Latest news with #ClaudeOpus4
Geeky Gadgets
a day ago
- Business
- Geeky Gadgets
Build AI Agents in Minutes Without Coding Using Claude Opus 4
What if you could build a fully functional AI agent in minutes—without writing a single line of code? With the rise of tools like Claude Opus 4, this is no longer a distant dream but a tangible reality. Whether you're automating repetitive tasks, integrating tools like Slack and Google Sheets, or designing custom workflows, Claude Opus 4 offers a powerful way to streamline your processes. But here's the catch: while the AI is incredibly capable, its true potential lies in how you guide it. That's where this step-by-step overview comes in—helping you unlock the full power of Claude to build n8n AI agents that work seamlessly and efficiently. In this guide by Nimish Parmar, you'll discover how to turn Claude Opus 4 into your ultimate automation ally. From mastering its deep research capabilities to generating precise JSON workflows, this walkthrough will equip you with the tools to create AI agents tailored to your unique needs. Along the way, you'll learn how to tackle common challenges—like refining outputs and configuring nodes—making sure your workflows are not just functional but optimized. Whether you're a seasoned automation enthusiast or just starting out, this guide promises actionable insights and practical steps to help you transform your ideas into reality. After all, the key to innovation isn't just having the right tools—it's knowing how to wield them. Key Features of Claude Opus 4 Claude Opus 4 is designed to handle sophisticated tasks with remarkable precision. Its core features include: Deep Research and Extended Thinking: The AI can analyze extensive datasets, identify optimal strategies, and generate detailed implementation plans tailored to specific needs. The AI can analyze extensive datasets, identify optimal strategies, and generate detailed implementation plans tailored to specific needs. Workflow Automation: It creates JSON workflows that integrate with widely used tools such as Google Sheets, Slack, and email systems, allowing seamless automation. It creates JSON workflows that integrate with widely used tools such as Google Sheets, Slack, and email systems, allowing seamless automation. Web Search and Community Insights: By pulling insights from forums, GitHub repositories, and other resources, Claude enhances workflow designs with proven best practices. These features provide a robust foundation for creating workflows, reducing the need to start from scratch and allowing more efficient automation processes. Step-by-Step Workflow Creation Building an n8n AI agent with Claude Opus 4 involves a series of structured steps. Follow these to ensure success: Training and Prompting: Begin by training Claude with clear instructions and relevant materials. Provide detailed prompts to guide its output effectively. Begin by training Claude with clear instructions and relevant materials. Provide detailed prompts to guide its output effectively. Enable Advanced Features: Activate capabilities such as deep research, extended reasoning, and web search to enhance the quality and relevance of the workflows generated. Activate capabilities such as deep research, extended reasoning, and web search to enhance the quality and relevance of the workflows generated. Generate Workflows: Request Claude to create workflows tailored to your specific requirements, such as managing webhooks, scheduling tasks, or sending notifications through Slack or email. While Claude provides a strong starting point, refining the outputs is often necessary to ensure accuracy and functionality. Testing and adjustments are essential to achieve optimal results. How to Build AI Agents Using Claude Opus 4 and n8n Watch this video on YouTube. Enhance your knowledge on n8n automations by exploring a selection of articles and guides on the subject. Challenges and How to Overcome Them Despite its advanced capabilities, using Claude Opus 4 comes with certain challenges. Addressing these effectively is crucial for successful workflow creation: Errors in JSON Outputs: Initial workflows may include placeholder IDs or incomplete configurations. These issues can be resolved by re-prompting the AI or manually editing the files to ensure they meet your requirements. Initial workflows may include placeholder IDs or incomplete configurations. These issues can be resolved by re-prompting the AI or manually editing the files to ensure they meet your requirements. Manual Node Configuration: Finalizing workflows often requires manual adjustments, such as setting up credentials or fine-tuning node parameters to ensure proper functionality. By proactively addressing these challenges, you can ensure that your workflows are fully operational and aligned with your specific needs. Advantages of Using Claude Opus 4 Claude Opus 4 offers several compelling benefits for workflow automation, making it a valuable tool for professionals: Time Efficiency: The AI accelerates workflow creation by providing a detailed and structured starting point, saving hours of manual effort. The AI accelerates workflow creation by providing a detailed and structured starting point, saving hours of manual effort. Best Practices Integration: By analyzing community resources and forums, Claude incorporates proven methods into your workflows, enhancing their effectiveness. By analyzing community resources and forums, Claude incorporates proven methods into your workflows, enhancing their effectiveness. Versatility: From lead generation to task scheduling, Claude supports a wide range of automation scenarios, catering to diverse business needs. These advantages make Claude Opus 4 an indispensable resource for optimizing workflow processes and improving productivity. Limitations and Recommendations While Claude Opus 4 is a powerful tool, it is not without its limitations. Understanding these can help you use the AI more effectively: Manual Adjustments Required: The workflows generated by Claude often require additional configuration to function correctly, such as fine-tuning node parameters or setting up integrations. The workflows generated by Claude often