Howardism · Vol. 03Plate II · No. 02
Derived, tagged.
Notes8TagDerivedOldest28 May 2026Newest28 May 2026
Every article tagged derived, newest first.
| 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 | |
| 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 | |
| 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 | |
| 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 |