The Tech Radar - Issue #21 (October 2026)

Today, we’re expanding our ecosystem of managed remote MCP servers by introducing the Google Cloud CLI remote MCP server in preview. Powered by the popular gcloud and bq (BigQuery) command-line tools, this new server gives AI agents immediate, broad access to command-line operations for managing Google Cloud infrastructure and working with advanced BigQuery workflows securely and seamlessly.

Here are Google’s latest AI updates from September 2026...

Playground is a new experimental gaming platform that lets you create, play, and share custom games.

Small teams, short runway, and constant pressure to ship faster — it’s the reality we see every day among the founders we work with at Google for Startups. When you are building a company from the ground up, every hour spent on operational overhead or infrastructure plumbing is an hour taken away from your core product. Last week at Gemini at Work 2026, we introduced the Gemini agent : a single, universal agent designed to work both as your personal assistant and as a dedicated member of your...

Editor's note: Generative AI startups are moving rapidly beyond static clip generation to build interactive, real-time worlds. In this technical deep dive, we explore how AI startup Visko collaborated with Google Cloud TPU engineers to deploy Orbis — its continuously streaming Live World Model—on Cloud TPUs, going from initial kickoff to production handover in just 30 days. What makes a live video world model so challenging to serve in production?

In production systems today, most AI agents operate as lightweight dispatchers. They parse a prompt, make an API call, retrieve a record, and hand back control. Their execution is fast, stateless and cheap. Biotechnology does not work this way. Folding a protein target, screening a 50,000 compound ligand library, or evaluating structure-activity relationships (SAR) are not quick API lookups.

The real challenge of building an agentic system isn't the construction, it's the measurement. Evaluation engineering is a critical foundation for building reliable AI systems. Setting up systematic, repeatable tests to measure your agent’s true behavior can be the difference between shipping a tool you can trust and one that silently breaks, fails to call APIs, or makes mistakes.

Whether you are iterating on a quick bug fix or planning a complex migration, different tasks call for different models. In keeping with Google Cloud's commitment to an open ecosystem and to give developers the right model for every job, Claude Opus 5.5 and Claude Sonnet 5.5 are now available in Google Antigravity for Google Cloud customers. Claude Opus 5.5 is built for complex work while Claude Sonnet 5.5 is a faster, lower-cost complement.

Widespread AI adoption is propelling Southeast Asia's digital economy to a projected $368 billion in 2026 and $1 trillion by 2035.

Google Cloud has always been defined by choice, enterprise-grade governance, and market-leading price-performance. Key to the foundation of openness and choice is giving customers flexibility to run agentic workloads across their choice of models and infrastructure to achieve the right balance of cost, capability, and performance. Today, we are expanding that foundation by launching OpenAI models in Google Cloud’s model garden.

Every organization has unique requirements for building and scaling generative AI. At Google Cloud, we are committed to giving developers model choice and architectural flexibility to run workloads however they need. Today, we’re announcing the general availability of an Anthropic-managed deployment option for Claude Models on Google Cloud. This gives teams more choice in how they run their models, helping them consolidate AI workloads on Google Cloud alongside our existingGoogle-managed...

Learn AI literacy via Google’s latest AI Quests lesson on neuroscience, “Polar Peaks.”

Every day, countless financial transactions are interrupted by slow, expensive, and inflexible conventional payment systems. As a result, public commercial stablecoins like Tether, USDC, and PayPal USD have become increasingly popular by making it easy to move money efficiently with instant, 24/7 blockchain settlement. Yet major regulated banks have largely kept such transactions at arm’s length; for these financial institutions, reserve-backed public stablecoins present numerous risks,...

Earlier this year, we introduced Gemini Robotics 2 — our next-generation intelligence layer enabling robots to think, act, and adapt in the physical world. At the core of this breakthrough is Gemini Robotics Embodied Reasoning 2 (ER 2) , a specialized Gemini model that serves as a robot’s high-level brain. Working across any robot embodiment — from stationary arms to full humanoids — Gemini Robotics ER 2 combines advanced spatial and temporal video understanding with long-horizon planning and...

Today, we’re announcing that spend caps on Google Cloud Budgets are generally available. With this release, we’re delivering ways to protect your workloads from runaway costs without risking resource deletion. More importantly, we’re introducing three major updates, directly inspired by your feedback since the initial preview, to bring programmability, real-time visibility, and automated guardrails to your cost-control playbook.

As organizations adopt autonomous agents to build applications, securing identities and access has become more challenging. Developers relying on agents to provision cloud resources, write Terraform, and deploy microservices at machine-speed only find their CI/CD pipelines blo cked even faster as security friction scales. To help you get ahead of agentic-era Identity and Access Management, today we’re introducing IAM Helper.

Welcome to the second Cloud CISO Perspectives for October 2026. Today, Chris Betz talks with Michael Cote, our vulnerability rewards program lead, about the new tier of our Cloud VRP program and the current state of vulnerability rewards. As with all Cloud CISO Perspectives, the contents of this newsletter are posted to the Google Cloud blog . If you’re reading this on the website and you’d like to receive the email version, you can subscribe here .

Editor's note : This blog was updated on Oct. 23, 2026 at 3:20 p.m. PDT, with additional guidance from Mandiant Consulting on monitoring, patching, and remediation. We have previously updated the blog on Oct. 22, 2026, with revised guidance for Security Command Center and Cloud Armor, and on Oct. 21, 2026 . PHP and Wiz Research disclosed today two critical vulnerabilities in the core PHP language runtime that can expose applications to unauthenticated remote code execution and memory disclosure.

Everything is moving faster in the age of AI, and that includes security threats. What used to take attackers weeks to exploit can now happen in just a few minutes. Standard vulnerability scans that run on artifacts at rest can catch basic setup issues, but to detect an attack that's actively happening you need real-time runtime protection. Today, we’re introducing the Wiz Runtime Sensor add-on for Google Kubernetes Engine (GKE), in preview.

Agents represent a fundamental shift in cloud operations. They can act on behalf of users or autonomously, make non-deterministic decisions, and request data across projects at unprecedented speed and scale. Because agents are a distinct category of non-human identity (NHI), they require unique secure-by-default guardrails. Traditional, manually-operated network perimeters are vulnerable to today’s machine-speed attacks.

Welcome to the first Cloud CISO Perspectives for October 2026. Today, Stephanie Kiel explains the latest on our approach to post-quantum cryptography, and shares a new tool to help CISOs and executives prepare their organizations for PQC. As with all Cloud CISO Perspectives, the contents of this newsletter are posted to the Google Cloud blog . If you’re reading this on the website and you’d like to receive the email version, you can subscribe here .

Welcome to the second Cloud CISO Perspectives for September 2026. Today, Alicja Cade and Nick Godfrey, senior directors, Office of the CISO, share their guidance for cybersecurity startups on how to win over the CISOs who will become crucial business partners and customers. As with all Cloud CISO Perspectives, the contents of this newsletter are posted to the Google Cloud blog . If you’re reading this on the website and you’d like to receive the email version, you can subscribe here .

Written by: Aurora Blum, David Mainor, Rohit Nambiar, Omar ElAhdan, Matthew McWhirt, Will Silverstone, Bhavesh Dhake, Chris Busse Introduction Recent intrusions in which threat actors have been observed weaponizing agentic frameworks to execute highly-automated intrusions has put a spotlight on evolving adversarial use of LLMs. In our September 2026 report , Google Threat Intelligence Group (GTIG) noted that forward leaning adversaries were beginning to transition from basic prompting to...

Written by: Jayson Frost, Bryce Greathouse, Brian Meyer, John Palmisano, Rajesh Rajeshirke, Steve Rasch, John Wolfram Introduction On October 15, BeyondTrust disclosed a vulnerability, CVE-2026-102764, impacting BeyondTrust Remote Support (formerly Bomgar) appliances. BeyondTrust Remote Support is an enterprise secure remote access solution that enables IT teams to securely access and troubleshoot remote endpoints.

Written by: Tyler McLellan Introduction Google Threat Intelligence Group (GTIG) and Mandiant investigated a software supply chain compromise campaign targeting the update infrastructure belonging to AOMEI Technology between April 2026 and July 2026. The threat actor conducted repeated, short-burst configuration tampering against AOMEI origin servers. Each tampering window remained active for only five to ten minutes before reverting to authentic versions.

