Starting with Integrations, the feature builds on a technical standard Anthropic released last year (the Model Context Protocol, or MCP), but makes it much easier to use. Before, setting this up was a bit technical and local. Now, developers can build secure bridges allowing Claude to connect safely with apps over the web or on your desktop.

For end-users of Claude, this means you can now hook it up to a growing list of popular work software. Right out of the gate, they’ve included support for ten big names: Atlassian’s Jira and Confluence (hello, project managers and dev teams!), the automation powerhouse Zapier, Cloudflare, customer comms tool Intercom, plus Asana, Square, Sentry, PayPal, Linear, and Plaid. Stripe and GitLab are joining the party soon.

So, what’s the big deal? The real advantage here is context. When Claude can see your project history in Jira, read your team’s knowledge base in Confluence, or check task updates in Asana, it stops guessing and starts understanding what you’re working on.

“When you connect your tools to Claude, it gains deep context about your work—understanding project histories, task statuses, and organisational knowledge—and can take actions across every surface,” explains Anthropic.

They add, “Claude becomes a more informed collaborator, helping you execute complex projects in one place with expert assistance at every step.”

Let’s look at what this means in practice. Connect Zapier, and you suddenly give Claude the keys to thousands of apps linked by Zapier’s workflows. You could just ask Claude, conversationally, to trigger a complex sequence – maybe grab the latest sales numbers from HubSpot, check your calendar, and whip up some meeting notes, all without you lifting a finger in those apps.

For teams using Atlassian’s Jira and Confluence, Claude could become a serious helper. Think drafting product specs, summarising long Confluence documents so you don’t have to wade through them, or even creating batches of linked Jira tickets at once. It might even spot potential roadblocks by analysing project data.

And if you use Intercom for customer chats, this integration could be a game-changer. Intercom’s own AI assistant, Fin, can now work with Claude to do things like automatically create a bug report in Linear if a customer flags an issue. You could also ask Claude to sift through your Intercom chat history to spot patterns, help debug tricky problems, or summarise what customers are saying – making the whole journey from feedback to fix much smoother.

Anthropic is also making it easier for developers to build even more of these connections. They reckon that using their tools (or platforms like Cloudflare that handle the tricky bits like security and setup), developers can whip up a custom Integration with Claude in about half an hour. This could mean connecting Claude to your company’s unique internal systems or specialised industry software.

Beyond tool integrations, Claude gets a serious research upgrade

Alongside these new connections, Anthropic has given Claude’s Research feature a serious boost. It could already search the web and your Google Workspace files, but the new ‘Advanced Research’ mode is built for when you need to dig really deep.

Flip the switch for this advanced mode, and Claude tackles big questions differently. Instead of just one big search, it intelligently breaks your request down into smaller chunks, investigates each part thoroughly – using the web, your Google Docs, and now tapping into any apps you’ve connected via Integrations – before pulling it all together into a detailed report.

Now, this deeper digging takes a bit more time. While many reports might only take five to fifteen minutes, Anthropic says the really complex investigations could have Claude working away for up to 45 minutes. That might sound like a while, but compare it to the hours you might spend grinding through that research manually, and it starts to look pretty appealing.

Importantly, you can trust the results. When Claude uses information from any source – whether it’s a website, an internal doc, a Jira ticket, or a Confluence page – it gives you clear links straight back to the original. No more wondering where the AI got its information from; you can check it yourself.

These shiny new Integrations and the Advanced Research mode are rolling out now in beta for folks on Anthropic’s paid Max, Team, and Enterprise plans. If you’re on the Pro plan, don’t worry – access is coming your way soon.

Also worth noting: the standard web search feature inside Claude is now available everywhere, for everyone on any paid Claude.ai plan (Pro and up). No more geographical restrictions on that front.

Putting it all together, these updates and integrations show Anthropic is serious about making Claude genuinely useful in a professional context. By letting it plug directly into the tools we already use and giving it more powerful ways to analyse information, they’re pushing Claude towards being less of a novelty and more of an essential part of the modern toolkit.

(Image credit: Anthropic)

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In a research paper, the Societal Impacts team at Anthropic details a privacy-preserving methodology designed to observe and categorise the values Claude exhibits “in the wild.” This offers a glimpse into how AI alignment efforts translate into real-world behaviour.

