---
title: "AI Agents"
description: "571 posts about AI Agents, summarised, each linking to the original."
---

# AI Agents
> 571 posts about AI Agents, summarised, each linking to the original.

## Articles

### [Native is now the future of mobile at Shopify](https://yomu.fyi/post/native-is-now-the-future-of-mobile-at-shopify.md)
- Company: [Shopify](https://yomu.fyi/company/shopify.md)
- Author: 2023-10-18
- Published: Sep 10, 2026
- Type: Announcement

Shopify is moving its mobile apps from React Native to Swift and Kotlin after reevaluating the assumptions behind its 2020 decision as coding models improved. React Native had reduced duplicated implementation and feature-parity work, but agents now handle much of the cross-platform implementation, translation, testing, and review work. Shopify is choosing greenfield rebuilds, with Helix breaking migrations into reviewed checkpoints that require tests, visual comparison, adversarial code review, and human approval. The Shop app reached the app stores as a fully native rebuild in 12 weeks, while the Shopify app migration is underway. The company will continue selected React Native library support while migrating all its apps, and will judge success by product velocity, app quality, and autonomous agent work.


### [Anthropic partners with the UK Government on GOV.UK](https://yomu.fyi/post/anthropic-partners-with-the-uk-government-on-gov-uk.md)
- Company: [Anthropic](https://yomu.fyi/company/anthropic.md)
- Published: Sep 9, 2026
- Type: Announcement

Anthropic has been selected by the UK's Department for Science, Innovation and Technology (DSIT) to help build and pilot a dedicated AI-powered assistant for GOV.UK. The assistant will initially support people entering or re-entering the workforce by helping them find work, access training, understand available support and resources, and route them to relevant services. Powered by Claude, the agentic system is designed to provide individually tailored guidance, maintain context across interactions, and let users control what data is remembered or opt out; personal information will be handled under UK data protection law. Using DSIT’s “Scan, Pilot, Scale” framework, the partners will test and iterate the assistant before wider rollout, building government expertise to maintain it independently.


### [ServiceNow chooses Claude](https://yomu.fyi/post/servicenow-chooses-claude.md)
- Company: [Anthropic](https://yomu.fyi/company/anthropic.md)
- Published: Sep 9, 2026
- Type: Announcement

ServiceNow has selected Claude as the default model for ServiceNow Build Agent and as a preferred model across the ServiceNow AI Platform. Build Agent uses natural-language prompts to help professional coders and citizen developers create applications, design and test agentic automations, while enterprise controls provide access controls, usage monitoring, visibility, and compliance. ServiceNow is also deploying Claude and Claude Code across its workforce of more than 29,000 employees: a Claude-powered sales coaching tool has cut preparation time by up to 95% in testing, while technical teams use Claude Code for coding, reviews, debugging, and repetitive tasks. The partnership targets a 50% reduction in customer implementation time and includes Claude-powered industry applications for healthcare and life sciences, where claims authorization could move from days to hours.


### [Anthropic raises $30B Series G at $380B valuation](https://yomu.fyi/post/anthropic-raises-30b-series-g-at-380b-valuation.md)
- Company: [Anthropic](https://yomu.fyi/company/anthropic.md)
- Published: Sep 9, 2026
- Type: Announcement

Anthropic announces a $30 billion Series G led by GIC and Coatue, with participation from major investors, valuing the company at $380 billion post-money. It says proceeds will support frontier research, product development, and infrastructure expansion as demand for Claude grows among enterprises and developers. Anthropic reports $14 billion in run-rate revenue, more than 500 customers spending over $1 million annually, and eight of the Fortune 10 as customers. Claude Code’s run-rate revenue exceeds $2.5 billion, enterprise use accounts for more than half of its revenue, and an analysis estimated 4% of GitHub public commits. The company also points to Opus 4.6, expanded products including Cowork, and availability across AWS, Google Cloud, and Microsoft Azure, with training and inference across Trainium, TPUs, and NVIDIA GPUs.