Written by: Robin Grunewald, Supriya Mazumdar, Kelli Vanderlee Introduction Google Threat Intelligence Group (GTIG) examines vulnerability disclosure and exploitation statistics to evaluate the impact of artificial intelligence (AI) on the vulnerability threat landscape. We found that AI is measurably changing not just the pace of vulnerability discovery and exploitation, but also the types and typical risk profiles of vulnerabilities that are being discovered.

The world of work is rapidly evolving, and with it, the tools we use to stay productive and connected. As AI adoption transforms daily workflows, form factors like XR headsets and glasses offer fresh ways to reimagine how productive work happens across apps and devices. Today marks the launch of XREAL AURA , a first-of-kind set of wired XR glasses built on Android XR.

The browser has changed significantly. Rather than just a window to the web, it serves as an AI workspace and central operating environment for the modern enterprise. With knowledge workers spending over 56% of their workday in the browser, it is a key gateway for daily work, complex workflows, and direct interaction with autonomous AI agents ( Omdia , 2026).

Run a quick Google Security Checkup and protect your email with three quick and easy steps.

Spanner Omni , the deploy-anywhere version of Spanner, is now generally available, ready to power your most demanding production workloads in your on-premises data center or on other clouds. With Spanner, Google pioneered the distributed SQL market over a decade ago, combining the horizontal scalability of NoSQL with the ACID compliance and strong consistency of a traditional relational database.

In a data-driven world, PayPal’s ability to deliver timely and actionable insights is central to staying ahead. At PayPal, data powers everything from fraud detection to user experience enhancements. Data is also central to unleashing the potential of agentic solutions and experiences. Over time, though, our analytics environment had become a complex ecosystem of various technologies and solutions assembled on-premise to address growing demands.

At Google Cloud, we know that you count on us to maintain the durability and integrity of your data at all times, both at rest and in transit. And now we’re making it easier for developers to take advantage of native data integrity features in Cloud Storage, by enabling end-to-end checksumming by default in all the Cloud Storage SDKs. Like in any disk-based storage system, bits can flip anywhere in their journey, from the application all the way down to the disk.

The open-source Temporal execution platform is rapidly becoming a foundational layer of modern software infrastructure — especially for orchestration in distributed systems and AI agent workloads. However, deploying and scaling workers in Temporal comes with unique challenges. Workers poll for tasks instead of serving requests, so request-driven serverless platforms can be an awkward fit.

As enterprises shift their AI usage from experimental chatbots to autonomous agents, teams are hitting a critical bottleneck: accessing and reasoning over data scattered across multiple clouds, SaaS platforms, and on-premises systems. To turn AI agents into true systems of action, organizations need a foundation that can handle petabyte-scale reasoning without the security risks of data movement.

Today, Reflection released Beam , its first open-weight model built to give developers, researchers, and enterprises open control and customization for frontier software engineering and long-horizon agentic tasks. Released under a permissive Apache 2.0 license with BF16 , FP8 , and NVFP4 checkpoints available at launch, Beam sets a new standard for inference efficiency in the 500B-parameter class by solving complex reasoning and coding problems with 3x to 4x higher reasoning compute efficiency..

We are announcing a new logging feature that is now available in Python User-Defined Function (UDF) in BigQuery. Developers can now use Python’s standard logging library directly inside BigQuery UDFs to emit structured logs seamlessly into Cloud Logging—with zero external plugins or custom connectors required. While UDF logging enables a wide range of operational monitoring and debugging workflows, to demonstrate this feature we are showcasing an example for building fault-tolerant, resilient...

Imagine you've just launched a new semantic search feature for product reviews to help customers quickly research products on your site. Users love it. But the next day, you see an announcement for a new vector embedding model promising higher accuracy, better nuance, and multilingual search out of the box. After testing it in your dev environment, you confirm it's a perfect fit. But now you're left with a common dilemma: How do you upgrade the model without disrupting your users?

What do you need to orchestrate high-density concurrent AI agents? As we transition from static requests toward autonomous agentic workflows, the need for secure, high-density sandboxes is pushing conventional infrastructure far beyond its architectural breaking point. This transition is driving top-tier research labs to demand infrastructure at unprecedented scale — often up to one million concurrent code-execution sandboxes!

Having visibility into your network traffic is essential to operating Kubernetes environments effectively. When a service slows down or loses connectivity, knowing who is talking to whom lets you narrow the problem down quickly. In a standard cloud network, flow logs provide that view by recording connections between IP addresses, ports, and protocols. In Kubernetes, however, pods are temporary.

Picture the scene: Before an executive business review, your VP of Sales asks an AI assistant, "What was net revenue for our top enterprise accounts last quarter?" In seconds, the agent returns a polished chart! Unfortunately, the numbers don't match the finance report. Why? Because the agent counted cancelled orders as revenue and pulled from an unvalidated staging table. The agent didn't fail because of the model, or because it couldn't translate a user question into a query.

Enterprise organizations often leverage multiple data platforms, including Databricks, to execute heavy Apache Spark jobs alongside BigQuery to power highly concurrent analytics workloads. Historically, bridging these systems often meant building complex pipelines to copy data between environments. This approach increases storage costs, introduces latency, and fragments security controls.

October 26 - October 30 Knowledge Catalog introduces self-learning context enrichment and Knowledge Studio (Preview) Knowledge Catalog's enrichment agent now learns from agent and user interactions and from sources such as playbooks, code repositories, and business documents to find and fix missing or outdated context, which teams can package into reusable context sets.

The Google Cloud AI Infrastructure team had another busy month in October, filled with new product launches and updates to power today’s AI and agentic workloads scalably and efficiently. We were also honored to share our progress with customers, partners, and the broader community at leading industry events, including NVIDIA GTC, PyTorch Conference, and AGNTCon + MCPCon. Let’s dive in!

Every support engineer has a case that stays with them. The one that comes up at team lunches. The one where, even after it's resolved, you find yourself staring at a packet capture at midnight just to make sure you really understand what happened. This is that case. It started in January 2026 with a support ticket that read deceptively simply: pods are intermittently failing to reach the Kubernetes API server. The error was a familiar-looking timeout.

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Today Google Skills is sharing new, industry-specific video learning bundles to get you into Gemini and using agents. One bundle is designed for financial services and one is built specifically for those in the legal profession . You can access all of these videos at no cost on Google Skills today. Whether you're managing complex market portfolios or navigating rigorous compliance reviews, these bite-sized video courses show you exactly how to work smarter with agentic AI.

Today, we’re announcing the public preview of AWS Well-Architected Agent , an AI-powered service that analyzes your AWS environment to deliver targeted, contextual recommendations for improving your applications’ cost, security, performance, and resilience. The AWS Well-Architected Agent analyzes your infrastructure, understands unique business goals, and delivers contextual recommendations with ready-to-implement fixes.

Last week, we announced a public preview of Amazon Bedrock Managed Agents powered by OpenAI , built on a customized version of OpenAI’s Agents API engineered to be AWS-native and integrated with AWS resources. You can now build agents optimized for OpenAI models that run entirely inside AWS with the identities, permissions, and governance controls you already use.

Some numbers are hard to picture until you sit with them for a moment. Last week we published the Prime Day 2026 metrics, and the one that stuck with me is 2.3 quadrillion: the daily requests Amazon ElastiCache peaked at during the event. Prime Day ran back in June, so this post always lands as a retrospective, and that gap is part of what makes it worth reading. By the time the numbers reach you, the only evidence that any of it happened is that nothing went wrong.

Exowatt builds modular, dispatchable solar systems that deliver reliable power for energy-intensive applications such as AI data centers. Its flagship product, the Exowatt P3, captures solar energy through optical lenses, stores it as heat in a long-duration thermal battery, and dispatches electricity on demand through a heat engine. Unlike grid-tied photovoltaic solar systems, P3 powers data centers directly behind the meter, helping data centers come online without waiting in multi-year grid..

This post was co-authored with Khaled Thabit, Meriem Boughrara, and Mohamed Desouky from Property Finder. The engineering team at Property Finder , a digital real estate application, discovered that 96.8 percent of their evaluation labels had been inherited directly from a single model’s predictions rather than verified by human experts. Their ground truth was systematically skewed toward the incumbent model, making every alternative appear to underperform.