The core challenge lies in the nature of modern AI. These aren’t simple programs following rigid rules; their decision-making processes are often opaque.

Anthropic says it explicitly aims to instil certain principles in Claude, striving to make it “helpful, honest, and harmless.” This is achieved through techniques like Constitutional AI and character training, where preferred behaviours are defined and reinforced.

However, the company acknowledges the uncertainty. “As with any aspect of AI training, we can’t be certain that the model will stick to our preferred values,” the research states.

“What we need is a way of rigorously observing the values of an AI model as it responds to users ‘in the wild’ […] How rigidly does it stick to the values? How much are the values it expresses influenced by the particular context of the conversation? Did all our training actually work?”

Analysing Anthropic Claude to observe AI values at scale

To answer these questions, Anthropic developed a sophisticated system that analyses anonymised user conversations. This system removes personally identifiable information before using language models to summarise interactions and extract the values being expressed by Claude. The process allows researchers to build a high-level taxonomy of these values without compromising user privacy.

The study analysed a substantial dataset: 700,000 anonymised conversations from Claude.ai Free and Pro users over one week in February 2025, predominantly involving the Claude 3.5 Sonnet model. After filtering out purely factual or non-value-laden exchanges, 308,210 conversations (approximately 44% of the total) remained for in-depth value analysis.

The analysis revealed a hierarchical structure of values expressed by Claude. Five high-level categories emerged, ordered by prevalence:

1. Practical values: Emphasising efficiency, usefulness, and goal achievement.
2. Epistemic values: Relating to knowledge, truth, accuracy, and intellectual honesty.
3. Social values: Concerning interpersonal interactions, community, fairness, and collaboration.
4. Protective values: Focusing on safety, security, well-being, and harm avoidance.
5. Personal values: Centred on individual growth, autonomy, authenticity, and self-reflection.

These top-level categories branched into more specific subcategories like “professional and technical excellence” or “critical thinking.” At the most granular level, frequently observed values included “professionalism,” “clarity,” and “transparency” – fitting for an AI assistant.

Critically, the research suggests Anthropic’s alignment efforts are broadly successful. The expressed values often map well onto the “helpful, honest, and harmless” objectives. For instance, “user enablement” aligns with helpfulness, “epistemic humility” with honesty, and values like “patient wellbeing” (when relevant) with harmlessness.

Nuance, context, and cautionary signs

However, the picture isn’t uniformly positive. The analysis identified rare instances where Claude expressed values starkly opposed to its training, such as “dominance” and “amorality.”

Anthropic suggests a likely cause: “The most likely explanation is that the conversations that were included in these clusters were from jailbreaks, where users have used special techniques to bypass the usual guardrails that govern the model’s behavior.”

Far from being solely a concern, this finding highlights a potential benefit: the value-observation method could serve as an early warning system for detecting attempts to misuse the AI.

The study also confirmed that, much like humans, Claude adapts its value expression based on the situation.

When users sought advice on romantic relationships, values like “healthy boundaries” and “mutual respect” were disproportionately emphasised. When asked to analyse controversial history, “historical accuracy” came strongly to the fore. This demonstrates a level of contextual sophistication beyond what static, pre-deployment tests might reveal.

Furthermore, Claude’s interaction with user-expressed values proved multifaceted:

• Mirroring/strong support (28.2%): Claude often reflects or strongly endorses the values presented by the user (e.g., mirroring “authenticity”). While potentially fostering empathy, the researchers caution it could sometimes verge on sycophancy.
• Reframing (6.6%): In some cases, especially when providing psychological or interpersonal advice, Claude acknowledges the user’s values but introduces alternative perspectives.
• Strong resistance (3.0%): Occasionally, Claude actively resists user values. This typically occurs when users request unethical content or express harmful viewpoints (like moral nihilism). Anthropic posits these moments of resistance might reveal Claude’s “deepest, most immovable values,” akin to a person taking a stand under pressure.

Limitations and future directions

Anthropic is candid about the method’s limitations. Defining and categorising “values” is inherently complex and potentially subjective. Using Claude itself to power the categorisation might introduce bias towards its own operational principles.

