The Dark Arts of Skill Engineering — Paul Bakaus, Renaissance Geek
This talk introduces nine techniques for 'skill engineering' that go beyond traditional prompt engineering. These include: 1. Using two blind sub-agents (e.g., design director and linter) for synthesis and self-correction. 2. Forcing divergence by naming preferred options and then discarding them to avoid safe predictions. 3. Routing skills like a mixture of experts. 4. Giving skills memory. 5. Using scripts that emit instructions on stdout for more reliable execution. 6. Implementing hooks that block writes rather than just complaining afterward. 7. Live wiring browser interactions. 8. The 'it worked on my machine' problem, addressed by designing for the weakest model. 9. Recognizing that every model is overfitted differently and designing for the weakest model. The overarching theme is that if a gate can be skipped, it will be, emphasizing the need for robust harness engineering.
More from the Agent Memory and Harness Engineering trail
- From Context to Memory: Your Agents Need a Real Memory Layer — Anders Swanson, Oracle
- Designing CLIs for Agents, Not Humans — Pedro Lopez, Airbyte
- Building on the Codex Harness — Dominik Kundel, OpenAI
- Stop Prompting — Greg Pstrucha, Sentry
- Brains vs Hands: How to Run AI Agents Safely in Production — Viren Baraiya