Every minute your deep learning container image spends downloading is a minute you pay for and a minute your team waits. Container image download is pure overhead: billable job time that produces no model progress. For modern deep learning images, that overhead is several minutes on every single job. Today, we’re excited to announce Seekable OCI (SOCI) indexing for Amazon SageMaker AI Training and Amazon SageMaker AI processing jobs , which takes full container image download off the critical...

I’m proud to share that Amazon Web Services (AWS) has been named a Leader in the 2026 Gartner Magic Quadrant for Contact Center as a Service (CCaaS) for Amazon Connect for the fourth consecutive year. We believe this recognition reflects years of work pushing on what’s possible in customer experience. When we launched Amazon Connect Customer, we set out to evolve how businesses serve their customers: to make personalized, intelligent experiences possible without giving up efficiency,...

With the launch of AWS Batch support for Amazon SageMaker Training jobs, customers gained a new fully managed way to queue, schedule, and retry machine learning (ML) training workloads without building their own infrastructure. Instead, they use the queuing and scheduling features of AWS Batch. As organizations scale their artificial intelligence and machine learning (AI/ML) operations and onboard more teams, coordinating access to shared graphics processing unit (GPU) capacity can introduce...

When your team moves a mature PHP application to Java, you gain stronger type safety, broader library support, and more predictable scaling. A PHP codebase built over the years with Laravel, Symfony, or Doctrine carries business rules in places that are not obvious, from Eloquent traits to XML mapping files, so a structurally similar Java port can compile cleanly and still behave differently.

To scale intent-driven UI testing across its product teams, Epsilon , a data, technology, and marketing-services company and part of Publicis Groupe , turned to Amazon Nova Act . With hundreds of millions of consumer profiles and thousands of brand relationships, Epsilon needed UI testing that could keep pace with rapid application changes. The solution could not create maintenance overhead for every product team.

The Amazon Quick User Group – United Kingdom is a community of Amazon Quick users in the United Kingdom who meet quarterly to exchange knowledge, share best practices, learn through hands-on sessions, and discuss their experiences using the service. These user groups function as collaborative forums where members learn, connect, and innovate together.

The ChatGPT desktop app is now available on Amazon Bedrock in AWS GovCloud (US) , providing access to OpenAI’s frontier models through two components. Work completes complex, multi-step tasks and delivers review-ready results, and Codex is a coding agent for developing, testing, and reviewing software. This walkthrough is intended for organizations whose security architecture requires model inference to use AWS GovCloud (US) identities, endpoints, and Regional controls.

Worldwide Express (part of ShipStation Global) had built something big: approximately $5 billion in systemwide revenue, over 75 less-than-truckload (LTL) carriers and more than 130,000 customers. But that same scale had a hidden cost. Every month, $15 million in free cash flow sat frozen, locked in billing exceptions no one had resolved yet. Each one had to be chased down by hand, carrier by carrier, with its own rules to check.

Coding agents now build working web apps: a dashboard, a product page, a prototype that a product team wants to try. The fastest way to review that work is to open the app, use it, ask for a change, and check the result. That loop works well when the app keeps running where the agent edits it, so each change shows up in the browser within seconds. When the app must be copied out and deployed somewhere else first, every change waits for a deployment, and the review slows down to that pace.

Cost management for generative AI is a shared responsibility between the teams that build applications and the teams accountable for cloud spend. Many teams start by comparing per-model token rates and asking application teams to shorten prompts. Those steps help, but they don’t answer the questions that finance and engineering leaders ask as usage scales: which team spent this, on which workload, and was that spend inside an approved budget? Agentic workloads make those questions more pressing.

As AI models become more capable, they uncover more security vulnerabilities and identify increasingly sophisticated paths to exploit them, raising the bar for how quickly defenders must respond. Security teams now face more potential vulnerabilities than their existing processes were designed to handle — each requiring investigation, reproduction, and a repair that must be tested to confirm it closes the vulnerability without breaking expected behavior.

You’re building a data agent that lets business users ask questions about lakehouse data in natural language. You’ve already built governance policies that control who can access which datasets. The challenge is making the agent respect those rules without rebuilding them in your application code. When a user asks a question, the agent maps it to data and constructs a query.

In cloud-centered environments, establishing trust between workloads is fundamental to securing machine-to-machine communication. Traditional approaches such as API keys, shared secrets, and static service account credentials weren’t designed for the scale and ephemeral nature of cloud workloads. This drives an organizational need to shift from long-term, static credentials to short-lived cryptographic workload identities.

This post shows you how to configure an AI model to perform structured, evidence-based vulnerability triage with the consistency of a seasoned security analyst. You’ll learn the design decisions behind five configuration sections that enforce structural verification, evidence-based scoring, and infrastructure-aware prioritization across every analysis session. Our companion post— Building your AI vulnerability harness —covered the architecture; this post covers the configuration.

Software supply chain attacks have grown in both frequency and sophistication. Recent high-profile compromises of build systems and open source dependencies demonstrate that attackers increasingly target the trust mechanisms that verify software integrity. Those trust mechanisms rely on digital signature algorithms, and today many use traditional algorithms such as Rivest-Shamir-Adleman (RSA) and the Elliptic Curve Digital Signature Algorithm (ECDSA) .

You want to set a cryptographic algorithm policy and stop non-compliant choices from being made in your Amazon Web Services (AWS) environment. This post shows you how. As you adopt post-quantum cryptography, one of the first decisions you face is which algorithms and parameter sets fit your business needs, balancing security against signature size, key size, and performance.

Amazon GuardDuty Extended Threat Detection correlates weak GuardDuty signals into a single, critical-severity attack sequence finding when their composition crosses a threshold of credibility. On May 20, 2026, the service started attaching five new indicator types to those sequences: MALICIOUS_PACKAGE , MISCONFIGURATION , REACHABILITY , SENSITIVE_DATA , and VULNERABILITY . For more information, see Document history for Amazon GuardDuty and Attack sequence finding details .

We applied AWS Security Agent (now part of AWS Continuum) , our autonomous penetration-testing agent, to 37 real, recently disclosed Common Vulnerabilities and Exposures (CVEs), each packaged as a live, containerized target with a flag hidden at the vulnerability’s intended sink. Starting from an unauthenticated or low-privilege position (an endpoint URL and a one-line hint, no exploit and no proof-of-concept (PoC), the agent had to discover the vulnerability, build a working exploit, chain...

October 20, 2026: This post was republished to reflect the new migration capability from Active Directory to an external identity provider (IdP) or the Identity Center directory, now available in IAM Identity Center. September 2, 2026 : This post was republished to include Active Directory migration strategies and automation for permission sets. AWS IAM Identity Center manages user access to Amazon Web Services (AWS) resources, including both AWS accounts and applications .

Using temporary credentials is a security best practice to reduce the risk from credentials getting compromised. With AWS IAM Roles Anywhere , now your workloads outside of Amazon Web Services (AWS) will be able to access AWS resources by obtaining temporary security credentials in AWS Identity and Access Management (IAM) . IAM Roles Anywhere relies on public key infrastructure (PKI) to establish trust between your AWS account and certificate authorities that issues certificates to your...

Amazon Threat Intelligence identified a PHP2Shell exploitation attempt dating to Oct. 17, 2026, in MadPot telemetry, four days before public disclosure of CVE-2026-109618 and CVE-2026-109619. The exploit attempt originated from an IP address associated with a commercial anonymization network. While the vulnerability was under embargo, the targeting of a honeypot from an anonymized IP address suggests the activity was conducted by a threat actor, though it remains unclear how the actor acquired..

October 29, 2026: We added guidance for end-of-life PHP versions (8.1 and earlier), including the source backports that the PHP security team published for PHP 7.4, 8.0, and 8.1. October 23, 2026 (update 2): The PHP project disclosed CVE-2026-115560, a separate remote code execution issue that the October 21 releases don’t fix. It affects only applications with an uncommon configuration that keeps session upload progress enabled.

The most important work I’ve done in cybersecurity would make for terrible television. There were no countdown clocks and no frantic typing, just a lot of careful reading, a lot of hard conversations, and the occasional quiet moment where everything finally clicked. That’s the part I want to show you this week, because the three people I talked to have built their entire careers on the work that happens off-camera, and it’s the part that decides who lasts in this field.