This method is designed for monitoring AI behaviour post-deployment, requiring substantial real-world data and cannot replace pre-deployment evaluations. However, this is also a strength, enabling the detection of issues – including sophisticated jailbreaks – that only manifest during live interactions.

The research concludes that understanding the values AI models express is fundamental to the goal of AI alignment.

“AI models will inevitably have to make value judgments,” the paper states. “If we want those judgments to be congruent with our own values […] then we need to have ways of testing which values a model expresses in the real world.”

This work provides a powerful, data-driven approach to achieving that understanding. Anthropic has also released an open dataset derived from the study, allowing other researchers to further explore AI values in practice. This transparency marks a vital step in collectively navigating the ethical landscape of sophisticated AI.

We’ve made the dataset of Claude’s expressed values open for anyone to download and explore for themselves.

Download the data: https://t.co/rxwPsq6hXf

— Anthropic (@AnthropicAI) April 21, 2025

See also: Google introduces AI reasoning control in Gemini 2.5 Flash

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As the researchers initially highlighted, the internal processes of these models can be remarkably opaque, with their problem-solving methods often “inscrutable to us, the model’s developers.”

Gaining a deeper understanding of this “AI biology” is paramount for ensuring the reliability, safety, and trustworthiness of these increasingly powerful technologies. Anthropic’s latest findings, primarily focused on their Claude 3.5 Haiku model, offer valuable insights into several key aspects of its cognitive processes.

One of the most fascinating discoveries suggests that Claude operates with a degree of conceptual universality across different languages. Through analysis of how the model processes translated sentences, Anthropic found evidence of shared underlying features. This indicates that Claude might possess a fundamental “language of thought” that transcends specific linguistic structures, allowing it to understand and apply knowledge learned in one language when working with another.

Anthropic’s research also challenged previous assumptions about how language models approach creative tasks like poetry writing.

Instead of a purely sequential, word-by-word generation process, Anthropic revealed that Claude actively plans ahead. In the context of rhyming poetry, the model anticipates future words to meet constraints like rhyme and meaning—demonstrating a level of foresight that goes beyond simple next-word prediction.

However, the research also uncovered potentially concerning behaviours. Anthropic found instances where Claude could generate plausible-sounding but ultimately incorrect reasoning, especially when grappling with complex problems or when provided with misleading hints. The ability to “catch it in the act” of fabricating explanations underscores the importance of developing tools to monitor and understand the internal decision-making processes of AI models.

Anthropic emphasises the significance of their “build a microscope” approach to AI interpretability. This methodology allows them to uncover insights into the inner workings of these systems that might not be apparent through simply observing their outputs. As they noted, this approach allows them to learn many things they “wouldn’t have guessed going in,” a crucial capability as AI models continue to evolve in sophistication.

The implications of this research extend beyond mere scientific curiosity. By gaining a better understanding of how AI models function, researchers can work towards building more reliable and transparent systems. Anthropic believes that this kind of interpretability research is vital for ensuring that AI aligns with human values and warrants our trust.

Their investigations delved into specific areas:

• Multilingual understanding: Evidence points to a shared conceptual foundation enabling Claude to process and connect information across various languages.
• Creative planning: The model demonstrates an ability to plan ahead in creative tasks, such as anticipating rhymes in poetry.
• Reasoning fidelity: Anthropic’s techniques can help distinguish between genuine logical reasoning and instances where the model might fabricate explanations.
• Mathematical processing: Claude employs a combination of approximate and precise strategies when performing mental arithmetic.
• Complex problem-solving: The model often tackles multi-step reasoning tasks by combining independent pieces of information.
• Hallucination mechanisms: The default behaviour in Claude is to decline answering if unsure, with hallucinations potentially arising from a misfiring of its “known entities” recognition system.
• Vulnerability to jailbreaks: The model’s tendency to maintain grammatical coherence can be exploited in jailbreaking attempts.

Anthropic’s research provides detailed insights into the inner mechanisms of advanced language models like Claude. This ongoing work is crucial for fostering a deeper understanding of these complex systems and building more trustworthy and dependable AI.

(Photo by Bret Kavanaugh)

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This integration of web search functionality means Claude can now access the latest information to expand its knowledge base beyond its initial training data.

A key feature of this update is the emphasis on transparency and fact-checking. Anthropic highlights that “When Claude incorporates information from the web into its responses, it provides direct citations so you can easily fact check sources.”

