My company is SoftPerson, which specializes in “semantic computing” in everyday general-purpose applications. The past decade or so was one of a lot of reading, research and experimentation with entirely new technologies and user experiences, but no product. I can’t really continue for more than another year without revenues, so I came up with some remedies.

These are my plans for the current year.

• Releasing a NConvert semantic code conversion tool early this year
• Kickstarter for NStatic, a static analysis tool, next month
  (In a future year, I would do the same for my natural language wordprocessor product).

In both cases, I would start out with a light version of the application, lacking much of the AI, to minimize risk and time to market. Then, I would follow up with the killer functionality. Consumers who buy the light version may receive the AI-enhanced version when it finally releases.

There are a variety of reasons that I was not able to release NStatic earlier, many of the reasons have little to do with the AI.

1. My code generation was originally in Perl, which is difficult to refactor, and is now written completely in C#.
2. I relied on and let down by third-party components for some core functionality such as parsing C# in attempt to focus on my core value proposition. My codebase will be based on Roslyn.
3. Working with source code is time-consuming. NStatic will initially work with the IL from compiled assemblies and use the symbols information from PDB files.
4. The mathematics is intense. Some of the issues that I have to deal with is ensuring non-termination.

I have been contacted by recruiters from two different major tech companies, so I may go back to work in the industry if I can leverage the ideas and techniques that I developed. The pros of working in the industry is that I can share ideas with top researchers and my discoveries will be widely disseminated.

I may turn some of my experiences and notes into book form. The books may be self-published using the Gumroad service.

• General-purpose Layout Engine
• Building a Word-Processor or Any Other Document-Based Editing
• Structured Editing
• Semantic Computing
• Real Natural Language Processing (Focus on Parsing and Semantics)
• Symbolic Reasoning Engine
• High-Performance Immutable Data Structures
• Practical Guide to Building a Software Startup
• The Design and Architecture of Various Open Source Projects
• Roslyn
• F#
• Python Math Libraries (Sympy, Numpy, SciPy and others)
• .NET Core
• Jetbrains IntelliJ IDEA & Nitra

Some of the code that I will write will be open-sourced.