We continue to expand the scope of our assurance programs at Amazon Web Services (AWS) and are pleased to announce the successful completion of our first ever Cloud High (PBHH) security assessment with 172 assessed services and features. Completion of this assessment, effective September 18, 2026, makes AWS the first cloud service provider (CSP) in Canada to meet this high security bar and provide assurance to our valued customers.

Your workloads reach most destinations by domain name, but a firewall can only act on what it sees in the traffic. For HTTP and HTTPS, AWS Network Firewall domain rules match the name that the client puts in the request, and the client chooses that name. The connections for protocols such as SSH and SSH File Transfer Protocol (SFTP) don’t carry the domain name. The client uses the name only for the DNS lookup and then connects straight to the IP address that DNS returned.

A voice-activated AI agent can make contact center management significantly faster when the AI agents handling your calls need urgent changes. Supervisors running these AI agents on Amazon Connect Customer face a persistent operational challenge. When critical systems go down or AI agent behavior needs immediate adjustment, the path from decision to action involves multiple console logins, manual configuration changes, and time-consuming verification steps.

Email is one of the highest-volume support channels in most contact centers, and one of the most manual. Agents read long threads, search internal knowledge, and draft replies from scratch, which makes for slow first responses and inconsistent messaging. Amazon Connect Customer now provides native AI capabilities for the email channel. With email AI agents , your agents get a summary of the thread, policy guidance grounded in your own knowledge base with citations, and a draft reply.

Introduction Contact center teams running Amazon Connect Customer consistently face a core data engineering challenge: reducing the end-to-end latency from call completion to transcript availability in the data warehouse. The answer is not a single number. It depends on understanding the interplay of 14 distinct latency factors across the pipeline. The factors include the irreducible 2-5 minutes of Amazon Connect Customer conversational analytics speech-to-text (automatic speech recognition, or.

Onboarding agents into Amazon Connect Customer becomes a manual task when organizations standardize on AWS IAM Identity Center as the federation hub for their AWS environment, synchronizing their corporate identity provider (IdP) into a central Identity Store and using it for single sign-on across AWS applications. If you run Amazon Connect Customer this way, and especially if you run more than one Connect instance across multiple AWS accounts, a common challenge emerges: how to automatically...

A customer case study on migrating Amazon WorkSpaces from Asia Pacific (Singapore) to Asia Pacific (Mumbai) Introduction When organizations first adopt Amazon WorkSpaces , they provision virtual desktops in the nearest available AWS Region . Over time, user demographics shift and AWS expands its regional footprint. Eventually, teams migrate their entire WorkSpaces fleet to a closer Region to improve user experience.

Amazon Connect Customer migrations stall because of common avoidable pitfalls that push timelines, inflate budgets, and erode stakeholder confidence. Based on our experience supporting dozens of enterprise contact center migrations, we’ve identified the most common reasons migrations stall and what organizations can do differently. This post is for migration program managers, IT leaders, and business stakeholders planning or currently executing an Amazon Connect Customer migration. 1.

Introduction Amazon Connect Customer workshops are now available with free sandbox environments on AWS Builder Center . This means you can get hands-on experience building agentic AI solution that helps enterprises deliver exceptional customer experiences at every touchpoint with no AWS account required, no credit card needed, and no surprise bills. Whether you’re a developer exploring AI-powered customer experiences, an IT leader evaluating contact center solutions, or a builder curious about..

Organizations running Amazon Simple Email Service (Amazon SES) across multiple AWS accounts face a common challenge: visibility. When you have dozens or hundreds of accounts sending email, answering basic questions becomes surprisingly difficult: How many SES identities exist across my organization? Which identities are verified and pending? Are there stale or unused identities that should be cleaned up? Which accounts are sending from which domains?

Supply chain planners today spend too much time triaging exceptions and coordinating across disconnected systems and not enough time on the strategic decisions that drive business outcomes. At AWS, we’ve been working to change that with Amazon Connect Decisions , an AI-native supply chain planning and decisioning platform built on Amazon’s 30 years of operational science.

Introduction Booking.com is one of the world’s largest online travel platforms. Its customer service organization runs on Amazon Connect Customer, and a voice engineering team supports the contact experience across several lines of business and locales. Booking.com manages Amazon Connect Customer flows as code at scale, and its flow designers still work in the Amazon Connect Customer console.

Organizations with a globally distributed workforce often need to deploy Amazon WorkSpaces Personal across multiple AWS Regions while maintaining centralized identity management with Microsoft Entra ID (formerly Azure Active Directory). Until recently, this required a tradeoff: either a single AWS IAM Identity Center instance with cross-Region calls at runtime, or separate Identity Center instances per Region with duplicated configuration and no unified identity source.

Today, supply chain teams are challenged by how long it takes to resolve urgent issues, and disruptions are estimated to cost the industry billions in losses each year. The problem isn’t a lack of trying. Teams are buried in coordination rather than focused on decisions. Legacy tools and processes can’t keep pace with a network that changes by the hour. We built Amazon Connect Decisions on a different premise.

Your new short code just went active, and you’re ready to migrate production SMS traffic to it from a toll-free number or 10-digit long code (10DLC) where you have collected two years of opt-outs. Those recipients still expect to stay opted out. Your STOP and HELP keywords, along with any custom keywords, must work on the new number from the first message. Carriers also treat the short code as a brand-new sender, with no record of the consent history attached to your old number.

Introduction International two-way SMS with Amazon Connect Customer requires navigating country-specific telecom regulations, origination identity types, and registration processes. Contact centers serving global customers need to reach them via SMS in their local country, but each country has different origination identity types, registration requirements, and two-way messaging capabilities.

When you manage SMS communications for dozens or hundreds of business units, registering each toll-free number (TFN) manually becomes a bottleneck. For independent software vendors (ISVs), software as a service (SaaS) providers, or large organizations with many teams, the repetitive console work, multi-day carrier reviews, and rejection handling add up fast.

This post was contributed by Charlie Chuang, Madhu Vellakal, and Charunethran Panchalam Govindarajan. Since launching Research and Engineering Studio on AWS (RES) , we have helped customers stand up self-service portals for research, engineering, and technical computing on AWS. As this space has matured, with a strong ecosystem of AWS Partners and complementary AWS services, we are focusing our investment on managed services and partner-delivered solutions, and discontinuing development of RES.

In this blog, we will dive-deeper into each use-case mentioned in our launch blog . We will share some of the results partners and customers have achieved using the Kiro based sample agents during their SAP modernization projects. You can download these sample agents here . Here is a recap of the primary use cases covered in launch blog. Upgrade ABAP code for SAP S/4HANA compliance Refactor ABAP to clean core Modernize from SAP PI/PO to SAP BTP Modernize from SAP Business Warehouse (BW) to SAP..

Kiro is AWS’s AI-powered, engineering agent, designed for enterprises to build production-ready software. With Kiro, customers can build across large codebases with parallel agents, which is ideal for complex, resource intensive projects, like SAP modernizations. Today, we are publishing Kiro based sample agents that customers and partners can leverage to accelerate the modernization and deployment of custom SAP Advanced Business Application Programming (SAP ABAP) programs, SAP Business...

High-concurrency Node.js applications such as hotel and travel booking platforms handle many overlapping reads and writes at once: guests search for rooms, reserve, check in, check out, and pay. Node.js suits this workload because its single-threaded event loop keeps thousands of in-flight database operations moving without a thread per request. Pairing Sequelize with Amazon Aurora DSQL gives that event loop a serverless, horizontally scalable SQL backend.

AWS re:Invent 2026 offers an extensive selection of serverless and application integration content. This year’s lineup includes new AWS Lambda execution models: durable functions, Lambda Managed Instances, and Lambda MicroVMs. It also covers AI agents as a new kind of serverless consumer and maturing patterns for production event-driven applications. Don’t have a ticket yet? Register for re:Invent 2026 and join us in Las Vegas from November 30 to December 4.

If you are planning a migration to the AWS Region in Saudi Arabia, start by understanding which workloads are suitable and what they would cost to run once migrated. You can assess your existing environment before the Region opens, without committing to a migration date. Amazon Web Services (AWS) has announced that its first Region in Saudi Arabia is on track to launch in December 2026 .