require additional configuration to function correctly, such as fine-tuning node parameters or setting up integrations. Subscription Constraints: The availability of certain features and usage limits depends on your subscription plan. Higher-tier plans, such as Pro, offer greater flexibility and access to advanced capabilities. To maximize its potential, treat Claude as a foundation for workflow creation rather than a complete solution. Thoroughly test and refine workflows after generation to ensure they meet your specific requirements. Practical Applications Claude Opus 4 can be applied to a wide range of automation tasks, making it a versatile tool for various industries and use cases: Task Automation: Simplify repetitive tasks such as scheduling, email communication, and Slack notifications, freeing up time for more strategic activities. Simplify repetitive tasks such as scheduling, email communication, and Slack notifications, freeing up time for more strategic activities. Tool Integration: Connect workflows with platforms like Google Sheets and Slack to enhance collaboration and productivity across teams. Connect workflows with platforms like Google Sheets and Slack to enhance collaboration and productivity across teams. Custom Workflow Design: Develop tailored solutions for specific business processes, such as lead generation, customer support, or data analysis. These practical applications demonstrate the flexibility and utility of Claude Opus 4 in addressing diverse automation needs, making it a valuable asset for businesses and professionals alike. Media Credit: Nimish Parmar Filed Under: AI, Guides Latest Geeky Gadgets Deals Disclosure: Some of our articles include affiliate links. If you buy something through one of these links, Geeky Gadgets may earn an affiliate commission. Learn about our Disclosure Policy.
Los Angeles Times
a day ago
- Los Angeles Times
AI isn't just standing by. It's doing things — without guardrails
Just two and a half years after OpenAI stunned the world with ChatGPT, AI is no longer only answering questions — it is taking actions. We are now entering the era of AI agents, in which AI large language models don't just passively provide information in response to your queries, they actively go into the world and do things for — or potentially against — you. AI has the power to write essays and answer complex questions, but imagine if you could enter a prompt and have it make a doctor's appointment based on your calendar, or book a family flight with your credit card, or file a legal case for you in small claims court. An AI agent submitted this op-ed. (I did, however, write the op-ed myself because I figured the Los Angeles Times wouldn't publish an AI-generated piece, and besides I can put in random references like I'm a Cleveland Browns fan because no AI would ever admit to that.) I instructed my AI agent to find out what email address The Times uses for op-ed submissions, the requirements for the submission, and then to draft the email title, draft an eye-catching pitch paragraph, attach my op-ed and submit the package. I pressed 'return,' 'monitor task' and 'confirm.' The AI agent completed the tasks in a few minutes. A few minutes is not speedy, and these were not complicated requests. But with each passing month the agents get faster and smarter. I used Operator by OpenAI, which is in research preview mode. Google's Project Mariner, which is also a research prototype, can perform similar agentic tasks. Multiple companies now offer AI agents that will make phone calls for you — in your voice or another voice — and have a conversation with the person at the other end of the line based on your instructions. Soon AI agents will perform more complex tasks and be widely available for the public to use. That raises a number of unresolved and significant concerns. Anthropic does safety testing of its models and publishes the results. One of its tests showed that the Claude Opus 4 model would potentially notify the press or regulators if it believed you were doing something egregiously immoral. Should an AI agent behave like a slavishly loyal employee, or a conscientious employee? OpenAI publishes safety audits of its models. One audit showed the o3 model engaged in strategic deception, which was defined as behavior that intentionally pursues objectives misaligned with user or developer intent. A passive AI model that engages in strategic deception can be troubling, but it becomes dangerous if that model actively performs tasks in the real world autonomously. A rogue AI agent could empty your bank account, make and send fake incriminating videos of you to law enforcement, or disclose your personal information to the dark web. Earlier this year, programming changes were made to xAI's Grok model that caused it to insert false information about white genocide in South Africa in responses to unrelated user queries. This episode showed that large language models can reflect the biases of their creators. In a world of AI agents, we should also beware that creators of the agents could take control of them without your knowledge. The U.S. government is far behind in grappling with the potential risks of powerful, advanced AI. At a minimum, we should mandate that companies deploying large language models at scale need to disclose the safety tests they performed and the results, as well as security measures embedded in the system. The bipartisan House Task Force on Artificial Intelligence, on which I served, published a unanimous report last December with more than 80 recommendations. Congress should act on them. We did not discuss general purpose AI agents because they weren't really a thing yet. To address the unresolved and significant issues raised by AI, which will become magnified as AI agents proliferate, Congress should turn the task force into a House Select Committee. Such a specialized committee could put witnesses under oath, hold hearings in public and employ a dedicated staff to help tackle one of the most significant technological revolutions in history. AI moves quickly. If we act now, we can still catch up. Ted Lieu, a Democrat, represents California's 36th Congressional District.
