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Dev.to

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16:06
2026-09-21
dev.to
ai-agents

Scoring A2A Agent Skills with System One (Jev) in .NET

A developer has built a pre-LLM gating layer in .NET that scores individual A2A agent skills against a user request using TypeSafe's System One (Jev) classification API, exposing only the winning skil…

16:05
2026-09-21
dev.to
ai-tools

The Frontend Role Is Changing — And AI Is Raising the Bar

A developer with a graphic design background argues that the frontend role has expanded well beyond interface building into architecture, design systems, performance, and deployment, with frameworks l…

15:35
2026-09-21
dev.to
ai-chips

NPU, DPU, QPU: Which One Actually Belongs in Your Stack

A developer's technical breakdown argues that NPUs and DPUs are already earning their keep in production stacks, while QPUs remain largely a research tool. The piece walks through ONNX Runtime inferen…

15:04
2026-09-21
dev.to
ai-agents

Harnessing AI: Essential Skills to Master in 2026

A roadmap for 2026 argues that the AI skill set has shifted from basic prompt writing toward agentic architectures, reasoning models, and multimodal integration. It recommends developers and product t…

15:03
2026-09-21
dev.to
ai-agents

How I Cut GPT-6 Astra Usage by ~95% Without Losing Quality

A developer built an open-source Codex skill, Astra Flash Orchestrator, that routes high-volume coding work to DeepSeek V4.1 Flash while reserving the pricier Astra model for planning, architecture, a…

15:02
2026-09-21
dev.to
artificial-intelligence

Why Human-in-the-Loop AI Makes Sense in Freight Dispatch

A developer argues that freight dispatch is better served by human-in-the-loop AI than full automation, since dispatch decisions combine deterministic calculations with contextual judgment. The propos…

15:00
2026-09-21
dev.to
ai-tools

We Measured the 200x Claim, and Got It Wrong Twice First

A developer benchmarked TypeSafe AI's Jev model against a mid-size open model on a real transactional email classification workload and initially produced two wrong results, including a 100% detection…

14:19
2026-09-21
dev.to
ai-agents

How to read a coding-agent benchmark without getting sold

A nine-author study led by Fan et al. held the underlying model and execution loop fixed while varying three coding-agent harness components — planning, action space, and context management — across 1…

14:12
2026-09-21
dev.to
ai-agents

The Four Layers of AI Engineering: From Prompts to Loops

A developer outlined a four-layer framework for AI engineering — prompt, context, harness, and loop — using a code-review agent as a running example. The writeup argues that prompt engineering is only…

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