An AI coding assistant for the parts that aren't typing
A chat-based AI coding assistant is strongest on comprehension tasks: explaining unfamiliar code, interpreting stack traces, proposing test cases and reviewing a diff. Inline autocomplete in your editor covers the typing; a chat thread covers the reasoning.
Editor autocomplete and a chat assistant solve different problems. Autocomplete finishes the line you were already writing. A thread helps when you don't yet know what to write.
ChatOTL is the second kind, with file attachments so the model sees the real code rather than your paraphrase of it.
Where it earns its place
- Reading an unfamiliar module and getting a map of what calls what.
- Turning a stack trace into a shortlist of plausible causes.
- Drafting test cases, including the edge cases you'd forget.
- Reviewing a diff for missed error handling and unclear naming.
- Translating a snippet between languages or frameworks as a starting point.
Attach the code, don't describe it
Source files — JS, TS, Python, Go, Rust, Java, SQL, shell and more — are extracted into the prompt, up to five files per message. Answers get sharply better when the model reads the actual types and imports.
Branch to compare approaches
Ask for one implementation, then branch the reply and ask for a different trade-off. You end up with two threads you can read side by side instead of one conversation that argued with itself.
Hard limits
- It cannot run your code, so nothing it suggests is tested until you test it.
- It doesn't know your private dependencies unless you attach them.
- Library APIs drift; verify anything version-sensitive against the docs.
Example prompts
- "Here are three files. Why does the second request see stale state?"
- "Write table-driven tests for this function, including the empty-input case."
- "Review this diff like a reviewer who cares about error handling."
Frequently asked questions
Does it replace an IDE assistant?
No — they complement each other. Keep autocomplete in the editor and use a thread for debugging, design and review.
Can I paste proprietary code?
Threads are scoped to your account. Whether you may send it to a hosted provider is a policy question; self-hosting an OpenAI-compatible endpoint keeps it internal.
Which languages does it handle?
Any language the underlying model knows. File extraction covers common source formats including TypeScript, Python, Go, Rust, Java, C-family, PHP, Ruby, Swift, SQL and shell.
Can my editor talk to ChatOTL directly?
Yes — connect Cursor or Claude over MCP and they can read, search and create your ChatOTL threads after OAuth consent.
Debug something real
Attach the files and the trace, and start from the actual code.
Open ChatOTL