Tyler Collins

Research computing consultant, Canada

I help researchers turn computational problems into reliable software and workflows: HPC systems, Python tooling, EEG/MEG pipelines, getting more out of the hardware you already have, and helping scientific teams use AI coding agents well.

Recent writing

All writing
  1. Workflow

    Think out loud with local Whisper

    Talking through a problem is a good way to organize your thoughts, and OpenWhispr with a local Whisper model lets you capture it for free on hardware you probably already have.

  2. AI agents

    Grants will need a line for tokens

    More research money is going to LLM tokens. I predict Canadian granting agencies will add a token allocation tied to sovereign, safe infrastructure.

  3. AI agents

    Send your agent a screenshot

    Agents only know the dashboards they were trained on. When menus keep moving or a UI looks wrong, a screenshot gives the agent what's actually on your screen.

  4. AI agents

    Get a second opinion from another model

    Models are tuned to write code differently. If you have the tokens, having one review another's work is basic hygiene, and personas take the idea further.

  5. Llm

    Clean-Room Rewrites for Researchers

    Tools like REA let a coding agent take closed software apart. Escaping research lock-in is one of the best uses for them, as long as you stay in your lane.