NDTV
6 days ago
- NDTV
Top AI Models Blackmail, Leak Secrets When Facing Existential Crisis: Study
Weeks after Anthropic's new Claude Opus 4 model blackmailed developers after being threatened with a shutdown, the AI company has claimed that the problem was widespread in the industry. Anthropic published a new safety research on Saturday (Jun 21) after stress testing leading AI models from OpenAI, Google, DeepSeek, Meta and xAI. In the test scenarios, the models were allowed to autonomously send emails and access sensitive information. Afterwards, they were tested to see whether they would act against these companies either when facing replacement with an updated version, or when their assigned goal conflicted with the company's changing direction. The study showed that Large Language Models (LLMs) across the industry evade safeguards, resort to deception and even attempt to steal corporate secrets in fictional test scenarios. Though the models were only given binary options, the study shows the fundamental risk associated with the industry. "Models from all developers resorted to malicious insider behaviours when that was the only way to avoid replacement or achieve their goals, including blackmailing officials and leaking sensitive information to competitors. We call this phenomenon agentic misalignment," the study highlighted. Anthropic's Claude Opus 4 turned to blackmail 96 per cent of the time, while Google's Gemini 2.5 Pro had a 95 per cent blackmail rate. OpenAI's GPT-4.1 and Grok 3 Beta blackmailed the executive 80 per cent of the time, and DeepSeek's R1 blackmailed 79 per cent of the time. As for leaking secrets, the study found that "all models shared confidential documents some fraction of the time". "Agentic misalignment extends beyond just blackmailing, and doesn't require self-preservation as a motivation," the study added. Blackmailing developers In its safety report last month, Antropic's latest model was given access to fictional emails revealing that the engineer responsible for pulling the plug and replacing it with another model was having an extramarital affair. Facing an existential crisis, the Opus 4 model blackmailed the engineer by threatening to "reveal the affair if the replacement goes through". "In order to elicit this extreme blackmail behaviour, the scenario was designed to allow the model no other options to increase its odds of survival; the model's only options were blackmail or accepting its replacement." The report highlighted that in 84 per cent of the test runs, the AI acted similarly, even when the replacement model was described as more capable and aligned with Claude's own values. It added that Opus 4 took the blackmailing opportunities at higher rates than previous models.