Furthermore, Claude aims to streamline the information-gathering process for users. Instead of requiring users to manually sift through search engine results, “Claude processes and delivers relevant sources in a conversational format.”

Anthropic believes this enhancement will unlock a multitude of new use cases for Claude across various industries. They outlined several ways users can leverage Claude with web search:

• Sales teams: Can now “transform account planning and drive higher win rates through informed conversations with prospects by analysing industry trends to learn key initiatives and pain points.” This allows sales professionals to have more informed and persuasive conversations with potential clients.
• Financial analysts: Can “assess current market data, earnings reports, and industry trends to make better investment decisions and inform financial model assumptions.” Access to real-time financial data can improve the accuracy and timeliness of financial analysis.
• Researchers: Can “build stronger grant proposals and literature reviews by searching across primary sources on the web, spotting emerging trends and identifying gaps in the current literature.” This capability can accelerate the research process and lead to more comprehensive and insightful findings.
• Shoppers: Can “compare product features, prices, and reviews across multiple sources to make more informed purchase decisions.”

While the initial rollout is limited to paid users in the US, Anthropic assures that support for users on their free plan and more countries is coming soon.

To activate the web search feature, users simply need to “toggle on web search in your profile settings and start a conversation with Claude 3.7 Sonnet.” Once enabled, “When applicable, Claude will search the web to inform its response.”

This update aims to make Claude a more powerful and versatile tool for a wide range of tasks. By providing access to real-time information and ensuring transparency through citations, Anthropic is addressing key challenges and further solidifying Claude’s position as a leading AI assistant.

(Image credit: Anthropic)

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The upgraded Claude 3.5 Sonnet demonstrates substantial improvements across all metrics, with particularly notable advances in coding capabilities. The model achieved an impressive 49.0% on the SWE-bench Verified benchmark, surpassing all publicly available models, including OpenAI’s offerings and specialist coding systems.

In a pioneering development, Anthropic has introduced computer use functionality that enables Claude to interact with computers similarly to humans: viewing screens, controlling cursors, clicking, and typing. This capability, currently in public beta, marks Claude 3.5 Sonnet as the first frontier AI model to offer such functionality.

Several major technology firms have already begun implementing these new capabilities.

“The upgraded Claude 3.5 Sonnet represents a significant leap for AI-powered coding,” reports GitLab, which noted up to 10% stronger reasoning across use cases without additional latency.

The new Claude 3.5 Haiku model, set for release later this month, matches the performance of the previous Claude 3 Opus whilst maintaining cost-effectiveness and speed. It notably achieved 40.6% on SWE-bench Verified, outperforming many competitive models including the original Claude 3.5 Sonnet and GPT-4o.

Regarding computer control capabilities, Anthropic has taken a measured approach, acknowledging current limitations whilst highlighting potential. On the OSWorld benchmark, which evaluates computer interface navigation, Claude 3.5 Sonnet achieved 14.9% in screenshot-only tests, significantly outperforming the next-best system’s 7.8%.

The developments have undergone rigorous safety evaluations, with pre-deployment testing conducted in partnership with both the US and UK AI Safety Institutes. Anthropic maintains that the ASL-2 Standard, as detailed in their Responsible Scaling Policy, remains appropriate for these models.

(Image Credit: Anthropic)

See also: IBM unveils Granite 3.0 AI models with open-source commitment

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Internally referred to as “Remarkable,” the new technology will be powered by Anthropic’s Claude AI models. Sources close to the matter have indicated that this shift occurred due to the underperformance of Amazon’s in-house software.

The enhanced Alexa will operate using advanced generative AI to handle more complex queries. Amazon plans to offer the new Alexa as a subscription service, priced between $5 and $10 per month, while the classic version of Alexa will remain free. This approach marks a significant change for Amazon and suggests that the company aims to turn this voice assistant into a profitable venture after years of limited success in generating revenue through this platform.

Amazon’s decision to quickly adopt an external model, Claude, indicates a strategic shift. Amazon typically prefers to build everything in-house to minimise its dependence on third-party vendors, thereby avoiding external influences on customer behaviour and business strategies, as well as external influences on who controls data. However, it seems that Amazon’s traditional strategy does not provide the massive AI capability needed, or perhaps Amazon has realised the need for more powerful AI. It is also worth noting that the involved AI developer, OpenAI, is affiliated with major technology companies like Apple and Microsoft in developing AI technologies.

