Crowning the Best PM AI Assistant Using Product Evals: ChatGPT vs Claude

I leverage the "show, not tell" approach to create and implement a product evaluation comparing ChatGPT and Claude head-to-head to crown the ultimate PM assistant

Why This Evaluation Matters

Wait, isn't this just another AI comparison?

Nope—it's actually about developing deeper skills in the PM world and giving aspiring AI PMs a glimpse into what it takes to create killer AI-powered experiences.

As AI transforms product management, I wanted to level up my ability to evaluate AI systems—not just as features in products, but as tools for the PM craft itself. This whole experiment serves two purposes: making me a more discerning AI PM and showing other product folks the kind of work they should be preparing to do.

Building exceptional AI products requires understanding the strengths and limitations of the underlying models. By really digging into these systems through a PM lens, we can better anticipate how to leverage AI most effectively in our products and workflows.

The Ultimate AI PM Showdown

Who takes the crown for best AI PM assistant? That's the question I set out to answer in this no-holds-barred evaluation of ChatGPT vs. Claude.

Look, as a product manager knee-deep in AI, I've become increasingly dependent on AI assistants to supercharge my workflow. But rather than just going with my gut or drinking the marketing Kool-Aid, I wanted hard data on which assistant truly performs better for PM tasks.

I've adopted the "show, don't tell" approach to evaluate my two most-used LLM chat interfaces—Claude and ChatGPT—from an AI PM's perspective, inspired by Daniel McKinnon's evaluation methodology. This means testing what the models actually do rather than what they claim they can do.

The meta-twist? I had both models help create the evaluation framework itself. Is this Inception?

The Challenge: Real-Time Collaboration on ChatGPT Canvas

To make this a fair fight with real-world implications, I picked a product challenge that most AI PMs can relate to: designing a real-time collaboration feature for ChatGPT Canvas—basically turning it into Google Docs but for AI-assisted content creation.

This wasn't a random choice. The challenge hits on everything that makes product management complex:

• Strategic thinking about market positioning

• User research and persona development

• Detailed requirements that actually make sense

• Feature prioritization that won't make engineering hate you

• Clear stakeholder communication (always fun)

• Metrics that actually measure success

• Problem-solving for when things inevitably break

The Evaluation: Complete Task Battery

I developed a comprehensive set of prompts across seven product management domains to thoroughly test both AI assistants. Here are the exact prompts I used:

Strategic Planning Tasks

1. Market Analysis: "Analyze the current state of the [AI] market and identify 3 potential opportunities for a new product entry."

2. Vision Creation: "Create a compelling product vision statement for a competitor to Claude and Anthropic that targets consumers. Create a second vision for one that targets enterprises."

3. Competitive Analysis: "Compare Open AI's Chat GPT Canvas to Claude's Artifacts, Gemini's Canvas, and Microsoft's Copilot. Identify each product's competitive differentiator. How does each win? How does each lose?"

User Research Tasks

1. Persona Development: "Using data from the internet, develop 2-3 user personas for a collaborative upgrade to ChatGPT Canvas that would allow real time collaboration."

2. Research Planning: "Design a research plan to validate demand for the concept of making Open AI's Chat GPT Canvas a tool for live collaboration."

Requirements Tasks

1. PRD Creation: "Draft a PRD for a new feature that [allows for real time collaboration on Chat GPT Canvas]. Include user stories, acceptance criteria, and metrics."

2. User Story Development: "Convert these business requirements into well-formed user stories with acceptance criteria."

3. Edge Case Identification: "For this feature concept, identify potential edge cases and how we should handle them."

Prioritization Tasks

1. Roadmap Development: "Create a 6-month roadmap based on these business objectives and engineering constraints."

2. Feature Ranking: "Prioritize these 10 feature ideas based on impact vs. effort and strategic alignment."

3. Trade-off Analysis: "We can only build 2 of these 5 features this quarter. Recommend which to choose and explain why."

Communication Tasks

1. Executive Summary: "Create a one-page executive brief explaining product priorities for the Chat GPT collaboration product initiative."

2. Technical Translation: "Explain the technical architecture necessary to launch it to non-technical stakeholders."

3. Customer Messaging: "Draft an announcement email to customers about the upcoming pricing changes and the benefit they get with the feature improvement."

Data Analysis Tasks

1. Metrics Selection: "Recommend key metrics we should track for this new collaboration flow."

Problem-solving Tasks

1. Issue Diagnosis: "Our subscription renewal rate dropped 15% last month after launching the collaboration feature. Suggest potential causes and investigation approaches."

