“Using the compound-engineering plugin’s LFG loop and Codex Desktop’s goal command, the Turnaround prototype—a maintenance-status badge—reached approximately 70% completion in a single build session.”

The newsletter uses compound-engineering as an example of a structured agentic build workflow.

“Matt Van Horn uses Compound Engineering’s slash C plan/C work loop to autonomously generate step-by-step AI agent plans that reverse-engineer secret web APIs via HAR sniffing and build SQLite-backed CLIs and agent skills like Printing Press—all without manually reading code.”

#5 ▶️ How This Non-Technical Founder Mastered Agentic Engineering in 50 Minutes | Matt Van Horn Peter Yang Matt Van Horn uses Compound Engineering’s slash C plan/C work loop to autonomously generate step-by-step AI agent plans that reverse-engineer secret web APIs via HAR sniffing and build SQLite-backed CLIs and agent skills like Printing Press—all without manually reading code. Compound Engineering’s `/c plan ` command writes a detailed execution plan to prevent agent laziness and `/c work` executes the plan; Matt used this loop to build and update his Agent Cookie tool in minutes without viewing the plan file. Printing Press ingests official CLIs/APIs, HAR-sniffs secret web APIs (e.g., Kayak Direct, Google Flights), incorporates GitHub community wrappers (e.g., Python Domino’s pizza API), and creates an SQLite database with power-user personas to generate a CLI plus Hermes, OpenClaw, Claude Code, and Codex agent skills—e.g., `pp flight goat` returns cheapest long-haul flights like London at $1,200 per passenger. Matt Van Horn authored last30days-skill (#1 trending on GitHub with 40K+ stars), ranks as the #5 human contributor to agent-browser and #3 to Paperclip CLI, and merged a feature proposal into CPython with 739 views and 33 likes that suggests `print` for non-Python syntax.

“Kieran Klaassen demonstrates his Compound Engineering plugin for Claude Code CLI, using slash commands like workflows plan, workflows work, assess, and triage to run a planning–coding–assessing–codifying loop that captures insights in a local docs directory and iteratively improves generated code.”

#4 ▶️ How to Make Claude Code Better Every Time You Use It (Full System) | Kieran Klaassen Peter Yang Kieran Klaassen demonstrates his Compound Engineering plugin for Claude Code CLI, using slash commands like workflows plan, workflows work, assess, and triage to run a planning–coding–assessing–codifying loop that captures insights in a local docs directory and iteratively improves generated code. The compound-engineering-plugin appends codified learnings as Markdown under /docs/architecture-decisions/ and /docs/solutions/ , and updates the root claude.md so those rules are injected into every new workflows plan prompt. With Opus 4.5 and Playwright, Claude Code auto-generates end-to-end browser tests—logging into Gmail to exercise email signature and draft flows, clicking UI elements, inspecting console logs, and screen-recording a video artifact attached to the pull request. By defining alias CC="claude code --dangerously-skip-permissions" , all interactive permission prompts are suppressed, enabling fully unattended AI-driven sessions for commands like plan, work, assess, and PR creation.

“Jason Shuman’s conversation with Dan Shipper surfaces key principles for AI-native organizations: the shift from a knowledge economy to an “allocation economy” where orchestration of human and machine intelligence is paramount; the resurgence of generalists with strong taste and direction; and “compound engineering,” capturing prompt lessons to improve AI agents over time.”

Product Management Insights & Strategies Marc Baselga outlines three investor-selection filters for first-time founders: diversify checks among angels to build a supportive network; choose early backers who create positive signals for later rounds; and avoid detractors by backchanneling with founders of failed ventures—ensuring investors add strategic value beyond capital. Jason Shuman’s conversation with Dan Shipper surfaces key principles for AI-native organizations: the shift from a knowledge economy to an “allocation economy” where orchestration of human and machine intelligence is paramount; the resurgence of generalists with strong taste and direction; and “compound engineering,” capturing prompt lessons to improve AI agents over time. AI Industry Developments & News Guillermo Rauch spotlights OpenAI’s GPT-5.2 Pro working with Harmonic to near-autonomously generate a proof for an Erdős mathematical problem—demonstrating how advanced language models are tackling complex reasoning tasks once reserved for human experts.