HumanLayer

Loop Engineering from First Principles — Kyle Mistele, HumanLayer

Jul 25, 2026 · 17:57

Kyle Mistele argues that the fix for AI-generated 40,000-line pull requests is not a better prompt but a better loop, borrowing from control theory: a sensor measures the gap between current and desired codebase state, a controller picks the smallest incremental change, and an actuator agent applies it using hand-written golden patterns. Mistele illustrates with HumanLayer's own loop that migrates their RPC API to Effect one procedure at a time, using AST grep as a deterministic sensor, a controller that selects the smallest unmigrated procedure, and an actuator agent gated by deterministic CI running a single iteration per day. The loop tracks its own PRs in version control, refuses to stack a new change while an earlier one is still open, and includes a feedback file and comment trigger for humans to re-steer it. Mistele concludes that this design makes the code incrementally better, readable, and verifiable, solving the problem of unreadable mass-generated code.

Harness Engineering is not Enough: Why Software Factories Fail — Dex Horthy, HumanLayer

Jul 23, 2026 · 19:18

Dex Horthy argues that the failure of lights-off software factories, including his own July 2025 experiment, is not a skill issue but a model training problem: coding models are reinforced only on passing tests, not on maintaining codebase quality, leading to slop code and outages. He explains that Claude Code succeeded where earlier CLI agents did not because it was the first model trained against the harness it ships in, optimizing for tool calls in an agentic loop. However, maintainability cannot be verified by current benchmarks like SWE-bench, which use binary test-pass rewards and ignore architectural degradation that only appears months later. Horthy advocates turning the lights back on—keeping human code review—but moving faster by investing upfront in product review, system architecture, program design (types and call graphs), and vertical slices. He claims thirty minutes of alignment saves hours of review, turning PR review from slop into a joy, and that this approach lets engineers still ship fast while owning code quality.

Full Walkthrough: Workflow for AI Coding — Matt Pocock

Apr 24, 2026 · 1:36:30

Matt Pocock presents a hands-on workshop on building a full AI-assisted coding workflow, arguing that software engineering fundamentals—not hype—make agents effective. He introduces the 'smart zone' and 'dumb zone' of LLMs (performance drops after ~100k tokens) and the 'Memento problem' (agents forget between sessions). His process starts with a 'Grill Me' skill that relentlessly questions the user until shared understanding is reached, then produces a PRD without reading it, slices work into vertical 'tracer bullet' issues, and runs agents AFK using TDD. He advocates designing codebases with deep, testable modules and shows Sandcastle, a TypeScript library for parallel agent execution with separate implementer (Sonnet) and reviewer (Opus). The workshop transforms ambiguous briefs into shippable features while keeping humans in the loop for QA and taste.

12-Factor Agents: Patterns of reliable LLM applications — Dex Horthy, HumanLayer

Jul 3, 2025 · 17:06

Dex Horthy, founder of HumanLayer, presents the 12-Factor Agents framework for building reliable LLM-powered applications, arguing that production-grade agents are primarily deterministic software with targeted LLM steps rather than fully autonomous loops. He distills patterns: own prompts and context windows, treat tools as JSON and code, use small focused agents with three to ten steps, contact humans via tool calls. Horthy emphasizes context engineering—LLMs are pure functions—and shows how to compact errors, unify state, and add pause/resume via APIs. He shares a DevOps agent that became a bash script, and advocates for outer-loop agents. The framework, which gained 4,000 GitHub stars in two months, treats agents as stateless reducers that meet users on any channel, with engineers controlling the inner loop of token and control flow.