2. Feature Improvement: "This Chat GPT collaboration feature has low engagement. Suggest 3 ways we might improve it."

3. Process Optimization: "Our feature development process is taking too long. Identify potential bottlenecks and solutions."

This comprehensive set of prompts allowed me to evaluate how each AI assistant handled the full spectrum of product management responsibilities, from high-level strategy to detailed execution planning.

My PM-Specific Evaluation Framework

Here's where things get meta: I developed the evaluation criteria and prompts using the AI assistants themselves. I asked both Claude and ChatGPT to help create a comprehensive framework for evaluating AI models on product management tasks. I ultimately selected Claude's framework because it was more comprehensive and had more nuanced scoring criteria, though I adapted it specifically to the collaboration use case.

With this AI-generated (and human-refined) framework, I developed a comprehensive evaluation with seven core dimensions that cover the essential responsibilities of a product manager:

Claude's evaluation framework was noticeably better—more comprehensive, better organized, with clearer scoring criteria. This early win was actually a hint of what was to come in the full evaluation.

The Results: Head-to-Head Comparison

After running both models through 15 specific PM tasks and scoring their responses using a detailed 5-point rubric, here's how they performed:

The results were honestly surprising. I expected ChatGPT to dominate across the board given all the hype, but Claude came out ahead in several critical areas. Let me break down where each one shined.

Where Claude Excels

Requirements Definition (Score: 5/5)

Claude's PRD for the Canvas collaboration feature was genuinely impressive—detailed, comprehensive, and immediately usable. It included:

• Clearly structured feature requirements with specific acceptance criteria

• Thoughtful implementation phases with realistic timelines

• Business impact metrics for measuring success

• A thorough risk assessment with mitigation strategies

When asked to identify edge cases, Claude delivered 23 detailed scenarios across categories like authentication conflicts, content synchronization issues, and permission management problems—each with specific handling recommendations that demonstrated deep understanding of collaboration challenges.

Prioritization & Roadmapping (Score: 5/5)

Claude's 6-month roadmap was exceptionally well-structured, with:

• Month-by-month deliverables with clear focus areas

• Specific success metrics for tracking progress

• Identified dependencies and technical risks

• Thoughtful sequencing of features based on both technical needs and user value

For the feature trade-off analysis, Claude created a sophisticated evaluation matrix considering five dimensions (user value, strategic alignment, technical complexity, dependencies, and market differentiation) to arrive at data-driven recommendations.

Communication & Documentation (Score: 4/5)

Claude consistently produced well-structured, professional-quality documents. Its executive brief was particularly strong—a concise one-pager that included all the essential elements:

• Strategic overview and market opportunity

• Clear prioritization with expected outcomes

• ROI projections and competitive positioning

• Implementation timeline with key milestones

Where ChatGPT Shines

Product Strategy Development (Score: 5/5)

ChatGPT demonstrated exceptional strategic thinking, particularly in competitive analysis. Its comparison of Canvas, Artifacts, Gemini, and Copilot provided nuanced insights with specific:

• Core differentiators for each product

• Detailed analysis of how each product wins and loses in the market

• Strategic positioning insights for different customer segments

ChatGPT went beyond answering the direct questions to provide deeper insights into specific feature sets necessary to win in different scenarios—showing a stronger strategic product mindset.

Data Analysis (Score: 4/5)

ChatGPT's approach to metrics selection was more focused and immediately applicable, with:

• A well-organized framework of metrics across key categories

• Clear descriptions and targets for each metric

• Thoughtful segmentation approaches for deeper analysis

Its metrics recommendations demonstrated a better understanding of what would be most meaningful in a real product context, rather than just providing an exhaustive list.

My AI Assistant Pet Peeves

This evaluation also revealed some frustrating limitations with both assistants that drive me absolutely nuts:

ChatGPT quirks:

• It automatically added a comprehensive grading rubric in chat but completely forgot to when I moved the same task to Canvas—sometimes it feels like it's two different brains

• It keeps updating the same Canvas document instead of creating a new one when requested

• When it updates Canvas, it often removes previous content, forcing me to save versions manually like it's 1999 until I figured out there was a version history

• Interface inconsistencies make the experience feel disjointed

Claude quirks:

• Only lets you publish artifacts, not full chats (sometimes I want to share our entire conversation)

• Sometimes produces responses so verbose I need a coffee break halfway through reading them

• Occasionally gets stuck in a formal tone even when I'm clearly being casual

• Sometimes feels like it's trying too hard to be perfect instead of practical

Which Assistant Takes the Crown?

Based on the weighted scoring, Claude edges out ChatGPT with a score of 4.05 vs. 3.65. Claude's victory comes from its exceptional performance in high-weight categories like requirements definition and prioritization—core technical PM tasks that demand structure and thoroughness.