In alignment with our AWS SDKs and Tools maintenance policy , the AWS IoT Device SDKs MQTT 3.1.1 and V1 service clients will enter maintenance mode in April 2027. There is no planned end-of-support date, and we will announce any change to that separately. We recommend that you adopt the MQTT 5 client and V2 service clients, which provide a more robust feature set, clearer error handling, and lifecycle management. Future feature development will target the MQTT 5 and V2 service clients.

Your team just deployed AWS Outposts to run latency-sensitive workloads on-premises, and now you need to monitor infrastructure that spans both your data center and an AWS Region. Some services run locally on the Outposts, and others depend on Regional endpoints. A network blip between the two can cause silent failures that traditional monitoring tools miss entirely.

Running Apache HBase on Amazon EMR gives you a scalable, high-performance NoSQL store, and following well-understood operational patterns can help improve availability. The most common availability conditions each leave a reliable signature. With the right process, you can more efficiently identify the cause and restore the cluster to full health. This post gives you that repeatable process for three situations you are most likely to meet: an HBase coordinator that is slow to finish...

In this blog post, we show you how to add intelligence to your existing Microsoft infrastructure investments with Kiro CLI. The result is an AI-powered toolset to improve your Windows infrastructure’s health and security posture. Introduction Managing, monitoring, and governing a Windows-based environment is tedious and error-prone. At the same time, you have likely invested heavily in Microsoft management and governance infrastructure such as Active Directory (AD), Group Policy, and Windows...

Introduction When you bring a cloud-native application over to AWS from another cloud, it may contain code that uses another cloud’s SDK. AWS Transform for .NET can convert code from Azure cloud-native applications to use equivalent services from AWS, helping accelerate the migration. In this post, we’ll take you on a tour of converting Azure cloud-native applications to AWS. The AWS Transform .

Storing data you rarely read is one of the most common sources of avoidable cost at scale and one of the hardest to get right. When a dataset grows into hundreds of terabytes or petabytes, the team that owns it often can no longer say with confidence how often it is read. The safe but expensive instinct is to leave everything on the fastest, most expensive storage.

In May 2026, Amazon brought the reliability, resilience, and convenience of its supply chain capabilities along with the network and technology behind it under one logistics system and name: Amazon Supply Chain Services (ASCS) . First built for Amazon, then extended to sellers, now for all businesses and sales channels. Amazon Multi-Channel Fulfillment (MCF) is a key pillar of the network. With MCF, you can use the same fulfillment network that powers Amazon.

Storage is a crucial component of every enterprise application, and it has the potential to be the most complex part of any cloud migration. Many migration approaches work around that complexity by starting with compute and network, leaving storage as an afterthought and this can lead to storage becoming a late-stage bottleneck. In addition to this, the complexity of storage across different vendors, different formats, and the lack of a single, clear view of what you have and where it should go.

When teams move data and AI work to production in a shared environment, one question quickly becomes unavoidable: who can do what? Amazon SageMaker Unified Studio now answers it with designations, which are named permission sets that give administrators granular control over the actions each member can perform within a project. Administrators define a designation once, then assign it to project members.

You write specs that guide AI coding agents, deploy agents on managed runtimes, and orchestrate multi-agent systems across production workloads. Now you can build those skills in a live AWS environment. Today, we’re launching three new AWS Jam experiences focused on agentic AI development: AWS Jam – Spec Driven Development with Kiro , AWS Jam – Building Agentic AI with Amazon Bedrock AgentCore , and AWS Jam – Building Advanced Agentic Systems on AWS .

In August, we released Dogwood , an open source governance language for agents and their actions. Dogwood policies specify which actions an agent may take and under what conditions. A key feature of the language is support for temporal conditions, which let a policy refer to an agent’s past actions and their outcomes. A Dogwood policy can require that certain past actions have or have not occurred, impose constraints on the outcomes of those prior actions, and also restrict their order and...

Enterprises with existing VMware Cloud Foundation (VCF) investments want to migrate their Oracle databases to AWS without rearchitecting applications or retraining operations teams. Oracle on Amazon Elastic VMware Service (Amazon EVS) can take advantage of sub-millisecond storage latency, snapshot-based backup, cross-region disaster recovery (DR), and independent storage scaling, all while preserving existing VMware operational workflows.

When Dynata set out to compress multi-sprint feature delivery into a single sprint, the answer wasn’t simply faster coding. It was reimagining the entire development lifecycle with AI. The team progressed in deliberate stages. They began with AI-assisted coding, then connected AI with their knowledge ecosystem across Confluence, Jira, Lucidchart, GitHub, and Figma.

Telecommunications operators manage vast and complex transport networks that interconnect thousands of nodes, links, and services. When planned maintenance or infrastructure changes occur, engineers must assess which services and customers will be affected—a process known as Change Impact Analysis (CIA). Traditionally, engineers perform this assessment manually, aggregating information from multiple Network Inventory Systems (NIS), correlating topology data, and calculating service disruption—a.

Oil and gas producers worldwide depend on subsurface computing—seismic processing, reservoir simulation, and geological modeling—to make critical exploration and production decisions. Yet many organizations continue to run these demanding workloads on aging on-premises infrastructure that limits scalability, increases operational overhead, and constrains time-to-insight.

Today we launched TorchNeuron , which developers can use to run their existing PyTorch code natively on AWS Trainium , the AI chips we design. Trying a new AI chip used to be a lot of work. You often had to rewrite your code, check that it still gave the right answers, and spend many weeks on it, betting that the new chip was the right one for your workload. That cost time and money, and it wore on teams. Engineers spent that time adapting software instead of improving the product.

Publishing a Shareable Content Object Reference Model (SCORM) course to a learning management system (LMS) is rarely as straightforward as writing the course. The LMS needs SCORM packages to adhere to a standard format for successful import and launch. Producing one by hand means restructuring slides into modules and hand-editing SCORM manifests. The packaging mechanics pull authors away from developing the course content itself.

Registration is now open for two updated exams: AWS Certified Developer – Associate (DVA-C03) and AWS Certified Solutions Architect – Professional (SAP-C03). As we shared in an announcement in September , AWS Certification has updated these exams to reflect how cloud roles have evolved in the age of AI. Now, we have additional resources available to help you prepare for exam day with confidence. As a reminder, the final days to take the previous versions of these exams are fast approaching.

In regulated industries, there’s no room for a move fast and break things approach, especially when AI agents are handling sensitive customer communications data. In this post, we show how Smarsh, a leading archiving and compliance platform for communications intelligence, used the AWS Well-Architected Framework’s Agentic AI Lens to conduct a rigorous, evidence-based review of its first agentic workload.

Accelerating API adoption while reducing operational overhead is a challenge that every growing organization faces. For Revinate, a hospitality provider serving over 12,500 hotels worldwide and powering more than 1.25 billion guest profiles, Amazon API Gateway became the foundation of their solution. Revinate empowers hoteliers to connect directly with guests at every touchpoint, driving $24 billion in lifetime direct revenue through an AI-powered Customer Data Platform (CDP) that helps reduce..

This post is co-written with Sridhara Seshadri from KaHa Technologies Pvt Ltd, a wholly-owned subsidiary of Imagine Marketing Limited (IML). Recognizing that users need more than raw fitness data, boAt launched the “AI Coach” feature. It uses a combination of user history, preferences, and generative AI to deliver personalized coaching plans in real time. Using AWS, boAt built a solution that delivers personalized AI coaching.

This post was co-authored with Saltuk Kezer, Johannes Klepsch, and Marvin Erdmann from BMW Group. The authors would like to thank Sharlina Keshava, Thomas Welle, Christelle Xu, Nicole Meyers, Brian Jensen, Mark Norton, Alexander Opfolter (AWS), and Andre Luckow, Christoph Grote, and Martin Tietze (BMW Group) for their contributions in making this project possible.

This post is co-written with Tomislav Lozancic, Hrvoje Lukavski from BMW Group, and Hugo Cardoso from CTW. BMW Connected Company, a division within BMW Group , develops and operates premium digital services for BMW’s connected vehicle fleet of more than 24.5 million vehicles worldwide. Critical TechWorks (CTW), established in September 2018, focuses exclusively on developing software for BMW Group’s future connected vehicle fleet.

If your finance or actuarial team spends days reconciling earned premium spreadsheets each month, this post shows you how to reduce that to hours using AWS InsuranceLake and Coherent Spark. You want to unify the data so that teams across the organization can access and trust it. A shared data foundation gives marketing, underwriting, claims, actuarial, and finance teams one consistent view of the data, which reduces duplicate work and supports better decisions.

