4 AI Agents Field Test Report: 30 Days, 9 Real Office Tasks

Have you ever encountered such frustrations? Under urgent deadlines, AI-generated reports come with messy formatting, distorted data, or even entirely fabricated information. In 2025, the wave of AI Agent report writing swept across the globe. Four mainstream platforms—Genspark, Manus, OpenAI, and Comet—all claim to handle office tasks such as report writing, PPT creation, and email drafting. But which ones deliver real-world results, and which are overstating their capabilities?

A team led by Silicon Valley analyst Will Lang spent 30 days designing 9 real-world office tasks spanning finance, marketing, education, and daily life scenarios, conducting a closed-book evaluation of these four AI Agents. The final conclusion: no AI Agent is perfect, yet the gaps between them are significant enough to impact office tool choices. Below is a core summary of this field test report.

I. Why This Evaluation Matters

Amid countless AI reviews on the market, this report stands out with three key strengths that guarantee its credibility:

1. Real-scenario testing: All tasks are derived from actual office demands, not entry-level text summarization. They include high-frequency work tasks such as “predicting ETH price in the next 24 hours”, “creating a PPT for a Paris travel plan”, and “sorting out the largest single-day drops in U.S. stock market history”.
2. Quantitative data support: Time spent, success rates, and error types are recorded for each task, with evaluations based on objective data rather than subjective opinions.
3. Professional team endorsement: Will Lang’s team tracks AI products firsthand in Silicon Valley long-term, offering professional insights to accurately assess tools’ real value without being misled by marketing hype.

Basic Test Info: 4 mainstream AI Agents tested on 9 real office tasks (including 5 PPT tasks + 4 report tasks), evaluated across four dimensions: content quality, functional integrity, execution efficiency, and data authenticity.

II. Head-to-Head Showdown: Overall Results

Comprehensive task success rate serves as the core metric, with specific data as follows (source: Will Lang’s team, July 2025 test):

• Genspark: 9/9 tasks completed, 100% success rate
• OpenAI: 8/9 tasks completed, 89% success rate
• Manus: 8/9 tasks completed, 89% success rate
• Comet: 4/9 tasks completed, 44% success rate

In terms of success rate, Genspark takes the top spot, but there are many insightful details behind this result.

III. Overall Conclusion: Strengths and Weaknesses of the 4 AI Agents

Based on performance across all 9 tasks, the testing team has defined each tool’s core positioning, strengths, and weaknesses for targeted selection:

• Genspark: The all-around strongest performer with a 100% success rate and the best PPT visual design, ideal for presentations requiring high-quality visual delivery. Drawback: Export functions are still in Beta, requiring pre-testing before final delivery.
• OpenAI: Excels in in-depth analysis with the most rigorous frameworks, suitable for scenarios demanding strict logical consistency. Drawback: Poor PPT visual effects and the slowest execution speed; use with caution in time-sensitive scenarios.
• Manus: The top choice for academic and in-depth research reports, delivering the most detailed content. Drawback: High risk of data hallucinations; generated content requires line-by-line verification, following the principle of “trust but verify”.
• Comet: The fastest (completing tasks in an average of 6 minutes) and most honest, perfect for quickly generating text summaries and report drafts. Drawback: Nearly unusable for PPT tasks.

IV. 3 Eye-Opening Core Findings

1. Speed ≠ Capability: Although Comet is the fastest, it failed to genuinely complete many tasks—speed is merely an illusion. Output quality per unit time is the true benchmark.
2. “Honesty” is a rare competitive advantage: When unable to complete a task, Comet clearly informs users instead of generating flawed, fabricated results. Agents that proactively acknowledge limitations are more trustworthy.
3. AI Agents should be positioned as “junior interns”: The optimal workflow is “human task decomposition + AI execution + human final review”, boosting office efficiency by 3–5 times. Treating AI as an “independent deliverer” significantly increases risks.

V. Final Thoughts: AI Amplifies You, Not Replaces You

In 2025, the era of AI Agent report writing has truly arrived, yet no tool is mature enough for fully automated work. No platform can produce flawless content without human input. This is not a setback—those who master AI are outpacing non-users by 3–5 times.

Will Lang’s team offers 3 practical actionable tips to use AI Agents efficiently:

1. Define clear boundaries: Add constraints such as “please cite data sources” and “inform me if unable to complete” in prompts to reduce data hallucination risks.
2. Use tools in combination: Generate drafts with Genspark, deepen analysis with Manus, and verify logic with OpenAI to leverage strengths and avoid weaknesses.
3. Insist on human final review: Regardless of how polished AI output appears, data verification is indispensable—you are the final arbiter of quality.

The AI wave evolves rapidly, with tools updating constantly. Seizing this opportunity will secure an advantage in future competition.