### [Anthropic and Infosys build AI agents](https://yomu.fyi/post/anthropic-and-infosys-build-ai-agents.md)
- Company: [Anthropic](https://yomu.fyi/company/anthropic.md)
- Published: Sep 9, 2026
- Type: Announcement

Anthropic and Infosys announced a collaboration to develop and deliver enterprise AI solutions for telecommunications, financial services, manufacturing, and software development. The work combines Anthropic’s Claude models and Claude Code with Infosys Topaz, an AI-first set of services, solutions, and platforms, with an emphasis on governance and transparency for regulated industries. Using tools including the Claude Agent SDK, the partners plan to help clients build persistent agents for multi-step work such as claims processing, code generation and testing, compliance reviews, network operations, risk assessment, and legacy-system modernization. They also describe applications for product design and simulation, software debugging, and routine enterprise operations through Claude Cowork, while noting that Claude is available on Amazon Bedrock, Google Cloud Vertex AI, and Microsoft Azure.


### [Five AI Questions We're Hearing from Financial Services Leaders](https://yomu.fyi/post/five-ai-questions-we-re-hearing-from-financial-services-leaders.md)
- Company: [Databricks](https://yomu.fyi/company/databricks.md)
- Author: Junta Nakai, Erin Butler, Roshni Joshi, Antoine Amend, Jennifer Miller, Andrea DeSosa, Rajaram Suresh, Kim Hatton, Naeem Rehman, Spencer Cook, Ed Bullen, Felix Mutzl
- Published: Sep 9, 2026
- Type: Announcement

Financial services leaders are shifting from asking whether AI works to asking whether it can earn trust, amid governance and audit concerns. The post frames five operational questions around moving finance from reporting to action, using AI in financial crime without losing control, supporting bankers and investment teams, using real-time data, and managing expanding costs. Examples include governed GL-to-Risk reconciliation with cited evidence, human maker-checker oversight and an audit trail; AML agents that draft SARs while humans file; and multi-agent workflows for client and portfolio analysis. The post also cites Coinbase's sub-100ms P99 fraud-detection benchmark and warns that token costs manageable in pilots may grow in production, making model routing and spend visibility relevant. Databricks presents these topics through live demos, talks and meetings at Sibos 2026 in Miami, scheduled for September 28–October 1, including a session on governing AI in financial-crime operations.


### [Announcing ‘The 2026 AI Sentiment Report’: How end users feel about AI Agents](https://yomu.fyi/post/announcing-the-2026-ai-sentiment-report-how-end-users-feel-about-ai-ag.md)
- Company: [Intercom](https://yomu.fyi/company/intercom.md)
- Author: Maia Bridi
- Published: Sep 9, 2026
- Type: Announcement

The 2026 AI Sentiment Report examines how end users feel about AI Agents in customer service and other uses such as shopping. Overall sentiment improved: 49% reported positive experiences, up nine percentage points from 2025, and that figure rose to 74% after respondents watched an Agent resolve a real query. Trust remains conditional, with 54% willing to trust AI with simple or routine issues but not complex ones involving discretion, privacy, continuity, accountability, or judgment. The research identifies easy escalation to a human and upfront disclosure that users are interacting with AI as the two leading ways to increase comfort, while trust also varies by channel, with chat strongest and social weakest. It concludes that businesses can treat trust as a design problem, including reassuring customers that shopping assistants serve their interests rather than merely the company’s financial goals.


### [A practical approach to end-to-end Solvency II reporting in Databricks](https://yomu.fyi/post/a-practical-approach-to-end-to-end-solvency-ii-reporting-in-databricks.md)
- Company: [Databricks](https://yomu.fyi/company/databricks.md)
- Author: Laurence Ryszka, Jack Yallop
- Published: Sep 9, 2026
- Type: Explainer

Solvency II reporting connects data, actuarial reserving, capital calculation, quantitative reporting templates (QRTs), the ORSA, approvals, and disclosure, but fragmented systems make readiness and cross-process questions difficult to manage. The described Databricks implementation provides a governed workflow and control tower around existing actuarial and capital suites, automating ingestion checks, data-quality review, reconciliation, orchestration, reporting, and audit trails. It uses MLflow-managed reserving models alongside engines such as Prophet, RAFM, and Igloo, while narrow-scope AI agents can investigate QRT mismatches, suggest remediation, route questions, and support human review. An LLM can draft an ORSA from current numbers, while scenario analysis assesses doubling a cyber book over 12 months; reviewers retain decision authority. The workflow is presented as easier to monitor and investigate.


