Research
Last verified: 2026-03-29
Deep Research reports from ChatGPT, Gemini, and Claude, stored for reference. These are AI-generated research reports, not published papers. Each subject has its own page with the prompt used and links to the individual provider reports.
Subjects
- Coding Agent Best Practices — Three reports on defining and structuring coding agents (model routing, subagents, orchestration, context engineering, state management). March 2026.
- Anthropic Guidance on Building Agents — Extracted findings from 7 Anthropic publications on agent design, context engineering, tool use, multi-agent systems, and autonomy. March 2026.
- AI Slop / Voice Prevention — Three reports on suppressing AI writing tells and matching a specific author voice (tell taxonomy, prompt strategies, reviewer prompts). March 2026.
- AI-Augmented PRDs and AI-Native SDLC — Three reports on PRD template structure, AI-augmented workflows, acceptance criteria, failure modes, and AI-native development lifecycles. March 2026.
- Design Docs for AI Coding Agents — Three reports on design doc templates, PRD-to-design handoff, trade-off documentation, implementation phasing, and structuring design docs as inputs to AI coding agents. March 2026.
- Autolearn v1: Autonomous PoC Learning System — Three reports on architecting an autonomous AI-native SDLC pipeline for continuous PoC learning on Kubernetes (structured planning, agent sandboxing, orchestration frameworks). March 2026.
- Claude Code Plugins — Three reports on which Claude Code plugins, skills, and marketplaces are worth installing (file-level audit, token cost, trust surface, stack fit, ecosystem gaps). April 2026.
- Agent-Native Design System — Single-provider (Claude) report on building a modern, agent-native design system for the blog as a predicate to a redesign: design tokens, Tailwind v4, Radix primitives, the shadcn/ui model, MCP glue, and a phased additive migration off MUI. Seed input for the PER-135 redesign. May 2026.
- ├── AI-Augmented PRDs and AI-Native SDLC
- │ ├── ChatGPT Deep Research: AI-Augmented PRDs and AI-Native SDLCs
- │ ├── Claude Deep Research: AI-Augmented PRDs and the AI-Native SDLC
- │ └── Gemini Deep Research: The Architecture of Intent — AI-Augmented Requirements and the AI-Native Lifecycle
- ├── AI Slop / Voice Prevention
- │ ├── ChatGPT Deep Research: Prompting Claude Opus 4.6 and Sonnet 4.6 for casual human prose
- │ ├── Claude Deep Research: A reviewer prompt to make AI writing sound like Kyle Pericak
- │ └── Gemini Deep Research: Linguistic Deconstruction and Strategic Prompt Engineering for Human-Centric Technical Prose in Claude 4.6 Systems
- ├── Anthropic Guidance on Building Agents
- ├── Autolearn v1: Autonomous PoC Learning System
- │ ├── ChatGPT Deep Research: Automating an AI-Native SDLC for Continuous PoC Learning in Kubernetes
- │ ├── Claude Deep Research: Automating an AI-Native SDLC Pipeline on Kubernetes
- │ └── Gemini Deep Research: Autonomous Infrastructure Engineering on Kubernetes
- ├── Claude Code Plugins
- │ ├── ChatGPT Deep Research: Claude Code plugins worth installing
- │ ├── Claude Deep Research: Five honest picks for a senior Claude Code stack
- │ └── Gemini Deep Research: Technical Audit and Strategic Curation of the Claude Code Plugin Ecosystem
- ├── Coding Agent Best Practices
- │ ├── ChatGPT Deep Research: Research-based best practices for defining and structuring coding agents with Claude Opus, Sonnet, and Haiku
- │ ├── Claude Deep Research: Definitive guide to Claude coding agent architecture
- │ └── Gemini Deep Research: Architectural Paradigms and Engineering Best Practices for Claude-Based Coding Agents
- ├── Design Docs Optimized for AI Coding Agents
- │ ├── ChatGPT Deep Research: Design Docs for AI Coding Agents
- │ ├── Claude Deep Research: Design Docs for AI Coding Agents
- │ └── Gemini Deep Research: Design Docs for AI Coding Agents
- └── A Modern, Agent-Native Design System for the Blog
- └── Claude Deep Research: A Modern, Agent-Native Design System for kyle.pericak.com