It’s a living research collection with 400+ commits covering practical experiments, usage patterns, step-by-step guides, model comparisons, AI coding tool evaluations (Cursor, Aider, Cline, Windsurf, etc.).
A large part of my work is *exploratory*: navigating large and messy information spaces, testing things hands-on, comparing different approaches, and identifying the small amount of signal that is actually useful.
My strongest skill is broad technical *investigation*. I can map an entire problem space rather than focus on a single tool, model, or hypothesis: find the relevant projects, papers, tools, workflows, discussions, benchmarks, and practical examples; test and compare what matters; and organize the results into a clear picture of the field.
The goal is not to arrive with a predetermined answer or recommend one particular tool. I can cover the *surrounding landscape* as thoroughly as possible and provide the evidence, comparisons, and structure. Your team can then decide which conclusions matter and what to do with them.
I can deliver the results as a structured PDF or HTML research artifact, or discuss the findings in a call. Depending on the project, I can also combine both formats: prepare a written report with the relevant evidence and comparisons, then walk your team through it and answer questions live.
I’m interested in projects where someone needs a broad, hands-on investigation of AI-assisted software development: understanding what exists, how different approaches compare, where they work, where they fail, and what is worth paying attention to.
I don’t know the conventional job title for this niche. If your team needs someone who can cover a large and changing technical field, turn scattered information into a structured overview, and give you a solid basis for making decisions, I’d be interested in talking.
It’s a living research collection with 400+ commits covering practical experiments, usage patterns, step-by-step guides, model comparisons, AI coding tool evaluations (Cursor, Aider, Cline, Windsurf, etc.).
A large part of my work is *exploratory*: navigating large and messy information spaces, testing things hands-on, comparing different approaches, and identifying the small amount of signal that is actually useful.
My strongest skill is broad technical *investigation*. I can map an entire problem space rather than focus on a single tool, model, or hypothesis: find the relevant projects, papers, tools, workflows, discussions, benchmarks, and practical examples; test and compare what matters; and organize the results into a clear picture of the field.
The goal is not to arrive with a predetermined answer or recommend one particular tool. I can cover the *surrounding landscape* as thoroughly as possible and provide the evidence, comparisons, and structure. Your team can then decide which conclusions matter and what to do with them.
I can deliver the results as a structured PDF or HTML research artifact, or discuss the findings in a call. Depending on the project, I can also combine both formats: prepare a written report with the relevant evidence and comparisons, then walk your team through it and answer questions live.
I’m interested in projects where someone needs a broad, hands-on investigation of AI-assisted software development: understanding what exists, how different approaches compare, where they work, where they fail, and what is worth paying attention to.
I don’t know the conventional job title for this niche. If your team needs someone who can cover a large and changing technical field, turn scattered information into a structured overview, and give you a solid basis for making decisions, I’d be interested in talking.
Who: Dan Voronov Location: Kyiv, Ukraine Remote: Yes Github: https://github.com/danvoronov Email: [email protected]