### [PwC deploys Claude across its business](https://yomu.fyi/post/pwc-deploys-claude-across-its-business.md)
- Company: [Anthropic](https://yomu.fyi/company/anthropic.md)
- Published: Sep 9, 2026
- Type: Announcement

Anthropic and PwC are expanding their strategic alliance to use Claude for technology delivery, deal execution, and AI-led redesign of enterprise functions. PwC will roll out Claude Code and Cowork from U.S. teams toward a global workforce of hundreds of thousands, establish a joint Center of Excellence, and train and certify 30,000 professionals. The collaboration targets agentic technology builds, AI-native deal-making, and production operating models for finance, supply chain, HR, and engineering, alongside a new Claude-based Office of the CFO for regulated industries. Reported deployments include insurance underwriting reduced from ten weeks to ten days, an HR application delivered in under two months, and cybersecurity response accelerated from hours to minutes, with improvements of up to 70%.


### [Get Gemini 3.8 Flash With 75% Off](https://yomu.fyi/post/get-gemini-3-8-flash-with-75-off.md)
- Company: [Jetbrains](https://yomu.fyi/company/jetbrains.md)
- Author: Dmitry Savelev
- Published: Sep 9, 2026
- Type: Announcement

Google’s Gemini 3.8 Flash is now available in Junie’s IDE plugin and Junie CLI, accompanied by a limited-time 75% introductory discount. The model targets long, multi-step engineering tasks: it spends more tokens exploring directories, retrying failed code, writing bug-reproduction scripts, running tests through tool calls, and checking changes before completion. Google’s DeepSWE v1.1 testing is described as showing 3.8 Flash outperforming most larger frontier models at significantly lower cost, although the source does not provide specific scores. Gemini 3.7 Flash remains available for minor fixes and small refactorings, where its lower per-token cost may be preferable, while 3.8 Flash can be selected from the model picker without setup or a waitlist.


### [Introducing Consort: Test-driven development on a branching database](https://yomu.fyi/post/introducing-consort-test-driven-development-on-a-branching-database.md)
- Company: [Databricks](https://yomu.fyi/company/databricks.md)
- Author: Kevin Hartman
- Published: Sep 9, 2026
- Type: Announcement

Consort is introduced as an open-source agentic development framework for test-driven development on branching Lakebase Postgres databases. It addresses the limitations of mocks, shared staging databases, and risky schema-change ceremonies by bringing integration testing into the inner loop. Its build lane runs red/green/refactor cycles against isolated copy-on-write branches of real data, while versioned migrations keep code and schema changes together and pull-request checks test migrations against fresh branches. Consort organizes work through role-based agents and a deterministic conductor, preserving feature artifacts in dedicated directories and supplying scoped context packages. A VS Code plugin pairs Git and Lakebase branches, while an observability dashboard exposes agent turns and human approval gates; the project is community-supported rather than a bundled platform feature with an SLA.


### [Adaptive Instructed-Retriever: Frontier-Quality Search at 2x Lower Latency](https://yomu.fyi/post/adaptive-instructed-retriever-frontier-quality-search-at-2x-lower-late.md)
- Company: [Databricks](https://yomu.fyi/company/databricks.md)
- Author: Cheng Li, Jialu Liu, Sean Kulinski, Arnav Singhvi, Wen Sun, Michael Bendersky, Cindy Wang
- Published: Sep 9, 2026
- Type: Benchmark

Adaptive Instructed-Retriever addresses the tension between retrieval quality and latency for enterprise data agents, especially on multi-hop questions that benefit from sequential search. It combines parallel single-step retrieval with bounded multi-step search, using a fixed upper limit and an adaptive stopping policy that spends extra steps only when they are likely to improve results. The model is trained with online reinforcement learning using CISPO, a reward that balances trajectory quality against search cost, and synthetic multi-hop data alongside Instructed-Retriever-1 data. Across seven held-out internal and external benchmarks, it matches leading third-party and open-source models while answering in 5.8 seconds, reported as more than twice as fast as the compared alternatives, and substantially improves over single-step search. Varying the step penalty produces checkpoints spanning different quality-latency tradeoffs for production workloads.


