Why drafting discipline, alignment, and scrutiny-readiness define “born strong” patents

By Ian Schick, PhD, Esq

As AI reshapes how patent applications are drafted, the question facing patent practitioners is no longer whether a draft can be produced, but whether it is built to endure. When drafting becomes easier, professional judgment, alignment, and durability matter more—not less. This article examines what patent quality means after AI, and why “born strong” begins with the decisions made at the draft.

By Ian Schick, PhD, Esq

A shift in patent drafting economics is changing what matters in filing strategy: when AI makes high-quality drafts cheap, the real differentiator becomes assurance—engineering disclosures to survive prosecution scrutiny, diligence, and adversarial pressure. That pushes portfolios toward a provisionals-first pipeline that captures inventions closer to the rate of disclosure, provided those provisionals are fully enabled and claim-forward. The downstream challenge becomes governance—deciding what to convert, consolidate, split, or abandon—because prosecution is the long-tail cost driver. A key tactic is provisional netting: consolidating related provisionals into one lead utility case to preserve priority while focusing near-term prosecution spend and keeping optionality for later claim expansion.

By Ian Schick, PhD, Esq

The USPTO’s updated AI-inventorship guidance reaffirms that only humans can conceive an invention—and therefore only humans can be inventors—while highlighting a growing risk in AI-assisted drafting: some tools may introduce technical material that the inventor never actually conceived. When AI adds new embodiments, features, or problem–solution pairings beyond the inventor’s disclosure, the application can end up containing subject matter with no proper human inventor, making it unclaimable and potentially complicating inventorship and priority. The safest drafting practices keep all descriptive content grounded in the inventor’s documented conception—treating AI as a tool to articulate, elaborate, and organize that disclosure rather than expand it—and require practitioners to verify that every meaningful element in the claims and specification can be traced back to a human mind.

This article compares seven leading AI patent drafting platforms used by patent attorneys and agents, grouping them into three buckets: agentic AI, copilots, and toolkits. It explains how each product fits into real-world drafting and prosecution workflows, highlighting strengths like analytics, proofreading, and Word-native assistants. Against that landscape, the article shows why an agentic, end-to-end system offers a fundamentally different level of leverage—moving matters from disclosure to filing-ready drafts while preserving professional quality and control. The conclusion is clear: copilots and toolkits are useful, but Paximal is positioned to be the drafting engine at the center of a modern patent practice.