Practical things you can use now: prompting tips, building workflows, how to use tools and lessons learned.
In production AI agents, context management is the real bottleneck. This post presents a four-layer context engineering framework (architecture, prompts, file-based tools, and verification agents), implemented in working code from Deep Insight, an open source multi-agent data analysis solution on the Strands Agents SDK and Amazon Bedrock AgentCore.
Grok 4.7 is now available on Amazon Bedrock. In this post, we build a tool-calling agent on Grok 4.7 and evaluate it on three reasoning tasks at four reasoning effort levels, measuring correctness and token cost per completed task. We show how to tune the trade-off per request and monitor it in production.
Last week, I wanted a small version of the prompt rewriter that ships with Qwen-Image 2.1. The official one is a 9B model that needs about 20 GB of memory and thinks for thousands of tokens before writing a single paragraph. On the Hub, I found only compressed copies of that same 9B model.
Amazon Bedrock AgentCore Runtime Instances gives multi-agent workflows AWS managed EC2 infrastructure with GPUs, persistent volumes, and multi-day sessions. In this post, we deploy a three-agent music production pipeline where the agents colocate on one GPU instance, share a filesystem, and hand work to each other to produce a finished track.
A rewrite this size wasn't affordable before agents. Here's what porting the Copilot agent runtime to 800,000 lines of production Rust actually took.
The Hugging Face team rebuilt most AUTOMATIC1111 functionality as the Workflow1111 canvas using Gradio Workflow. Its 11 media pipelines and 73 nodes cover text-to-image, high-resolution fixes, image-to-image, prompt matrices, VLM reverse prompting, detection-generated inpainting masks, ControlNet-style annotators, background removal, PNG Info and image-to-video.
Mistral helped a European energy operator migrate 40,000 lines of Fortran 77 to C++. Learn how it was done, and the lessons to carry forward.
Sentence Transformers v6.0 adds a fourth model type, MultiVectorEncoder, for ColBERT-style late-interaction retrieval, with a complete training approach.
A Hugging Face blog tutorial demonstrates a streaming data loop for Strands Robots. The same Robot() object records demonstrations, syncs them to a Storage Bucket, streams training data from the Hub and deploys the checkpoint back to hardware, keeping the LeRobot disk format unchanged throughout.
Mistral built an autonomous agent on its open-source coding assistant Vibe to read Rails source files, generate or improve RSpec tests and run within CI/CD without human intervention.