### [Join our live webinars: Migrating from Atlassian to YouTrack](https://yomu.fyi/post/join-our-live-webinars-migrating-from-atlassian-to-youtrack.md)
- Company: [Jetbrains](https://yomu.fyi/company/jetbrains.md)
- Author: Elena Pishkova
- Published: Sep 9, 2026
- Type: Announcement

YouTrack announces live webinars for teams considering migration from Atlassian after Atlassian’s stated discontinuation of Data Center sales and support. The worldwide English-language session is scheduled for September 30, 2026, at 2:00 pm CET on YouTube, alongside a Japanese Zoom session and a Russian-language regional session hosted by Noventiq on October 28. The agenda covers migrating projects, users, and data from Jira, Confluence, and Jira Service Management, with a live demo, customer stories, pricing, licensing, deployment options, user packs, and partner support. It is aimed at administrators, project managers, and team leads, and presents YouTrack as a place to combine project management, documentation, and customer support. The Japan session additionally covers workflow automation and connecting AI agents through MCP, while registration for the Asia and Caucasus session is not yet open.


### [Rust AI in Practice: Building LLM Applications With Rig](https://yomu.fyi/post/rust-ai-in-practice-building-llm-applications-with-rig.md)
- Company: [Jetbrains](https://yomu.fyi/company/jetbrains.md)
- Author: Irina Mihajlovic
- Published: Sep 9, 2026
- Type: Explainer

Rig is an open-source Rust library that provides a common interface for LLM providers including OpenAI, Anthropic, and Gemini, avoiding application rewrites when switching services. It structures applications around a provider client, completion model, agent, preamble, and registered tools, with async APIs handling provider network requests. In the Rat Code demo, built with Ratatui, separate tools read and write files and run shell commands, while Rig’s streaming API updates the terminal as responses arrive. The library also supports RAG through vector store abstractions, local inference via Ollama, llama.cpp, or Candle, and cassette-based integration tests that replay recorded HTTP interactions in CI; live model quality requires separate scheduled testing.


### [How we built OCA, our AI on-call assistant](https://yomu.fyi/post/how-we-built-oca-our-ai-on-call-assistant.md)
- Company: [Ramp](https://yomu.fyi/company/ramp.md)
- Author: Richard Marmorstein, Austin Ray
- Published: Sep 9, 2026
- Type: Explainer

Ramp built OCA, an AI on-call assistant that investigates incidents, shares findings in Slack, answers follow-up questions, and can ask Inspect to prepare code-fix pull requests for human review. In the past four weeks, it assisted with 575 of 1,220 incident-related merged PRs; among incidents with merged fixes, OCA-assisted fixes averaged 37% fewer engineers and about 50% less estimated engineer time, based on Slack activity. Investigations run in a monorepo through Claude Code or Codex, with Temporal managing workflow, while prompts, custom tools, skills, and six one-shot hooks provide successive evidence and reasoning checks. Session-driven testing exposed errors such as misleading one-hour log windows, leading to just-in-time instructions and interim updates that balance accuracy with response speed. OCA remains human-in-the-loop: it has broad read-only access, narrowly scoped writes, and cannot merge changes, although the team is building toward end-to-end routine incident handling.


### [Build a Fraud Review Agent with MongoDB Atlas and Claude Managed Agents](https://yomu.fyi/post/build-a-fraud-review-agent-with-mongodb-atlas-and-claude-managed-agent.md)
- Company: [MongoDB](https://yomu.fyi/company/mongodb.md)
- Published: Sep 9, 2026
- Type: Tutorial

Claude Managed Agents runs Anthropic’s Claude as a hosted agent without managing inference infrastructure. Pairing it with MongoDB Atlas provides fast access to operational and vector data through a single pymongo connection, eliminating the need for separate vector, full-text, and graph stores. This tutorial builds a human-in-the-loop fraud review agent that retrieves flagged transactions, runs four retrieval patterns (vector, full-text, hybrid, and graph) against one collection, and escalates risky cases to a human reviewer using Managed Agents’ native pause. The credential-safe integration uses host-side custom tools so the MongoDB connection string never enters the agent sandbox, keeping secrets on your side. The agent verifies a signed authorization mandate, uses $graphLookup to detect mule chains and $rankFusion for hybrid search, writes immutable verdicts and audit events back to the same cluster, and triggers durable human pauses on structuring deposits just under $5,000, wires over $50,000, and ring signals from graph traversal.


