Research buying a yak
AI with ALLIE. Task: AI with ALLIE Posts My personal review of 10+ AI agents and what actually works The AI Agents Report Card you wish your boss gave you. Allie K. Miller May 15, 2025 AI with ALLIE The professional’s guide to quick AI bites for your personal life, work life, and beyond. What you'll learn in this newsletter: Which AI agents actually deliver value right now Which AI agents actually deliver value right now Where even the best agents still fall embarrassingly short Where even the best agents still fall embarrassingly short The surprising truth about those sleek, impressive interfaces The surprising truth about those sleek, impressive interfaces The economics of delegating to AI (and when it's worth the premium) The economics of delegating to AI (and when it's worth the premium) Five practical takeaways to guide your AI strategy Five practical takeaways to guide your AI strategy Hey cyborgs, What if AI could just handle tasks for you? Plan a week's worth of perfect meals, generate a detailed competitor analysis, or intelligently reschedule your entire day when one meeting shifts—all without you lifting a finger? An AI agent, or thousands of AI agents, that can reason through its own steps and execute on your behalf would be pretty life-changing… I've been on an AI agent testing spree lately, and I dragged my entire team along for the ride. Last month, I assigned everyone to test at least two different AI agents and come back with demos to share and very opinionated first impressions on design, process, flow, performance, speed, and accuracy. After watching presentations, comparing notes, and hashing out what worked (and mostly what didn't), we've uncovered some fascinating insights about where these digital helpers actually stand today. Allie note: you can steal my idea and have your team test AI agents too! Since many AI agent platforms cost money because it’s a more expensive workflow to run, I gave everyone a $100 budget—you can scale yours accordingly. You can also provide a list of agents that you’re interested in your team testing. I would also recommend a quick primer of your company AI policy prior to this test, as well as discussing as a group potential use cases you might have internally. If you plan on using these in work scenarios that require company data, it is a safer test to provide your employees or small team with a set of documents with fake data. The dream is seductive, but I’m just going to rip the bandaid off here, we're definitely living in the awkward teenage years of AI agents. They show flashes of brilliance followed by face-palm moments of utter incompetence. And if you haven’t watched my Intro to AI Agents primer, you need to start there. Our Testing Team Goes Wild Our testing covered a broad range of players in the AI agent space, from the giants to the newcomers: Operator (from OpenAI/ChatGPT) Operator (from OpenAI/ChatGPT) Claude Computer Use Claude Computer Use Perplexity AI Assistant Perplexity AI Assistant Lindy AI Lindy AI Manus AI Manus AI Proxy by Convergence Proxy by Convergence Clay AI Clay AI You.com ARI You.com ARI ChatGPT's Deep Research ChatGPT's Deep Research Microsoft Copilot AI Agents (pre-built) Microsoft Copilot AI Agents (pre-built) Microsoft Copilot AI Agents (DIY) Microsoft Copilot AI Agents (DIY) Plus Project Mariner and Agentspace (unreleased from Google) Plus Project Mariner and Agentspace (unreleased from Google) Each team member approached testing with different real-world scenarios—from selling jewelry to custom-framing art, scheduling personal errands around work meetings to gathering sales intelligence. Let's dive into what we discovered. Task-Focused Agents These tools aim to execute specific tasks with varying levels of autonomy. Operator earned a solid B-/C+ in our testing. It works for quick, straightforward tasks but lacks nuance. One team member used it to find a gluten-free restaurant near a concert venue in Minneapolis and successfully made a reservation (that’s a big deal!). Another tested it to find options for selling a unique piece of jewelry, though the results left her uncertain whether she was getting the best value. This Operator highlights a key insight that would reappear throughout our testing: AI agents excel when you need a solution (any decent restaurant nearby) but fall apart when you want the perfect solution.; tools: Manus. Human role: The original post does not say how a person stayed involved.; limitations: Manus requires significant human oversight; it is not fully autonomous and often needs manual redirection. Costs are high compared to alternatives like ChatGPT. Research tools struggle with follow-up refinement, chronological order, and spatial reasoning. Users must verify all data, especially for regulated items like livestock, as AI agents may hallucinate or miss critical compliance details..
