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3,045 results • Page 2 of 254

Driving the Agent Quality Flywheel from Your Coding Agent
ProgrammingNews

Driving the Agent Quality Flywheel from Your Coding Agent

Building AI agents often leaves developers uncertain if prompt tweaks to fix single errors will accidentally cause widespread regressions in production. To bridge this gap, Google has introduced a new developer skill for coding agents that automates a five-stage evaluation flywheel: preparing data, running inference, grading with adaptive AutoRaters, analyzing failure clusters, and executing targeted optimizations. Running continuously against production traffic or on-demand via synthetic scenarios, this tool allows developers to describe testing goals in plain language while an independent evaluation service safely validates and counts actual performance improvements.

Google Developers·July 24, 2026·1 min read
Build reliable multi-agent applications with ADK Go 2.0. Discover our new graph-based workflow engine, built-in human-in-the-loop, and dynamic orchestration
TechnologyRelease

Build reliable multi-agent applications with ADK Go 2.0. Discover our new graph-based workflow engine, built-in human-in-the-loop, and dynamic orchestration

The Agent Development Kit (ADK) for Go 2.0 has been released, introducing a first-class, graph-based workflow engine to help developers compose complex, multi-agent applications. This update adds built-in primitives for human-in-the-loop (HITL) orchestration, dynamic execution using plain Go code, and automated resilience features like exponential backoff retries. By unifying the execution model, both single-agent applications and intricate graphs now run on the same runtime, simplifying telemetry and state persistence.

Google Developers·July 24, 2026·1 min read
Build Cross-Language Multi-Agent Team with Google’s Agent Development Kit and A2A
TechnologyNews

Build Cross-Language Multi-Agent Team with Google’s Agent Development Kit and A2A

How a Python agent and a Go agent collaborate on contract compliance using the Agent2Agent protocolY...

Google Developers·July 24, 2026·1 min read
Systems Engineering Playbook: Optimizing Qwen 3.5-397B MoE on Ironwood (TPU7x)
TechnologyRelease

Systems Engineering Playbook: Optimizing Qwen 3.5-397B MoE on Ironwood (TPU7x)

To serve the 397B-parameter Qwen 3.5 Mixture-of-Experts (MoE) model on Ironwood TPUs, engineers developed a modular JAX/Pallas optimization stack that achieved up to a 4.7x inference speedup for prefill-heavy workloads. The team bypassed severe hardware sharding constraints by deploying a hybrid Data Parallelism and Expert Parallelism (DP+EP) topology, paired with custom low-level communication fusions like a hierarchical reduce-scatter to optimize cross-device token routing. Finally, by executing hardware-aware custom kernels—such as Batched Ragged Page Attention and a fully-fused Gated DeltaNet (GDN) block—they successfully saturated HBM bandwidth and TensorCore MXUs to push system throughput near its theoretical roofline limits.

Google Developers·July 24, 2026·1 min read
Run Ray on TPU, Part 1: The foundations
TechnologyNews

Run Ray on TPU, Part 1: The foundations

Ray 2.55 introduces official, first-class support for Google Cloud TPUs, enabling developers to run distributed Python workloads on Google's accelerators using the familiar Ray task-and-actor APIs. To handle the strict networking requirement of keeping multi-host TPU "slices" together over their Inter-Chip Interconnect (ICI), the KubeRay Operator on GKE automatically provisions and labels the underlying hardware layout. Ray Core utilizes these labels via its slice_placement_group() primitive to atomically reserve complete slices, allowing developers to deploy jobs through KubeRay, Ray Train, or Ray Serve simply by declaring a hardware topology (like "4x4") without writing custom placement code.

Google Developers·July 24, 2026·1 min read
Evolving Spec-Driven Development: Conductor Now Supports Antigravity
TechnologyRelease

Evolving Spec-Driven Development: Conductor Now Supports Antigravity

Conductor has evolved from a Gemini CLI extension into a portable plugin, bringing conversational Spec-Driven Development (SDD) to ecosystems like Antigravity CLI and Claude. Rather than relying on strict command sequences, developers can now chat naturally with their AI assistant while it dynamically manages persistent markdown artifacts (like spec.md and plan.md) in the background. This update eliminates workflow friction while ensuring your repository remains a version-controlled, single source of truth for your project's architecture and state across different AI tools.

Google Developers·July 24, 2026·1 min read
We terminated a TPU mid-training and it recovered in seconds: Introduction to elastic training with MaxText
TechnologyNews

We terminated a TPU mid-training and it recovered in seconds: Introduction to elastic training with MaxText

Distributed AI training is notoriously fragile because losing a single machine typically crashes the entire multi-node job, forcing a time-consuming, full-workload infrastructure restart. To address this, Google’s JAX ecosystem utilizes elastic training via Pathways, which converts a hardware failure into a catchable Python exception so the running process can survive. When an unplanned failure occurs, the system automatically replaces only the broken worker, restores the last viable checkpoint from Cloud Storage, and resumes training in place—minimizing total downtime to under two minutes without ever restarting the main controller process.

Google Developers·July 24, 2026·1 min read
Build agentic full-stack apps with Genkit
TechnologyOpen Source

Build agentic full-stack apps with Genkit

The open-source Genkit framework has introduced the Agents API, a full-stack tool designed to simplify the complex plumbing of conversational AI by packaging message history, tool loops, and streaming into a single interface. The API supports flexible, server- or client-managed state persistence—allowing for advanced workflows like history branching, long-running detached tasks, and multi-agent coordination—while seamlessly connecting backends to frontends via a unified wire protocol. Currently available in preview for TypeScript and Go, it also integrates with the Genkit Developer UI to allow developers to easily test, debug, and inspect agent snapshots without writing client code.

Google Developers·July 24, 2026·1 min read
Why we built ADK 2.0
TechnologyRelease

Why we built ADK 2.0

Answering the questions of "why we built ADK 2.0". This explains the rationale, some of the features, and why a developer should consider upgrading. This will be published the day after ADK go 2.0 launches.

Google Developers·July 24, 2026·1 min read
The Economics of Owning a Data Center [video]
BusinessNews

The Economics of Owning a Data Center [video]

1 point 0 comments on Hacker News · youtube.com

Hacker News·July 24, 2026·1 min read
Making Deformable a Mirror
TechnologyNews

Making Deformable a Mirror

1 point 0 comments on Hacker News · youtube.com

Hacker News·July 24, 2026·1 min read
JEP 401: Value Objects officially proposed to target JDK 28
TechnologyNews

JEP 401: Value Objects officially proposed to target JDK 28

1 point 1 comment on Hacker News · openjdk.org

Hacker News·July 24, 2026·1 min read
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