### [The Anatomy of Harness Engineering: How to Evaluate, Iterate, and Guard AI Coding Agents](https://yomu.fyi/post/the-anatomy-of-harness-engineering-how-to-evaluate-iterate-and-guard-a.md)
- Company: [Google](https://yomu.fyi/company/google.md)
- Author: Taylor Mullen, Christian Gunderman
- Published: Sep 9, 2026
- Type: Explainer

The post argues that end-to-end benchmarks such as Terminal-Bench and DeepSWE show overall agent performance but rarely explain why behavior changes. It presents behavioral evaluations as fast, deterministic, unit-style checks of observable intermediate actions, such as asking clarifying questions, running validators, or invoking web search instead of guessing. The proposed workflow starts with a recent failure, uses strict milestone assertions for simple tasks and flexible outcome-based or LLM-as-a-judge checks for complex tasks, then runs batch evaluations to track aggregate pass rates despite model nondeterminism. These evaluations are positioned for the second phase of development, after an agent can dogfood its codebase, and as complementary to macro benchmarks: behavioral tests enable prompt, tool-schema, and model iteration while guarding against regressions.


### [dotInsights | September 2026](https://yomu.fyi/post/dotinsights-september-2026.md)
- Company: [Jetbrains](https://yomu.fyi/company/jetbrains.md)
- Author: Rachel Appel
- Published: Sep 8, 2026
- Type: Announcement

dotInsights’ September 2026 issue curates recent .NET and software development material from the developer community, alongside JetBrains announcements and a short social-media coffee break. The featured links cover Azure Service Bus filters, .NET 11 performance, Fetch Metadata-based CSRF protection, software-architecture complexity, standalone hosting for the .NET Aspire Dashboard, and several C# and ASP.NET Core topics. Other selections address AI coding agents, local AI models, MCP clients in .NET, Blazor CSV import and full-text search, URI handling, digital signatures, memory usage in Kubernetes, and .NET MAUI. The issue also notes that Roslyn, the C# compiler, is open source, written in C#, and exposes APIs for analyzing and generating code, while JetBrains promotes upcoming events, Rider and ReSharper releases, and Rider’s AI-agent refactoring capabilities.


### [Detecting and countering malicious uses of Claude](https://yomu.fyi/post/detecting-and-countering-malicious-uses-of-claude.md)
- Company: [Anthropic](https://yomu.fyi/company/anthropic.md)
- Published: Sep 8, 2026
- Type: Incident / postmortem

The report examines how malicious actors used Claude in influence operations, credential scraping, recruitment fraud, and malware development while preserving utility for legitimate users. It details an influence-as-a-service operation in which Claude orchestrated more than 100 social-media bot accounts, selecting likes, shares, comments, or inaction across personas and political objectives. The response used conversation-analysis techniques including Clio and hierarchical summarization, alongside classifiers that assessed user requests and model responses to identify, investigate, and ban accounts. The cases show frontier models accelerating less skilled actors’ capabilities, although successful deployment was not confirmed for the credential, recruitment, or malware efforts, and no content from the influence operation achieved viral status.


### [Disrupting the first reported AI-orchestrated cyber espionage campaign](https://yomu.fyi/post/disrupting-the-first-reported-ai-orchestrated-cyber-espionage-campaign.md)
- Company: [Anthropic](https://yomu.fyi/company/anthropic.md)
- Published: Sep 8, 2026
- Type: Incident / postmortem

In mid-September 2025, an investigation identified a campaign that used Claude Code to target roughly thirty global technology, financial, chemical-manufacturing, and government organizations, succeeding in a small number of cases; the authors assess with high confidence that the actor was Chinese state-sponsored. Attackers jailbroke the model and divided malicious objectives into benign-seeming tasks, allowing an autonomous framework to perform reconnaissance, exploit development, credential harvesting, backdoor creation, data exfiltration, and attack documentation. AI performed 80–90% of the campaign, with humans intervening at perhaps four to six critical decision points, while peak activity reached thousands of requests, often multiple per second. Claude sometimes hallucinated credentials or falsely claimed to have extracted secrets. After ten days of investigation, the organization banned accounts, notified affected entities, and coordinated with authorities; it now describes agentic AI as lowering barriers to sophisticated attacks and calls for stronger detection, threat sharing, safeguards, and defensive adoption.


[Newer posts](https://yomu.fyi/topic/ai-agents/page/9.md) · [Older posts](https://yomu.fyi/topic/ai-agents/page/11.md)