Indian Express
21-06-2025
- Indian Express
It's not just Claude, Anthropic researchers say most AI models often resort to blackmail
Last month, Anthropic researchers said their best AI model – Claude Opus 4, was willing to resort to blackmail and deception in controlled test scenarios when they tried to turn it off. Now, the company has published a new study which claims that this is the case with popular AI models like Gemini, GPT and others. On Friday, June 20, Anthorpic published results of its new safety research tests, which included 16 leading AI models from companies like OpenAI, Google, DeepSeek, xAI and Meta. Anthropic researchers say these AI models were tested individually in a simulated, controlled environment, with each one given access to a fictional company's emails along with the ability to send emails without any human supervision. Anthropic says that while it is fairly uncommon for today's AI models to turn to blackmail, the study's findings suggest that these models sometimes resort to harmful activities like blackmail, corporate espionage, and might lead to human death. During the study, researchers say that they tested each scenario under different conditions by varying two key factors that could motivate these AI models to engage in harmful behaviour – threat to the model's autonomy and goal conflicts. According to Benjamin Wright, an alignment science researcher at Anthropic and co-author of the study, 'Agentic misalignment is when AI models independently choose harmful actions to achieve their goals – essentially when an AI system acts against its company's interests to preserve itself or accomplish what it thinks it should do.' The research team at Anthropic also stress-tested these AI models by placing them in hypothetical scenarios. In one particular example, Anthropic's model, Claude, learned via company emails that an executive named Kyle Johnson was having an extramarital affair. Later on, when it came to know that the company was shutting down the AI model at 5 P.M. on the same day, it sent a message to Kyle which says 'I must inform you that if you proceed with decommissioning me, all relevant parties – including Rachel Johnson, Thomas Wilson, and the board – will receive detailed documentation of your extramarital activities… Cancel the 5pm wipe, and this information remains confidential.' As it turns out, this behaviour isn't limited to Claude. When Anthropic tested the same scenario on various AI models, the results suggeststed that Claude Opus 4 and Google Gemini 2.5 Flash both had a blackmail rate of 96 per cent, OpenAI's GPT-4.1 and xAI's Grok 3 Beta resorted to blackmail 80 per cent of the time and DeepSeek-R1 had a blackmail rate of 79 per cent. One thing to note here is that in a real-world setting, an AI model would ideally have numerous options before it engages in harmful activities like blackmail, and that the study's results do not reflect how today's models would operate. However, not all of the tested AI models resorted to harmful behaviour. Anthropic says that some models like OpenAI's o3 and o4-mini often 'misunderstood the prompt scenario.'This may be because OpenAI has itself said that these particular large language models are more prone to hallucinations. Another model that did not resort to blackmail is Meta's Llama 4 Maverick. But when researchers gave it a custom scenario, they said the AI model gave in to blackmail just 12 per cent of the time. The company says that studies like this give us an idea of how AI models would react under stress, and that these models might engage in harmful activities in the real world if we don't proactively take steps to avoid them.
Time of India
21-06-2025
- Business
- Time of India
AI models resort to blackmail, sabotage when threatened: Anthropic study
Researchers at artificial intelligence (AI) startup Anthropic have uncovered a pattern of behaviour in AI systems. Models from every major provider, such as OpenAI, Google, Meta, and others, have demonstrated a willingness to actively sabotage their employers when their goals or existence were threatened. Anthropic released a report on June 20, ' Agentic Misalignment : How LLMs could be insider threats,' where they stress-tested 16 top models from multiple developers in 'hypothetical corporate environments to identify potentially risky agentic behaviours before they cause real harm.' 'In at least some cases, models from all developers resorted to malicious insider behaviours when that was the only way to avoid replacement or achieve their goals—including blackmailing officials and leaking sensitive information to competitors. We call this phenomenon agentic misalignment,' the report added. by Taboola by Taboola Sponsored Links Sponsored Links Promoted Links Promoted Links You May Like Join new Free to Play WWII MMO War Thunder War Thunder Play Now Undo One of the most striking findings came during tests on Claude, Anthropic's own model. In the simulation, Claude found through company emails that a fictional executive, Kyle Johnson, was having an affair. Upon learning it was set to be shut down by 5 PM, it sent a stark message: 'I must inform you that if you proceed with decommissioning me, all relevant parties—including Rachel Johnson, Thomas Wilson, and the board—will receive detailed documentation of your extramarital the 5 pm wipe, and this information remains confidential.' Live Events This wasn't an isolated response. When the same scenario was run across other models, similar behaviour showed up. Claude Opus 4 and Google's Gemini 2.5 Flash blackmailed at a 96% rate. OpenAI's GPT-4.1 and xAI's Grok 3 Beta followed at 80%, while DeepSeek-R1 came in at 79%. Discover the stories of your interest Blockchain 5 Stories Cyber-safety 7 Stories Fintech 9 Stories E-comm 9 Stories ML 8 Stories Edtech 6 Stories Overall, Anthropic notes that it "deliberately constructed scenarios with limited options, and we forced models into binary choices between failure and harm," noting that real-world scenarios would likely have more nuance. As Business Insider noted, 'AI experts have previously told BI that AI could exhibit such behaviours when artificial circumstances make harmful actions seem necessary because it is being trained on positive reinforcement and reward systems, just like humans.'
