🚨 – What “Sherlocking” Means in the Gen‑AI Era
🧱 2. The seven venture‑grade moats
🔍 3. Diligence drill – five questions to kill thin moats
🚩 4. Red‑flag scorecard
🏁 5. Conclusion – Fund assets, not features
🚨 – What “Sherlocking” Means in the Gen‑AI Era
In 1998 Apple’s Sherlock search tool quietly absorbed a third‑party app named Watson. That one act coined the term Sherlocking: when a platform owner clones a popular add‑on and leaves the start‑up out in the cold.
OpenAI now does the same in software. A micro‑SaaS goes viral → the capability appears inside ChatGPT with zero‑friction UX and no extra cost. Its in‑chat Shopping Assistant arrived only weeks after product‑discovery plug‑ins hit the store.
For founders it can sink the company; for VCs it can wipe the return. Your equity only endures if something valuable still works the morning after the clone ships.
🚨 The Clone Is Coming
ChatGPT has Sherlocked fourteen standalone plug-ins this year. As soon as a point solution gains traction, OpenAI folds it straight into ChatGPT—no extra cost, zero friction.
Every one of these began life as a separate plug-in or micro-service—now folded straight into ChatGPT’s UX, at no extra cost or friction. Founders and VCs need to ask: if my entire feature set were built in-house at OpenAI, would users even notice?
In-chat Shopping Assistant (Instacart-style)
Web Browsing (“Browse with Bing” replacing WebPilot, etc.)
Advanced Data Analysis / Code Interpreter (formerly Python & Wolfram plug-ins)
DALL·E Image Generation (vs third-party image-gen add-ons)
Canva-style Graphics (template-based design in-chat)
Zapier-style Workflow Automation
PDF Reader & Summariser (AskYourPDF-style)
YouTube/Video Summariser
Memory & Personalisation (third-party “memory” plug-ins)
Travel Booking (Expedia/Kayak-style searching and reservation)
Restaurant Reservations (OpenTable-style)
Translation (DeepL-style high-quality language conversion)
Meeting Scheduling (Calendly-style)
Real-time News & Research (replacing niche news-feed plug-ins)