Engineering Manager / Technical Lead
A topic hub collecting every article tagged Loop Engineering. Use it to explore related posts and follow this theme across the site.
20 articles
Modern production apps require many layers to maintain. A prompt-first repository adds instructions, skills, MCP, and bounded loops so agents can move faster without bypassing reliability controls.
A source-checked guide to Pi — the minimal terminal coding harness behind OpenClaw — with comparisons to Claude Code, Cursor, Codex, and OpenCode, plus handoff workflows and when the minimal approach wins.
A practical guide for engineers and PMs on when to build general-purpose horizontal agents, when to invest in domain-specific vertical agents, and how loop engineering differs for each—including hybrid architectures that route across both.
A practical playbook for engineers and PMs facing messy problems with many possible answers, hidden risks, and no obvious best path.
A practical guide for students, junior developers, self-taught builders, and PMs who want to use AI as a coach, quiz partner, and debugging buddy without outsourcing the struggle that makes learning stick.
A practical guide for engineers on when nit comments help, when they become review noise, and how many are enough before a team should automate, approve, or move the discussion out of the PR.
A practical research-backed guide to building a senior-engineer agent that plans work, writes structured subagent prompts, orchestrates execution, and opens pull requests, plus an honest map of the gaps, assumptions, and confidence needed for trustworthy auto-PRs.
AI can generate most of the code. It still cannot decide what to build, sense when 'correct-looking' output is quietly wrong, or own the consequences. A field guide to the tasks that stay human — for engineers and PMs.
A practical guide for engineers and PMs who want AI coding agents to move fast without breaking architecture decisions, module boundaries, ownership, and long-term system quality.
A practical guide for engineers and PMs who want to improve daily AI-agent work by auditing instructions, skills, subagents, tools, and review habits.
A source-audited guide to modern autonomous workflows: when to use n8n, CrewAI, Cloudflare Agents, LangGraph, or Agno, where teams stumble, and why this is practical now.
A practical guide for engineers and PMs on what belongs in the main AI coding conversation, what can be delegated to subagents, and what the real tradeoffs look like in Cursor and Claude Code.
A practical research guide for using Gherkin, BDD, Spec-Driven Development, and eval-driven workflows to make AI-assisted delivery clearer, safer, and easier to review.
The grill-me skill is a tiny prompt pattern with a big payoff: make the agent interview you before it builds. This guide explains how it works, how to create your own project skill, and how to fit it into a practical agentic development workflow.
A research-backed guide for engineers and PMs on what is now redundant with stronger coding agents, when a good prompt is sufficient, and when prompts need scaffolding, tools, evals, and workflow design.
A practical research audit for engineers and PMs: when agent skills improve coding agents, when default agents plus repo context are enough, and how to evaluate the tradeoff.
Self-modifying software is not science fiction. It sits on deep computability theory and shows up today in JIT compilers, livepatching, dynamic updates, malware, and AI-assisted code loops.
The current evidence does not support trusting model size alone for secure code generation. Secure agentic coding needs threat modeling, constrained tools, scanners, evals, and human approval gates.
There is no truly bulletproof system prompt. But there is a practical engineering standard for making prompts far more robust across Sonnet, Haiku, GPT, and reasoning-style models.
Most AI code review bots fail for a simple reason: they optimize for visible comments instead of reviewer trust. This guide pulls together current benchmarks, practitioner reports, product limitations, and design patterns for building a code review agent that is fast, quieter, less biased, and less hallucination-prone.
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