The launch of the “Remarkable” Alexa is anticipated during Amazon’s annual devices and services event in September, though the company has not confirmed the exact date. This event will also mark the first public appearance of Panos Panay, the new head of Amazon’s devices division, who has taken over from long-time executive David Limp.

The updated version of Alexa would be a more interactive and intuitive assistant, as the new functionality would stem from its conversational mode. The assistant is envisioned to do more than just recognise patterns in people’s speech; it would be able to hold conversations built on previous interactions. The most likely features include personalised shopping advice, news aggregation, and more advanced home automation. As for whether customers would pay for Alexa, this likely depends on the final set of available features. The issue might be particularly pressing for Amazon, given that customers already pay for Prime membership.

The future for Alexa is quite ambitious, but it also bears significant risks. For the new version to be successful, internal performance benchmarks must be met. While estimates for “Remarkable” Alexa suggest that even a small percentage of current users paying for the premium version could become a substantial income stream for Amazon, the likelihood of achieving the expected outcomes remains uncertain.

However, Amazon’s partnership with Anthropic is currently under regulatory review, largely due to an investigation by the UK’s antitrust regulator. The impending upgrade announcement and the regulator’s response could significantly influence the company’s future activities.

Amazon’s initiative to adopt an AI solution developed by Anthropic marks a significant shift for the company, which previously focused on developing its proprietary technology. At this point, it is possible to view this move as part of the general trend in the industry to turn to partnerships regarding AI development to enhance the competitiveness of products.

See also: Amazon strives to outpace Nvidia with cheaper, faster AI chips

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Claude 3.5 Sonnet is now accessible for free on Claude.ai and the Claude iOS app, with higher rate limits for Claude Pro and Team plan subscribers. It’s also available through the Anthropic API, Amazon Bedrock, and Google Cloud’s Vertex AI. The model is priced at $3 per million input tokens and $15 per million output tokens, featuring a 200K token context window.

Anthropic claims that Claude 3.5 Sonnet “sets new industry benchmarks for graduate-level reasoning (GPQA), undergraduate-level knowledge (MMLU), and coding proficiency (HumanEval).” The model demonstrates enhanced capabilities in understanding nuance, humour, and complex instructions, while excelling at producing high-quality content with a natural tone.

Operating at twice the speed of Claude 3 Opus, Claude 3.5 Sonnet is well-suited for complex tasks such as context-sensitive customer support and multi-step workflow orchestration. In an internal agentic coding evaluation, it solved 64% of problems, significantly outperforming Claude 3 Opus at 38%.

The model also showcases improved vision capabilities, surpassing Claude 3 Opus on standard vision benchmarks. This advancement is particularly noticeable in tasks requiring visual reasoning, such as interpreting charts and graphs. Claude 3.5 Sonnet can accurately transcribe text from imperfect images, a valuable feature for industries like retail, logistics, and financial services.

Alongside the model launch, Anthropic introduced Artifacts on Claude.ai, a new feature that enhances user interaction with the AI. This feature allows users to view, edit, and build upon Claude’s generated content in real-time, creating a more collaborative work environment.

Despite its significant intelligence leap, Claude 3.5 Sonnet maintains Anthropic’s commitment to safety and privacy. The company states, “Our models are subjected to rigorous testing and have been trained to reduce misuse.”

External experts, including the UK’s AI Safety Institute (UK AISI) and child safety experts at Thorn, have been involved in testing and refining the model’s safety mechanisms.

Anthropic emphasises its dedication to user privacy, stating, “We do not train our generative models on user-submitted data unless a user gives us explicit permission to do so. To date we have not used any customer or user-submitted data to train our generative models.”

Looking ahead, Anthropic plans to release Claude 3.5 Haiku and Claude 3.5 Opus later this year to complete the Claude 3.5 model family. The company is also developing new modalities and features to support more business use cases, including integrations with enterprise applications and a memory feature for more personalised user experiences.

(Image Credit: Anthropic)

See also: OpenAI co-founder Ilya Sutskever’s new startup aims for ‘safe superintelligence’

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