Tools
Published on Agent Work Atlas:
Overview
AI with ALLIE
Workflow
AI with ALLIE Posts My personal review of 10+ AI agents and what actually works The AI Agents Report Card you wish your boss gave you. Allie K. Miller May 15, 2025 AI with ALLIE The professional’s guide to quick AI bites for your personal life, work life, and beyond. What you'll learn in this newsletter: Which AI agents actually deliver value right now Which AI agents actually deliver value right now Where even the best agents still fall embarrassingly short Where even the best agents still fall embarrassingly short The surprising truth about those sleek, impressive interfaces The surprising truth about those sleek, impressive interfaces The economics of delegating to AI (and when it's worth the premium) The economics of delegating to AI (and when it's worth the premium) Five practical takeaways to guide your AI strategy Five practical takeaways to guide your AI strategy Hey cyborgs, What if AI could just handle tasks for you? Plan a week's worth of perfect meals, generate a detailed competitor analysis, or intelligently reschedule your entire day when one meeting shifts—all without you lifting a finger? An AI agent, or thousands of AI agents, that can reason through its own steps and execute on your behalf would be pretty life-changing… I've been on an AI agent testing spree lately, and I dragged my entire team along for the ride. Last month, I assigned everyone to test at least two different AI agents and come back with demos to share and very opinionated first impressions on design, process, flow, performance, speed, and accuracy. After watching presentations, comparing notes, and hashing out what worked (and mostly what didn't), we've uncovered some fascinating insights about where these digital helpers actually stand today. Allie note: you can steal my idea and have your team test AI agents too! Since many AI agent platforms cost money because it’s a more expensive workflow to run, I gave everyone a $100 budget—you can scale yours accordingly. You can also provide a list of agents that you’re interested in your team testing. I would also recommend a quick primer of your company AI policy prior to this test, as well as discussing as a group potential use cases you might have internally. If you plan on using these in work scenarios that require company data, it is a safer test to provide your employees or small team with a set of documents with fake data. The dream is seductive, but I’m just going to rip the bandaid off here, we're definitely living in the awkward teenage years of AI agents. They show flashes of brilliance followed by face-palm moments of utter incompetence. And if you haven’t watched my Intro to AI Agents primer, you need to start there. Our Testing Team Goes Wild Our testing covered a broad range of players in the AI agent space, from the giants to the newcomers: Operator (from OpenAI/ChatGPT) Operator (from OpenAI/ChatGPT) Claude Computer Use Claude Computer Use Perplexity AI Assistant Perplexity AI Assistant Lindy AI Lindy AI Manus AI Manus AI Proxy by Convergence Proxy by Convergence Clay AI Clay AI You.com ARI You.com ARI ChatGPT's Deep Research ChatGPT's Deep Research Microsoft Copilot AI Agents (pre-built) Microsoft Copilot AI Agents (pre-built) Microsoft Copilot AI Agents (DIY) Microsoft Copilot AI Agents (DIY) Plus Project Mariner and Agentspace (unreleased from Google) Plus Project Mariner and Agentspace (unreleased from Google) Each team member approached testing with different real-world scenarios—from selling jewelry to custom-framing art, scheduling personal errands around work meetings to gathering sales intelligence. Let's dive into what we discovered. Task-Focused Agents These tools aim to execute specific tasks with varying levels of autonomy. Operator earned a solid B-/C+ in our testing. It works for quick, straightforward tasks but lacks nuance. One team member used it to find a gluten-free restaurant near a concert venue in Minneapolis and successfully made a reservation (that’s a big deal!). Another tested it to find options for selling a unique piece of jewelry, though the results left her uncertain whether she was getting the best value. This Operator highlights a key insight that would reappear throughout our testing: AI agents excel when you need a solution (any decent restaurant nearby) but fall apart when you want the perfect solution.
Reported result
The source does not report specific outcomes for the yak purchase, only that the author used Manus for this task. Manus is described as the best performer in task-focused testing but is expensive ($4 per task) and slow (15 minutes per prompt). It excels at finding 'good enough' solutions but fails at optimizing for perfect results. No verified success metrics for the yak research are provided.
Human role
The original post does not say how a person stayed involved.
Limitations
Manus requires significant human oversight; it is not fully autonomous and often needs manual redirection. Costs are high compared to alternatives like ChatGPT. Research tools struggle with follow-up refinement, chronological order, and spatial reasoning. Users must verify all data, especially for regulated items like livestock, as AI agents may hallucinate or miss critical compliance details.
Try it
I want to use Manus AI to research the feasibility of buying a [specific animal/item, e.g., yak] for [purpose, e.g., farm use] in [location]. First, define the key constraints: [budget range], [required certifications], and [import/export rules]. Instruct Manus to search for reputable breeders, current market prices, and regulatory requirements. Ask it to summarize findings in a table with columns for Vendor, Price, Location, and Compliance Status. Crucially, do not let Manus execute any purchases or send messages. Review the output for hallucinations or missing data. If the agent gets stuck, manually redirect it or take over the search. Verify all vendor credentials and legal requirements independently before proceeding. Start with a small sample query to test Manus's accuracy and cost-efficiency before running a full research task.
Source reports are not independently verified. Publication date is the catalog publication date, not the original article date.