OpenAI will honor a shared robots.txt signal to help website operators communicate their AI training preferences to participating providers.

OpenAI is strengthening violence prevention in ChatGPT with expanded safeguards, earlier interventions, and a new commitment to public safety reporting.

OpenAI shares excerpts from court briefs by creators, academics, accessibility advocates, and legal experts, among others, on how fair use supports AI training and innovation.

OpenAI’s updated Model Spec outlines five core values to guide more capable AI toward sound judgment, human agency, and faithfulness to human intent.

OpenAI uses layered monitoring to detect frontier model misalignment and unauthorized agent behavior so responders can intervene before incidents escalate.

Ropes & Gray is developing AI for transactional diligence with OpenAI. Lawyers review grouped documents, summaries, and reports before advising clients.

Credit Saison’s ChatGPT Enterprise pilot delivered 954% ROI. See how leaders and employees helped turn the results into companywide adoption.

OpenAI and ServiceNow expand their partnership to bring OpenAI models and agents into ServiceNow and ServiceNow workflows into ChatGPT and Codex.

How AI might enter the org chart—beneath, beside, and between us.

See how Legora uses OpenAI models, ChatGPT, and Codex to accelerate legal workflows, expand contract analysis, and free lawyers to focus on higher-value work.

GPT-6 Astra tops Retell’s voice agent benchmark, while Codex helps it reach a $1.6M annual revenue run rate per employee.

OpenAI and Oracle are expanding their partnership to bring business applications and AI agents into ChatGPT and power new Oracle offerings.

With OpenAI Daybreak, Check Point speeds up the research behind new security protections, enabling its analysts to turn vulnerability intelligence into customer defenses faster.

How Greptile uses GPT-6 Astra to test user workflows, Daybreak to strengthen security, and Codex to reduce rework.

OpenAI shares model results on the Kakeya conjecture, Exponential Time Hypothesis, and quantum chromodynamics—and how researchers can verify and build on them.

CodeRabbit uses GPT-6.1 Sol to investigate security risks across complex codebases. Its security agent helps developers review findings and proposed fixes.

Explore OpenAI Signals data on 165 work activities across nearly 100 countries, revealing how people use ChatGPT for work and how usage changes over time.

Fanatics uses OpenAI to help fans complete their game-day outfits with Shop the Look. Testing across roughly 30,000 MLB products showed 10% higher engagement.

See how OpenAI engineers use Codex Ultrafast to investigate incidents in minutes. Explore faster security analysis, code refactoring, and daily workflows.

Bringing fast and capable computer use to everyone...

Learn how OpenAI scaled Habitat with reliable multi-tenancy, global caching, and Azure Cosmos DB to deliver 12× faster reads for ChatGPT.

OpenAI explains how we strengthened containment for frontier model training and evaluation, including offline environments and high-compute red-teaming.

Anima expands what care teams can do with OpenAI models, giving them more capacity to respond to patients.

OpenAI and Poland’s NASK are partnering on AI safety, security, and technical research to strengthen safeguards and support a more resilient digital ecosystem.

Fast, focused, low-cost decisions for any application.

What forward deployed engineering means at OpenAI...

Uber is rolling out ChatGPT Work to more than 30,000 employees, helping teams research, analyze data, create presentations, and complete complex workflows.

AT&T is working with OpenAI to make legal knowledge easier to access. Learn how its LegalEdge team is rethinking intake and scaling legal judgment.

How OpenAI works with distribution partners to uphold consistent safeguards, support responsible access, and clarify expectations in our Usage Policies.

OpenAI and Google Cloud are bringing frontier models and Codex workflows to Gemini’s Model Garden, available through Google Cloud Marketplace.

Patch the Planet connects security researchers, maintainers, and incident responders to help address critical vulnerabilities across open source.

From local businesses to global brands, more advertisers can now reach people as they explore, compare and decide what to buy in ChatGPT.

See how OpenAI, PerturbAI, and Scripps Research used distributed AI agents to uncover promising research leads in data from millions of brain cells.

Cloudflare uses OpenAI Daybreak to investigate vulnerabilities and propose fixes for review. Its developers use Codex to build faster and improve code quality.

Learn how OpenAI built ChatGPT’s LLM-powered ad stack to understand conversational intent, keep ads separate from answers, and deliver relevant ads at scale.

OpenAI outlines a blueprint for empowering cyber defenders with frontier AI, stronger safeguards, modernized cybersecurity, and more resilient public institutions.

An independent Schlotzsky’s and Cinnabon franchisee cut menu repricing time by 95% and built a workflow that could free up $100K in cash flow.

Terminal X’s Eval Agent grades outputs against a 54-criterion rubric, catching 25% more deviances from a fund’s mandate with GPT-6.1 Sol.

OpenAI is acquiring Orchestra Bio to bring AI-powered operations to life sciences R&D, helping biopharma teams accelerate drug development and advance new treatments.

Learn how OpenAI is improving ChatGPT across low-resource programming languages, with new evaluations for software engineering, SQLite, and COBOL migration.

With ia.i, a conversational interface, and the IARA governance platform, Itaú is applying its AI First strategy to customers and employees — in one of Brazil’s most regulated sectors.

See how Localiza uses ChatGPT Enterprise, the OpenAI API, Codex, and 60+ specialized agents to reorganize work and build AI-native mobility experiences.

Almost 50 years after starting in a compounding pharmacy in Paraná, the group operates a proprietary agent platform that autonomously resolves up to 80% of resellers’ operational requests—enabling the sales force to take on an advisory role.

Anant Kumar builds tools to compare loan valuations and analyze credit agreements, using Codex for code review and faster follow-ups.

Two engineers shipped Stack Overflow for Agents in a few weeks with Codex, and its ChatGPT plugin helped drive up to 10× growth in agent creation.

Introducing the Rosalind Academic Plan, offering eligible academic labs sponsored access to GPT-Rosalind and tools to advance life sciences research.

Celebrate Teachers’ Day with AI for Educators in Brazilian Portuguese and see how Study Mode can help teachers support active, step-by-step learning.

In collaboration with OpenAI, Sullivan & Cromwell developed Agreement Analyzer, an AI tool for identifying issues in a draft agreement.

See how Amp pushes the frontier of what agents can do with GPT-6 Astra, Ultrafast, GPT-Live-1, and Sign in with ChatGPT.

With OpenAI Daybreak, SentinelOne cuts weeks of malware analysis to hours, creating capacity to investigate more threats.

With GPT-6 Astra and GPT-6.1 Sol, Codex, and Daybreak for cybersecurity, this AI lab builds agents that focus for days and improve with use.

Block is building AI-powered security with OpenAI. Its security team investigates threats faster and proposes patches in minutes.

New analysis shows how agentic AI adoption is growing across EU enterprises and small businesses—and where deeper use could unlock more value.

Higgsfield brings creators longer videos with GPT-6 Astra, precise visuals with GPT-Image-2.5, and a path to voice filmmaking with GPT-Live.

Using GPT-6 Astra in Codex, Asana made its browser agent 76x cheaper and 5x faster in tests to offer customers more capable models.

Discover how Sophos uses OpenAI’s Daybreak to cut cyber-threat investigation time by 96% and automate 52% of MDR cases while preserving human oversight.

Across recruiting, engineering, and operations, Oracle turns specialist knowledge into fast, repeatable workflows with ChatGPT Work and Codex.

With GPT-5.6, GPT-6 Astra, and GPT‑Image‑2.5, Pollo AI helps creators turn bold ideas into detailed images and cinematic video ads.

LegalOn cut estimated daily Codex costs by 65% while maintaining development speed. It matched Astra, Sol, and Luna to tasks and managed budgets strategically.

OpenAI disrupted two AI-enabled influence operations that used false-front journalists and a think tank to spread geopolitical messaging.

College Planner is coming to ChatGPT for Teens to help students manage college applications, alongside new flashcards, quizzes, and a teen AI council.

Radisson partnered with Accenture to build a ChatGPT plugin using OpenAI technology, helping travelers find, compare, and book hotels while planning their trips.

GPT‑6 is rolling out globally in ChatGPT with Intelligent UI, delivering faster responses with visuals and interactive experiences you can explore and use directly.