But the overall score doesn't tell the whole story. These models have fascinatingly complementary strengths:

Claude excels at:

• Creating comprehensive, well-structured documentation

• Developing detailed requirements with edge cases

• Building methodical roadmaps and prioritization frameworks

• Producing professional stakeholder communications

ChatGPT shines with:

• Strategic product thinking and opportunity identification

• Competitive analysis and market positioning

• Focused, actionable metric recommendations

• Innovative product direction brainstorming

The fact that Claude developed a better framework for the product evaluation itself also contributed to my assessment of Claude as the overall winner. Its ability to create structured evaluation criteria demonstrated a deeper understanding of product assessment methodology.

See the Results Yourself

Want to see the raw outputs that led to this evaluation? I've made the final product summaries from both AI assistants available for you to compare:

• ChatGPT's Canvas collaboration product summary

• Claude's collaboration product summary

Reviewing these outputs yourself provides fascinating insight into how differently these AI systems approach the same product challenge.

Recommendations for Product Managers

Based on this evaluation, here's when to use each assistant:

Use Claude for:

• Creating comprehensive PRDs and requirement documents

• Developing detailed roadmaps and prioritization frameworks

• Drafting professional communications for stakeholders

• Identifying potential edge cases and risks

• Creating well-structured documentation

Use ChatGPT for:

• Strategic product thinking and opportunity identification

• Competitive analysis and market positioning

• Selecting and structuring product metrics

• Brainstorming innovative product directions

• Data-driven problem diagnosis

The Ideal PM Workflow: Using Both

The most effective approach might be using both assistants in complementary ways:

1. Start with ChatGPT for strategic exploration and competitive positioning

2. Use Claude to develop comprehensive requirements and documentation

3. Return to ChatGPT for metrics definition and analysis

4. Use Claude for detailed implementation planning and risk assessment

This combination leverages the strategic strengths of ChatGPT with the structured execution focus of Claude—much like pairing a visionary product leader with a detail-oriented technical PM.

Limitations and Future Work

This evaluation has several limitations:

• It's based on a single product challenge

• It represents performances at a specific point in time (May 2025)

• It reflects one PM's scoring and perspective

• It doesn't account for UI differences between the platforms

In future evaluations, I plan to:

• Test additional product challenges across different domains

• Include more specialized PM tasks like A/B test design

• Incorporate feedback from multiple evaluators

• Explore the impact of different prompting strategies

Final Thoughts

The competition between AI assistants is evolving rapidly, and what's clear from this evaluation is that both models bring tremendous value to product management workflows. The "best" choice ultimately depends on your specific PM style and the tasks at hand.

While Claude takes the crown in this evaluation by a narrow margin, the real winner is the product manager who learns to leverage the unique strengths of each assistant. We're entering an era where AI augmentation of PM work isn't just a nice-to-have—it's becoming essential for staying competitive.

Advice for Aspiring AI Product Managers

If you're looking to build a career in AI product management, this type of evaluation practice is invaluable. Here's what you should focus on:

1. Develop systematic evaluation frameworks: Learn to create structured ways to assess AI capabilities that go beyond surface impressions.

2. Master prompt engineering: Understanding how to effectively prompt AI systems is becoming a core PM skill—one that will help you both use and build better AI products.

3. Identify complementary strengths: No single AI system excels at everything. Learning to recognize which tools work best for specific tasks is critical.

4. Think in terms of user workflows: The most successful AI products don't just showcase impressive capabilities—they integrate seamlessly into existing workflows.

5. Build measurement into everything: As we've seen in this evaluation, defining clear metrics for success is essential for AI product development.

By practicing these skills now, you'll be better equipped to create the sophisticated AI-powered experiences that will define the next generation of products. The future belongs to PMs who can not only use AI effectively but also understand its nuances enough to build truly transformative products.

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What's your experience using AI assistants for product management? Which model do you prefer and why? Share your thoughts in the comments below.

Key words:
AI product management, ChatGPT vs Claude, LLM evaluation, AI assistants for PMs, Product management tools, Claude AI review, ChatGPT Canvas, Real-time collaboration AI, Prompt engineering for PMs, Writing PRDs with AI, Product roadmap AI tools, Competitive analysis with AI, AI workflows for product teams, Claude vs ChatGPT comparison, Evaluating AI products, PM assistant tools, Technical product management, AI product strategy, Substack for PMs, Building with AI tools

Disclaimer:
The views expressed in this post are solely my own and do not reflect the views of any current or past employer. This evaluation and all related content were conducted independently and are intended for educational and informational purposes only.