Search: “context”

This article provides practical guidelines and best practices for maintaining a clean, well-organized context when working with AI systems, likely covering techniques for prompt engineering, managing

Abner Li / 9to5Google: Google launches a Gemini Mac app, featuring a keyboard shortcut, screen sharing for better context, image generation with Nano Banana, and more — Gemini now has a native Mac app

Aaron Holmes / The Information: Microsoft says it is “exploring the potential of technologies like OpenClaw in an enterprise context”, including a team of always-on agents within Microsoft 365 — As Mi

Sema4.ai Inc. a startup that provides tools for building and managing artificial intelligence agents, today announced a massive revamp of its platform, with big changes coming to every layer of the ag

Enterprise AI needs agentic transformation to turn scattered experiments into measurable business outcomes. The next phase of AI adoption is less about picking models and more about making enterprise

Process mining software company Celonis SE said today it has snapped up the Massachusetts Institute of Technology-linked decision intelligence startup Ikigai Labs Inc., planning to use it to power a n

Subquadratic, a company developing a novel generative artificial intelligence model, launched today with 29 million in seed funding. The new large language model, dubbed SubQ, uses what the company ca

For as long as Cisco Systems Inc. has held its WebexOne event, the show has aimed to drive thought leadership in the collaboration industry. This year, with artificial intelligence on tap, it had its

On-device personal AI requires models and agent software that can operate within fixed hardware limits. Developers also need ways to keep those systems improving after deployment. Model builders are r

Diffusion Large Language Models (dLLMs) have emerged as a promising alternative to purely autoregressive language models because they can decode multiple tokens in parallel. However, state-of-the-art

Fine-tuning isn't dead, but the way most teams iterate on AI products has split in two. A tiny fraction run continuous RL against their own environments; everyone else has moved the iteration loop out

Starburst Data Inc. today is expanding its push into enterprise artificial intelligence with the introduction of a platform aimed at allowing organizations to run AI workloads directly on distributed

In this post, you will learn how to implement Recursive Language Models (RLM) using Amazon Bedrock AgentCore Code Interpreter and the Strands Agents SDK. By the end, you will know how to process docum

You can build a measurably better agent from data you already have, without retraining a thing. The data is what your experienced humans do when they correct the AI. Capture... The post Building a sel

As agents start changing software, they need a way to verify their work that includes traces, evals, feedback, and APIs. This is where Phoenix goes next — not the next release, but what this product b

Enterprise software is on the verge of its first compounding data loop, the same kind of self-reinforcing mechanism that built the most valuable consumer businesses of the last twenty years.... The po

Enterprise AI ambitions are stalling not because models are hard to build, but because the data foundations underneath them were never designed to support intelligent workloads at scale — and a unifie

Query Tags is a Databricks feature that adds contextual metadata to warehouse queries, enabling better tracking, organization, and management of query workloads. This capability allows users to label

If you’re iterating on deploying large language models (LLMs) on AWS GPU instances, you’ve probably noticed the larger the model to be loaded into GPU High Bandwidth Memory (HBM), the longer the painf

Databricks describes contextual policies in Omnigent, a framework that leverages session state to implement more effective governance and control mechanisms for AI agents. By maintaining and utilizing

Amplitude Inc. today introduced an embedded artificial intelligence support agent that helps users navigate digital products without leaving the application. Amplitude AI Assistant uses behavioral dat

Lovelace AI Inc. is emerging from stealth mode today with an approach to enterprise artificial intelligence that it says is necessary for high-stakes decision-making, particularly in environments wher

Traditional data catalogs were built as manual inventories for technical users, focusing on table structures rather than the deep context that AI agents need. When agents lack business semantics and d

--> .abbel-fig { display: block; text-align: center; margin: 2.4em 0; line-height: 1.4; max-width: 100%; } .abbel-fig img { display: block; margin: 0.65em auto 0; height: auto; max-width: 100%; } /* I

Automated lint: 20 errors, 8743 warnings, 3 info

Auto-generated index of all tools mentioned across the wiki.

Automated lint: 26 errors, 6728 warnings, 3 info

In this episode of The Agent Factory, we explore the reality of building with autonomous agents alongside Ryan Lopopolo, a software engineer at Google Cloud and the person who coined the term agent ha

Automated lint: 12 errors, 53990 warnings, 3 info

Agents are only as capable as the context they can reach. An agent with reliable access to the right information makes decisions grounded in fact; one without it guesses. And the work agents produce i

Editor’s note: This article is adapted from Thomas Kurian’s keynote address at Gemini at Work 2026. It includes a number of announcements: Gemini, a single, universal agent for work that answers your

Automated lint: 19 errors, 64915 warnings, 3 info

Enterprise AI agents need persistent memory to execute complex, multi-day workflows and long-horizon tasks. In this blog, we examine how a 2-tier memory architecture using Memorystore for Valkey for s

Google Cloud Next ‘26 took place this week in Las Vegas, and the energy was incredible as we welcomed over 32,000 leaders, developers, and partners to explore the Agentic Era with us. Across three key

Automated lint: 17 errors, 59669 warnings, 3 info

Automated lint: 14 errors, 54840 warnings, 3 info

Automated lint: 12 errors, 54839 warnings, 3 info

Many of the questions that matter in enterprise data aren't just about individual rows — they're about how things connect: how two accounts are linked, what path a payment took, what context grounds a

Coinbase CEO Brian Armstrong recently posed the question every company scaling AI is asking: how do you keep spend flat while token usage grows exponentially? This isn’t hypothetical. It’s confronting

Auto-generated index of all models mentioned across the wiki.

QueryData launches in preview today. It is a tool for translating natural language into database queries with near-100% accuracy. With QueryData, you can build agentic experiences across AlloyDB, Clou

Long agent traces composed of chains of thought and tool calls accumulate stale content that anchor subsequent generations, and eventually outgrow the context window. Existing scaffolds mitigate it wi

Presented by Tata Communications Enterprises are deploying AI agents, voice AI, and automation across messaging, voice, and digital channels faster than the architecture meant to support it. Most of t

For financial institutions, operational resilience has long been embedded in regulatory and supervisory expectations — to say nothing of the high expectations of consumers. With the implementation of

As enterprise generative AI transitions from simple, conversational chatbots to autonomous multi-agent workflows, developers face a critical bottleneck: scale. In a production environment, an enterpri

Every device, user, and microservice generates data. Ingesting this data, extracting meaning and insights, and driving business decisions in real time has the potential to deliver transformational bus