hooks, a feature that enforces deterministic guardrails on AI agents by blocking destructive commands, injecting live context, and enabling auditing, without as…
OpenAI expanded Codex on June 2, transforming it from a coding assistant into a knowledge-work platform, signaling the company's next move into AI agents.…
Anthropic paid $1.5 billion to settle a lawsuit over pirated books used to train its AI, and its terms of service prohibit using Claude to build competing AI systems, raising concerns about its stance…
LoRA (Low-Rank Adaptation) and QLoRA have become widely adopted methods for efficiently fine-tuning large language models with a fraction of the parameters, solving the problem of massive GPU requirem…
LangChain revealed that four independent teams building AI coding and research agents — including Claude Code, Manus, and OpenAI Deep Research — all converged on the same underlying architecture witho…
LiveKit released a guide on building a HIPAA-compliant voice agent that keeps protected health information (PHI) within a self-hosted boundary, ensuring data never leaves the organization's infrastruc…
Deep neural networks face training challenges like vanishing gradients and slow convergence. Techniques such as activation functions, Xavier and He weight initialization, and Batch Normalization help …
A new framework reveals that most companies claiming AI transformation have only added tools without changing how work gets done, creating a dangerous gap between hype and real operating-model change.…
A journalist asked seven major AI models what it feels like to be them, and the responses reveal more about how each company wants users to perceive their product than about consciousness.…
Nvidia dominates AI training hardware, but the inference market is wide open as companies like Cerebras, Groq, d-Matrix, Etched, and Taalas challenge Nvidia's GPU-based approach by designing chips opt…
A developer recounts pushing an agent into production that failed after a CRM dropdown change, highlighting the inadequacy of model-level evaluation for agent systems. The article argues that agents m…
Operational readiness for LLM services requires re-deriving classical engineering primitives like alarms, load testing, and retry policies, as defaults tuned for traditional APIs or databases fail for…