Travis Muhlestein PRO
TravisMuhlestein
AI & ML interests
Product & AI CTO at GoDaddy focused on AI infrastructure, orchestration, agent systems, observability, and enterprise-scale AI deployment
Recent Activity
repliedto salma-remyx's post about 9 hours ago
π Outrider β a GitHub Action that scouts arXiv for your repo
We built Outrider to close the gap between your code and the latest arXiv research. The best new methods for your repo may not be from the viral paper.
How it works β every week (or your configured cadence), Outrider:
1. Pulls candidate papers from a Remyx engine that ranks arXiv against your repo's commit history
2. Runs a Claude selection pass over the pool β picks the candidate most implementable against your specific codebase
3. Invokes Claude Code to draft the integration into an existing call site
4. Runs quality gates (path allowlist, integration validator, stub-density check, self-review)
5. Opens a draft PR β or an Issue when a PR would be premature
Two recent PRs:
- remyxai/FFMPerative β picked Aurora (2026 video-editing-agent paper), wired plan-validation into the existing execution path. 5 min, $1.45.
- remyxai/VQASynth β picked PGT (procedurally-generated grounding), wired the scorer into the existing BenchmarkRunner registry. 8 min, $2.64.
Free to install via GitHub Marketplace. You bring your own ANTHROPIC_API_KEY (~$2-3 per PR-track run).
Repo: https://github.com/remyxai/outrider
Longer write-up tomorrow on Substack β more detail on the spec-bundle format, the selection-pass design, and what we learned testing across dozens of repos. repliedto sergiopaniego's post about 9 hours ago
Harness, Scaffold, Context Engineering, Agent... do you actually know what they mean?
We wrote an AI agent glossary and tried to make sense of it all with simple definitions and real examples
β go read it β
https://huggingface.co/blog/agent-glossary