Uploaded November 2025 | Updated September 2026, 12 hours ago

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HumanLayer founder Dexter Horthy shares tools and practices for making coding agents effective on hard problems. He outlines a research‑plan‑implement workflow, why senior engineers must set AI coding standards, and how code review should emphasize mental alignment. Dexter also discusses Claude Skills and the AI Tinkerers community.

CHAPTERS:
0:03 - Intro: HumanLayer and coding agents for hard problems
0:18 - Tools: OSS prompts and an IDE for many agent sessions
0:29 - Parallel coding agents; research‑plan‑implement
0:43 - Beyond small tasks: toward 99% AI‑assisted code
1:34 - Adoption rift: senior skeptics vs junior acceleration
2:41 - Need top‑down standards to avoid “slop”
3:04 - Standard setting in the AI era
3:49 - Code review hierarchy; style is least important
4:25 - Code review for mental alignment, not box‑checking
5:34 - Real example: huge Golang PRs require plans
6:18 - Research phase: objective codebase understanding
6:41 - Implementation plan: steps, tests, phasing
6:59 - Check deviations and tests
7:22 - The human layer: natural‑language docs and strategy
8:10 - Why big companies may adopt AI coding faster
8:31 - Expert knowledge of models and instructions
8:43 - Proliferate best practices via prompts/workflows
9:15 - Claude Skills vs slash commands/subagents
10:05 - Skills flexibility; avoid context forking
11:31 - AI Tinkerers: builders learning from builders
12:14 - Join: ai tinkerers.org (SF chapter and events)