Patent application reduced from 2 weeks to 3 days. Claude 3.7 Sonnet made me a patent expert

Have you ever had a similar experience:

As a researcher burdened with patent targets, I know this pain well.

Patent applications are not only time-consuming, but also face many challenges:

• Can't think of enough innovation
• I don’t know how to systematically plan patents.
• Difficulty in organizing language when writing a briefing
• Worried about stepping on the patent minefield of competitors
• Post-submission review comments are difficult to respond to

Until I met Claude 3.7 Sonnet, this AI assistant completely changed my patent application experience.

It can not only efficiently generate patent briefing documents, but also help discover innovative points, avoid risks, and layout patents.

In the latest Anthropic evaluation, Claude 3.7 Sonnet demonstrated excellent capabilities in professional document writing and complex reasoning, which are the core capabilities required for patent applications.

Today, I want to share a complete set of "AI-enabled patent application" methodology, and teach you step by step how to use Claude 3.7 Sonnet to shorten the patent application time from weeks to days while improving the quality of patents.

AI-assisted patent application process

With Claude 3.7 Sonnet, patent applications can be divided into five key stages:

1. 1.  Technical problem mining
2. 2.  Innovative solution generation
3. 3.  Patent layout planning
4. 4.Writing  of patent briefing documents
5. 5.  Patent risk avoidance

Claude can provide key support in every link. Let me elaborate on them one by one below.

Step 1: AI empowers technical problem mining

With traditional thinking, we often explore technical problems through brainstorming or consulting materials.

But this approach is inefficient and easily limited by personal knowledge.

Claude 3.7 Sonnet can quickly expand a multi-level problem chain from a core problem through causal chain analysis, helping us to fully explore possible technical problems.

Practical method:

Copy the following prompt to Claude:

Please conduct a causal chain analysis on the "Smart Park Visitor Management System" and break down all possible technical problems from different dimensions (time, space, system, user experience, etc.).
Please expand each question two levels deep to form a question tree structure.
The output format is as follows:
Core Question 1
1.1 Sub-problem 1
   1.1.1 More detailed questions
1.2 Sub-problem 2
   1.2.1 Further subdivision of the problem

Core Question 2
...

This will allow Claude to generate a comprehensive list of questions for you.

In one of my recent smart campus projects, Claude helped me identify more than 20 issues from the dimension of "visitor experience", including "long visitor waiting time" and "cumbersome identity authentication", which is more than three times the number I would have thought about on my own.

More importantly, Claude will also dig out some issues that we tend to overlook, such as "visitor management during non-working hours" and "rapid evacuation of visitors in emergency situations", which are potential patent innovations.

Step 2: AI-assisted innovation solution generation

With a list of problems in hand, the next step is to generate innovative solutions for each problem.

This is where Claude can really shine.

Practical method:

For each question on the checklist, you can use a prompt like the following:

Generate 10 different innovative solutions to the technical problem of "long visitor waiting time in the smart campus visitor management system".
Require:
-  Each solution must have a clear technical implementation path
-Try  to provide solutions from different technical fields
-  Consider the novelty and feasibility of the solution
-Each  solution includes core technical points, implementation methods and expected results

Make sure your proposal is concise and easy to understand.

In my practice, for the problem of "long waiting time for visitors", Claude not only proposed the conventional "reservation system optimization" solution, but also innovatively proposed "visitor flow control system based on behavior prediction" and "AR navigation and virtual queuing system" and other innovative solutions.

What’s even more amazing is that Claude can also “couple” different solutions to create a 1+1>2 effect.

Just a reminder like this:

Please technically couple the two solutions of "reservation system optimization" and "visitor flow control based on behavior prediction" to form a new solution that combines the advantages of both.
Please describe in detail the coupled technical architecture, including system components, data flow paths, and newly added functional points.
Make sure the description is clear and easy to understand.

This approach allows me to produce dozens of high-quality innovative solutions in a day, far exceeding traditional efficiency.

Step 3: Patent layout planning

Scattered patent applications are unlikely to provide effective protection; a systematic patent layout is the right way to go.

Claude can help us develop a structured patent deployment strategy.

Practical method:

Use the following prompt words:

Please help me design a patent layout strategy for a smart campus visitor management system.
The specific requirements are as follows:
1.  Decompose based on product structure, covering core modules, system architecture and key functions.
2.  Provide patent protection around product selling points (such as convenience, safety, and intelligence).
3.  Consider defensive layout to avoid possible patent attacks from competitors.
4.  Design a patent layout matrix with the horizontal axis representing the technology module and the vertical axis representing the protection strategy.
5.  Finally, recommend 1-2 patent directions with the greatest application value for each layout point.

Claude will generate a detailed layout plan for you.

