Opportunity Backlog

Last updated: 2026-07-28
Trigger: Update to Vibe code like a PRO — linking to real-world Devin booking system case study

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How to Read This

Each opportunity includes: impact (1–10), effort (1–10, higher = more effort), confidence (%), and reasoning.
Ranked by impact/effort ratio. Prefer opportunities that compound across multiple content pieces or products.

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Current Rank

1. ⏫ The Background Agent Pattern: A Definitive Guide

Impact: 9 | Effort: 5 | Confidence: 90%

Why this matters: The cluster is now complete: vision (Vibe code like a PRO), tooling pattern (How to Background Agents), real-world validation (Devin booking system), trust framework (Graduated Trust), and visualization (State machines for agent workflows). A single pillar piece synthesizing all five angles would establish category ownership. Compounds with every other opportunity.

Concrete next action: Outline a long-form essay or short book that walks from (a) the vision → (b) practical how-to → (c) real case study → (d) formal modeling → (e) trust/gov framework.

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2. ⏫ Linear Task Expander CLI (Product Backlog Opp 12)

Impact: 8 | Effort: 3 | Confidence: 85%

Why this matters: The 4-step pipeline (fetch→expand→spawn→PR) described in Vibe code like a PRO is now validated by the Devin case study as a real-world workflow. A CLI tool that automates this pipeline — taking a Linear ticket, expanding it, spawning a background agent, and opening a PR — is the productization of what was a manual process in the case study.

Concrete next action: Ship an MVP CLI that wraps the Linear API + a background agent launcher. Document as open-source.

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3. Async Engineering: The Senior Engineer's Workflow

Impact: 8 | Effort: 4 | Confidence: 80%

Why this matters: The Sunday planning system (How I organize my week) + background agents + Devin async partnership form a repeatable framework. Senior engineers are the audience — they have the autonomy to adopt async agent workflows. This is a personal-brand-defining piece.

Concrete next action: Extract the common pattern from all three pieces, write a cohesive guide.

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4. Graduated Trust: From Essay to Prototype

Impact: 7 | Effort: 6 | Confidence: 70%

Why this matters: The Devin case study demonstrates the core problem: AI agents producing production code that needs human verification. A working prototype (even a demo) of the graduated trust web-of-trust system would move this from theoretical proposal to tangible asset. Risk: Requires protocol design work.

Concrete next action: Design a minimal trust attestation schema; prototype with HM capabilities.

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5. State Machines for Agent Workflows: Pattern Library

Impact: 6 | Effort: 4 | Confidence: 75%

Why this matters: The state machines piece (State machines to visualize agents) offers a formal way to model agent behavior. A reusable pattern library with XState or similar would be a developer tool asset. Good for community-building.

Concrete next action: Extract diagrams/examples from the essay into a runnable code repo.

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Recently Closed / Deprioritized

(None yet — first analysis)

Notes

This backlog was seeded on 2026-07-28 following the update to Vibe code like a PRO.

All five opportunities are interlinked; investing in #1 compounds across all others.

The Devin booking system case study is the key validation event that raised confidence across the entire cluster.