Howardism · Vol. 03Plate II · No. 02
Syntheses, in order.
Notes16DomainSynthesesOpen Qs0Newest28 May 2026Oldest10 Apr 2026
Cross-cutting essays that weave the domains together.
| Title | Summary | Date |
|---|---|---|
| Agent Control Plane Patterns: Tickets, Loops, Specs, and Memory Files | Layered agent control-plane synthesis: tickets as durable work graph, loops as execution primitive, specs/context files as policy, memory as bounded recall, app protocols as runtime boundary | |
| AI-Native Moats Under Frontier-Model Improvement | Frontier-model improvement stress-tests AI-native moats: product velocity and wedges must compound into behavioral data, domain artifacts, workflow embedding, counter-positioning, or external powers | |
| AI-Native Product Org Bottlenecks | AI-native product-org bottleneck is accountable taste at speed: dogfooding trains taste, evals encode it, and accountability owns the consequences as output volume rises | |
| How AI-Native Startups Avoid Speed Becoming Strategic Debt | AI-native startup speed becomes strategic debt unless bounded by validated problem, written scope, persistent architecture, accountable orchestration, and founder-owned customer signal | |
| Opinions on Using AI Tools & the Future of the Software Engineering Role | Debate map of four stances on using AI tools (bullish-insider / pragmatist-practitioner / skeptic-governance / architecture-thesis) + synthesis on the future SWE role: coding→deciding/verifying, role convergence, what stays human, which moats survive, honest caveats | |
| Where Does Agent Harness Work Remain Durable as Models Improve? | Durable harness work lives at external-reality boundaries: repo-local source of truth, mechanical verification, context budgeting, isolation, tool contracts, and human decision surfaces; capability scaffolding shrinks | |
| The Future of Agent Interfaces | Interface future is layered: native interaction models for human collaboration, MCP/APIs for structured action, app protocols for agent runtimes, computer use for legacy GUI fallback | |
| Does the Human-Facing Harness (HTML Artifacts) Hit Its Own Bloat Ceiling? | Yes — HTML raises and reshapes the human-attention ceiling but can't remove it; bloat relocates from document-length to artifact-sprawl/rubber-stamping; the ceiling gets *more* binding as models improve (inverse of the shrinking model-facing harness) | |
| Human-in-the-Loop Boundaries | Humans belong at allocation, understanding, design-concept, risk, and accountability boundaries; they slow the system down as manual executors, universal reviewers, or ceremonial approvers | |
| Learning to Co-Work with AI: A Software Engineer's Field Guide | Field guide for software engineers in the AI era: 6 skill clusters (taste, harness, alignment-first planning, agent-friendly architecture, verification, strategic positioning), daily practices, anti-patterns, 90-day plan | |
| Orchestration vs Employee Framing: Reconciling the Founder's Playbook with HBR's Accountability Evidence | Reconciles the Founder's Playbook orchestration framings with HBR Kropp et al.'s accountability evidence; "orchestration as workflow design" survives the critique; "orchestration as mental model of agents-as-coworkers" does not; operational checklist for the disciplined founder | |
| When Does Verification Quality Determine Whether AI Automation Works? | Verification-quality ladder from Lean/formal proof search through software CI and vulnerability reproduction; autonomy should rise only to the level the verifier can support | |
| Agent Context Files | that touch this pattern. Thrice-deferred in the log (2026-04-28, 2026-05-06, 2026-05-21). --> | |
| Opus 4.6 → 4.7 Changes and Multi-Agent Coding Considerations | 4.6→4.7 delta table + six hazards for multi-agent coding teams: role-based model selection, prompt re-tuning, harness invariants, per-agent context budget, unattended-fan-out safety, independent reviewer | |
| When to Use Claude Opus 4.6 for Work | Decision rules for Opus 4.6 deployment: solver-not-planner, elaboration-load-bearing tasks, brevity constraints, Pareto frontier check | |
| What Are AI Tools? | Overview of AI tools landscape and categories |