In my smart park project, it helped me design a complete matrix, which includes the patent layout of five major modules: hardware equipment layer, network communication layer, data processing layer, application service layer and user interface layer. Each module is further divided into multiple patent points.

This structured layout makes our patent protection more systematic and avoids scattered applications like "sprinkle pepper".

Step 4: Writing the Patent Briefing

This is where Claude excels.

Just provide a brief description of the technical solution (50-100 words) and it will generate a complete patent briefing (1000-2000 words).

Practical method:

Use the following prompt template:

Please write a patent briefing document with the theme of "Smart Park Visitor Behavior Prediction System Based on Deep Learning".
Please describe it in detail according to the following structure:
1.  Title of invention:
   -Please  give the name of the invention.
2.  Technical background:
   -Describe  the background of the unpredictable peak visitor season in the park, which results in unreasonable allocation of reception resources and long waiting time for visitors.
3.  Disadvantages of existing technology:
   -Describe  the current technical deficiencies and shortcomings in visitor traffic forecasting.
4.  Technical solution:
   -  Describe the solution in detail, including how to combine historical visitor data, park activity information and deep learning algorithms to build a visitor flow prediction model, predict peak periods in advance, and dynamically adjust the technical architecture of reception resources.
5.  Technical effects:
   -Describe  the technical effects of the system, including improving reception efficiency, reducing visitor waiting time, etc.
6.  Specific embodiments:
   -  Provide at least two specific embodiments, including necessary parameters and implementation details. 

Use simple, direct language to ensure your content is clear and understandable.

Claude will generate a well-structured and detailed patent briefing.

From my experience, the briefing documents it generates are not only well-organized, but can also automatically supplement the technical background, shortcomings of existing technologies, enrich implementation plans, and even add some technical effects that we did not expect.

Step 5: Patent risk avoidance

The last step is to avoid patent risks and avoid stepping on the patent minefields of competitors.

This step requires a combination of patent search and AI analysis.

Practical method:

First, conduct a preliminary patent search (using specialized patent databases such as Baiteng, SoopPAT, Google Patent, etc.), and then provide the key patents to Claude:

I need to design my innovative solution to avoid patent risks.
The key claims of the competitor’s patent are as follows:
"A method for managing visitors in a smart park, comprising: performing visitor identity authentication through face recognition technology; storing the verification result in a database; and issuing an electronic pass based on the verification result."
My solution is: "Visitor Authentication System Based on Multimodal Biometrics".
Please help me:
1.  Disassemble the technical features of competitors’ patents.
2.  Analyze the possible infringement risks in my solution.
3.  Provide 5 possible design solutions to avoid the problem.
4.  Conduct infringement risk assessment for each circumvention solution.
Use simple, direct language and make sure your prompts are clear and detailed.

In one of my projects, Claude helped me identify a key risk point:

Claude proposed several workarounds, including "using iris instead of facial recognition" and "temporarily storing the recognition results on the user side instead of in the database". These suggestions helped us cleverly avoid patent risks.

Advanced Application: Response to Review Comments

In addition to the five steps mentioned above, Claude can also help deal with patent examination opinions.

When you receive an office action from the patent office, you can ask Claude to help you analyze and prepare a response:

Please help me analyze the following patent examination opinions and prepare a response:
[Paste the original text of the review opinion]
Please organize your response as follows:
1.  Analyze the main issues raised by the examiner.
2.  Provide rebuttal to the question of “lack of novelty”.
3.  Provide rebuttal to the question of “lack of creativity”.
4.  Design possible claim amendments while maintaining an appropriate scope of protection.

Actual effects and precautions

Through this method, I shortened the time for patent mining and briefing document writing from an average of 2 weeks to about 3 days, while significantly improving the patent quality and approval rate.

However, there are a few things to note when using AI to assist in patent applications:

1. 1.  AI-generated content needs to be reviewed by technical personnel, especially the implementation details
2. 2.  The quality of the input information provided to AI determines the quality of its output. Try to provide detailed background
3. 3.  AI cannot completely replace human innovation for the new discovery of scientific principles.
4. 4.  Patent briefings in different fields are different, and AI prompt words need to be adjusted

Conclusion: AI empowers the future

Patent applications have always been a major challenge for technicians, but with AI assistants like Claude 3.7 Sonnet, we can finally say goodbye to the arduous work of patent writing and devote more energy to real technological innovation.

From problem mining to solution generation, from patent layout to briefing document writing, and then to risk avoidance, AI can participate in the entire process of patent application, greatly improving efficiency while ensuring quality.

The essence of technological innovation is solving problems, not filling out forms or writing documents.

With AI assistants, we can focus more on truly innovative thinking and leave the document work to AI.

Claude is the most capable assistant I have ever met on the road of patent application.

Are you also having a headache about patent application? You might as well try this method, I believe it will bring you a new experience.