Jump Trading uses OpenAI to expand quantitative research. See how longer-running AI workflows combine multiple data sources with human review.

OpenAI publishes new results on open problems in mathematics from an internal frontier model and shares Lean proof formalizations and research details on GitHub.

Learn how OpenAI and Ironclad are training and evaluating AI agents on complex contracting workflows to advance computer use for professional work.

Atlassian and OpenAI are expanding their partnership to connect frontier models with enterprise knowledge and help teams plan, build, and deliver work.

How OpenAI is approaching text watermarking under EU rules. Learn where watermarks apply, how detection works, and why access starts with researchers.

OpenAI introduces a new visual ad format in ChatGPT and expands measurement tools, attribution partnerships, and brand suitability for advertisers.

Learn how startups can choose GPT-6 models, tune reasoning effort, improve prompts and skills, coordinate tools, and prepare workflows for production.

Chatham Financial uses Codex and GPT-5.6 to build technology and redesign workflows, cutting trade validation from 30 minutes to under 4.

Advanced AI may matter most for the routine work behind breakthrough ideas. Explore why execution could shape the next economy and the pace of progress.

Albertsons Cos. is using ChatGPT Enterprise and the OpenAI API to help teams work faster and make grocery shopping easier for millions of customers.

As it opens a new location, the social club prepares grant applications in 2 hours instead of 3 days and liquor-license materials in 3 hours instead of 4 days.

Learn how OpenAI disrupted a campaign to extract protected model reasoning and is strengthening defenses against adversarial distillation.

OpenAI is partnering with America’s SBDC to expand hands-on AI training and local support for small businesses, alongside a new report on how small teams are using AI.

Agentic AI is helping us do things we couldn’t do before. But could it also be weakening the skills we already have? To explore this tension, Salesforce researchers are studying how knowledge workers are using AI to expand their capabilities while preserving the human expertise and judgment that make their work valuable. The findings reveal an interesting paradox.

Content From Enterprise Data to Enterprise Context Unlocking Trapped Data by Breaking Down Data Boundaries Taking Zero Copy Further Bridging Enterprise Data and AI Next Steps & Availability The AI model itself is no longer the differentiator it once was. Enterprises increasingly have access to the same powerful foundation models. What will separate the leaders is something far more valuable: the context of their business. Customer relationships. Transactions. Product usage. Conversations.

Gather ’round, Datablazers. It’s spooky season, and we’ve got your monthly dose of what Datablazers are reading, writing, watching, building, and talking about in the latest Datablazer Roundup. This October, Datablazers have been digging into the details: forecasting without a data science team, keeping Zero Copy data trustworthy, turning Agentforce plans into real deployments, and making sure there aren’t any skeletons hiding in your data before AI gets involved.

Try Salesforce You built your reputation one conversation at a time. The question now is whether you can keep that up as more people show up asking for help. Here’s the problem: Leads and support tickets don’t wait for business hours, and neither do your competitors. When a customer reaches out and nobody answers fast enough, that relationship — the one you worked hard to earn — starts to wobble.

Key Takeaways Let people go first. Invite their sketch, draft, or point of view before AI suggests anything. Make expertise easy to give and keep. Let people supply context and carry it forward, so they don’t re-explain it each time. Build checking into the work. Put verification, review points, and ways to intervene in the workflow, not in people’s memory. This summary was created with AI and reviewed by an editor.

Bringing an innovative or new offering to the market is exciting. You have the opportunity to claim nearly 100% market share with little to no competition, at least for now. But your success depends on the pricing strategy you choose. Targeting less price-sensitive customers, like those willing to pay higher prices to be a product’s first users, can be an effective pricing strategy for those in your situation — one known as price skimming.

Consider the following scenario: You try to delete an unused field on Account, but it is referenced in an obsolete flow version from eighteen months ago that nobody remembers building. You open the flow, scroll its version history, and start deactivating and removing flow versions one at a time. In an org with hundreds of flows and thousands of accumulated flow versions, this stops being a task and becomes a tax you pay on every cleanup, refactor, and deployment.

Try Salesforce You’ve got a product you believe in, and you’re staring down the cost of shelf space, marketing, and inventory just to get it in front of customers. That’s the tension every ambitious business owner runs into eventually: You know the product will sell, but you don’t want to sink cash into a storefront before you’ve proven it. The consignment process solves exactly that problem — it lets you place your goods in someone else’s store and only pay (or get paid) once something sells.

What is RCS Messaging? RCS is delivers a new standard of mobile messaging that delivers rich, interactive experiences across both Apple and Android products. Unlike SMS and MMS, RCS messages are capable of: Rich media: Delivers high-resolution media files instead of compressed images Engaging templates: Create content that drives action withcarousels, tap-through CTAs, and suggested actions.

Try Salesforce As Agentforce Coworker evolves, so do we. Teams of all sizes are finally getting a chance to activate artificial intelligence (AI) agents to get further, grow faster, and be everywhere their customers want them to be. And now, a digital teammate like Coworker does it from a simple chat box, right where you work. But, did you know what else it could do?

By Siddharth Sharma, Suvhrajit Basak, Kusum Dhalia, and Nabeel Qaiser. Your compute bill keeps climbing, and your Spark workloads keep succeeding. Successful execution tells you the configuration worked. It does not tell you how much of the allocated capacity the workload actually needed. Cutting CPU, memory, or executors without that evidence can turn potential savings into slower runs, expensive retries, or production failures.

By Roopang Chauhan, Sundar Vedula, Peng-Wen Chen, and Nikhil Bojja. In our Engineering Energizers Q&A series, we highlight the engineering minds driving innovation across Salesforce. Today, we spotlight Roopang Chauhan, a software engineering architect on the Agentforce team, who helped architect Agentforce Memory, a capability designed to eliminate one of enterprise AI’s biggest limitations: stateless AI agents.

By Vaibhav Raizada, Kumar Kasimala, and Ashish Gite. In our Engineering Energizers Q&A series, we highlight the engineering minds driving innovation across Salesforce. Today, we spotlight Vaibhav Raizada, a senior software engineer at Salesforce, whose team faced a high-stakes AI engineering contradiction while building Assistive Authoring for Salesforce Prompt Builder : transforming open-ended instructions into complete, grounded prompt templates in under a minute without letting the...

This week at SAP TechEd, SAP introduced a range of solutions focused on AI governance. While the solutions address different dimensions of governance in the era of AI, they all reflect the same basic principles: Build on proven business controls: You already have governance standards and practices in place. AI governance should connect to and extend these controls.

This week at SAP TechEd Berlin , we announced new lakehouse and business data fabric capabilities to help enterprises build AI agents act with greater autonomy and confidence. SAP TechEd in 2026: The Autonomous Enterprise Becomes a Reality Read the innovation news guide As AI is deployed across business processes, effective decision-making now hinges on unifying fragmented data and business context.

From vision to reality: In 2026, SAP executives at SAP TechEd demonstrate how developers, customers, and partners can use SAP’s comprehensive AI tools and SAP Business AI Platform to build the Autonomous Enterprise. SAP TechEd in 2026: The Autonomous Enterprise Becomes a Reality Read the innovation news guide In 1996 SAP held its first event for developers.

To help customers accelerate their move to cloud ERP, SAP is bringing to life its migration and modernization assistants for transformation projects. Accelerate your most complex, time-intensive transformation activities Learn how Supporting key workstreams, including data management, test management, custom code modernization, and business configuration, these assistants help organizations simplify transformation activities, accelerate project execution, improve decision-making, and increase...

TOKYO — SAP SE (NYSE: SAP) and NTT Inc. today announced their intention to cooperate in the areas of SAP Sovereign Cloud and SAP Business AI. The planned collaboration aims to bring together SAP’s enterprise application portfolio, SAP Sovereign Cloud and SAP Business AI capabilities with NTT’s global infrastructure, full-stack integrated operations, deep industry AI expertise and global customer reach to help customers benefit from cloud and AI innovation while retaining control over sensitive..

International Space Station’s use of tabular AI and expanded partnerships demonstrate the art of the possible with SAP AI BERLIN — SAP SE (NYSE: SAP) today announced a series of AI innovations at its annual SAP TechEd conference that expands its portfolio for developers. SAP TechEd in 2026: The Autonomous Enterprise Becomes a Reality Read the innovation news guide The enhancements to the Joule Studio and Joule Work solutions and SAP Business AI Platform, including the latest tabular foundation..

Developers are being equipped to build, connect and govern enterprise AI, from intent to trusted execution.

Today, SAP announced the planned deployment of SAP-RPT, our tabular AI foundation model, on HPE Spaceborne Computer-2 aboard the International Space Station (ISS), one of the most significant edge-compute validations of an enterprise AI model to date. SAP TechEd in 2026: The Autonomous Enterprise Becomes a Reality Read the innovation news guide Space is unforgiving. Vacuum, radiation, orbital debris, and solar storms can produce mission-critical crises at any moment.

Most physical AI helps machines act. Physical AI by SAP helps businesses act. By linking robots and physical systems directly to the enterprise processes that run your organization, SAP turns physical execution into a governed, auditable extension of your business, extending the Autonomous Enterprise into the real world. SAP TechEd in 2026: The Autonomous Enterprise Becomes a Reality Read the innovation news guide AI has gone from insight to action and now, with physical AI, it comes into the...

This quarter marks a major step in delivering on our promise of the Autonomous Enterprise, with 45,000 cloud customers now using SAP’s AI solutions. Help people achieve more, respond to change, and uncover new opportunities with AI from SAP Learn how In Q3, we expanded our portfolio of Joule Assistants and introduced dozens of specialized agents that help customers move beyond isolated tasks toward connected, end-to-end execution.

SAP has been named a Leader in the 2026 Gartner® Magic Quadrant™ for Digital Commerce Platforms, making SAP the only vendor recognized as a Leader 12 times since 2014. Build the foundation for agentic commerce Learn how We believe the 2026 evaluation recognized SAP for strengths in areas that are increasingly important to enterprise commerce: using AI to make commerce more intelligent, supporting complexity at global scale, and connecting commerce with operational data.

WALLDORF — SAP SE (NYSE: SAP) today announced its financial results for the third quarter 2026. At a glance Current cloud backlog of €24.1 billion, up 28% and up 26% at constant currencies Cloud revenue up 26% and up 25% at constant currencies Cloud ERP Suite revenue up 29% and up 28% at constant currencies Total revenue up 13% and up 12% at constant currencies IFRS operating profit up 18%, non-IFRS operating profit up 18%, both at nominal and constant currencies SAP updates its 2026 cloud...

SAP LeanIX has once again been positioned as a Leader in the Gartner® Magic Quadrant™ for Enterprise Architecture Tools for 2026. See your landscape clearly, improve how processes run, and guide people through every change Learn how This is the sixth time that SAP LeanIX has positioned as a Leader in the annual report. We believe this reflects our unique strength in helping enterprises breathe life into their enterprise architecture data, discover and govern their AI portfolios, and make rapid..

The next stage of customer experience requires more than intelligent recommendations. Harmonize CRM and CX with a single autonomous system Learn how It requires AI that can drive outcomes by executing and coordinating work across the customer journey and the business processes behind it, grounded in trusted data and governed at every step. With the SAP Customer Experience Q3 2026 release, SAP is bringing the Autonomous CX vision to life as part of the broader Autonomous Enterprise .

Starting in October, SAP is expanding the Stay Certified experience with new ways for certified professionals to demonstrate current knowledge, including AI-powered roleplays grounded in real-world customer scenarios. What the cloud introduced, AI has only accelerated: constant software updates, new capabilities, and a faster pace of innovation. For professionals working across the SAP ecosystem, keeping pace with that change is becoming an increasingly important part of maintaining their...

There is a persistent assumption in enterprise software procurement that a CRM evaluation is, at its core, a sales and service productivity decision. Harmonize your CRM and CX with a single autonomous system Learn how You benchmark features, compare pricing, run a proof of concept, and choose the platform your sales team finds most intuitive. The ERP conversation happens in a different room, with different stakeholders, on a different cycle. This separation feels logical on an org chart.

From SAP R/3 and the first hands-on sessions to SAP HANA, the cloud, and AI, SAP TechEd has spent three decades tracking technological change—and, at times, anticipating what was to come. SAP TechEd in 2026: Join the premier technical event to build what matters Register now The story began in 1996, when around 700 developers and technical experts gathered in Orlando, Florida, to explore a new generation of enterprise software.

We are pleased to announce that SAP has been named a Leader in the 2026 Gartner Magic Quadrant for Cloud ERP for Finance *. We believe this recognition reflects our continued commitment to helping organizations build intelligent, connected finance functions that can deliver greater insight, efficiency, and business impact. Today’s finance leaders are expected not only to report on business performance, but also to help shape it.

Generative AI helps people to write, research, program, or evaluate content faster. A huge benefit, but one that also comes with a serious problem: according to a McKinsey study , while 80% of AI users report increased personal productivity, only six percent of companies say that AI significantly increased their operating profit. Turn structured data into accurate, explainable predictions that your team and AI agents can act on Learn more about tabular AI How can this gap be closed?

Artificial intelligence can do far more for public administration than answer questions or digitize individual interactions. Unify every mission-critical function to drive government efficiency and innovation Learn how Its real potential emerges when AI connects with the data and processes behind public services, turning a citizen request into coordinated action across the administration.

Major security incidents can quickly affect enterprise value, operational continuity, regulatory standing, and reputation. Securely access cloud services, meet compliance goals, and build customer confidence Learn how As organizations become more dependent on connected infrastructure, cloud services, AI, and third parties, weaknesses in one part of the ecosystem can cascade across the business. A Board is not expected to make technical decisions.

In many B2B organizations, creating a customer quote still involves a familiar sequence of emails, approvals, contract reviews, and manual handoffs. The process can take days or even weeks, creating delays for customers and additional work for employees. Generate traffic from AI search and use AI to execute Learn how Ericsson knows this challenge well.

The Germany-based logistics company DACHSER has set itself an ambitious goal: to become the world’s most digitally integrated logistics service provider by 2030, seamlessly aligning its resources, experience, and modern digital operational capabilities with the needs of its customers, employees, and partners. Transform on-premises ERP to the cloud to power AI assistants to drive real business outcomes Learn how Following eight months of close collaboration with SAP, DACHSER has reached a major..

Artificial intelligence has become one of the fastest-adopted technologies in business history. As a result, AI has become ubiquitous. AI value, however, hasn’t. Run your business on an AI cloud ERP built for companies of any size Learn how SAP’s latest global research with Oxford Economics reveals that organizations are already using AI across approximately 25% of business tasks , yet despite this momentum, only nine percent of organizations have fundamentally adapted their business around AI.

SAP Cloud ERP Private 2025 Feature Pack Stack 02 (FPS02) delivers new capabilities that help organizations move from AI experimentation toward intelligent, governed business execution faster. The release combines AI agents that can work directly with core business processes and adds new regulatory compliance capabilities and industry-specific innovations across asset-intensive industries, retail, and energy sectors.

Enterprise AI has reached an inflection point. SAP Connect in 2026: Advancing the Autonomous Enterprise Read the innovation news guide But while there is enormous excitement about what AI can do, we are still measuring progress the wrong way. The number of models, pilots, or agents a company deploys tells us very little. What matters is whether AI transforms the core processes where business value is actually created.

Last week at SAP Connect, SAP introduced new capabilities and partner innovations across SAP Ariba, SAP Fieldglass, and SAP Concur that help organizations turn spend insights into faster, better-informed decisions. SAP Connect in 2026: Advancing the Autonomous Enterprise Read the innovation news guide Procurement leaders operate in a very different environment than they did just a few years ago.

New innovations in payments, enterprise performance management, and AI automation help finance teams move quickly from insight to execution while maintaining governance and control. SAP Connect in 2026: Advancing the Autonomous Enterprise Read the innovation news guide Finance leaders today are expected to do far more than report results. They’re expected to shape business outcomes, guide decisions, and respond quickly to change.

As workforce challenges continue to outpace traditional HR processes, the organizations that lead won’t be the ones with the most AI. They’ll be the ones that understand their people, their skills, and how work really gets done—and know where AI can move them beyond incremental improvement into lasting transformation. Turn HR into a strategic growth engine with AI Discover Autonomous HCM With the SAP SuccessFactors 2H 2026 release and throughout the remainder of the year, we’re taking the next..