Goldman Sachs’ Claude Pivot, Debenhams AI Checkout, & AIG Agent Scaling

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AI HUSTLE | February 19, 2026

Welcome to AI Hustle, the newsletter that demystifies AI and turns complex tech into your next business advantage. This week, we're tackling a universal pain point: turning scattered post-meeting thoughts into polished, client-ready documents. We'll break down a simple workflow that saves hours and closes deals faster. Then, we’ll look at how giants like Goldman Sachs, AIG, and Debenhams are using AI agents not just for flashy demos, but to fundamentally rewire their core operations for massive efficiency gains. Let's get to it.

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The Hustle: The AI Project Ghostwriter

The Goal: Turn a messy, 5-minute voice memo into a structured Project Brief or Statement of Work, complete with a drafted follow-up email.

The Tools:

* A voice memo app (e.g., Apple's Voice Memos, Google Recorder)

* Cloud storage (Google Drive, Dropbox)

* Zapier (Automation glue)

* Otter.ai (Transcription)

* An AI Model (e.g., Claude 3, GPT-4)

Step 1: Capture the Brain-Dump (The Input)

Right after a client call or meeting, while the details are fresh, open your phone's voice memo app. Record a 3-5 minute "brain-dump." Don't worry about structure. Just talk through the client's problem, what they need, the proposed solution, key deliverables you discussed, potential timeline, and any other relevant details. When you're done, save this audio file to a dedicated folder in your cloud storage (e.g., a Google Drive folder named "New Project Memos").

Step 2: Trigger the Automation (The Trigger)

This is where the magic starts. Set up a "Zap" in Zapier. The trigger is: "New File in Google Drive Folder." Point it to the "New Project Memos" folder you created in Step 1. This means every time you drop a new audio file in there, the entire workflow kicks off automatically.

Step 3: Transcribe and Structure (The AI/Logic)

The Zap continues with a series of actions. First, send the audio file from Google Drive to Otter.ai to be transcribed into raw text. Next, take that raw text and send it to your AI model (like Claude 3) with a detailed prompt.

Your prompt is the secret sauce. Instruct the AI to act as a senior project manager and format the messy transcript into a professional Statement of Work using a specific template. For example:

"From the following transcript, create a formal Statement of Work. Structure it with these sections: 1. Project Overview, 2. Scope of Work, 3. Key Deliverables, 4. Proposed Timeline, 5. Next Steps. Extract all relevant details from the text and populate these sections. If information is missing, use placeholders like '[Client to provide specific date]'. The tone should be professional and confident."

Step 4: Draft the Follow-Up (The Output)

The final action in your Zap is to take the structured document created by the AI and use it to draft an email. Add another AI step with a prompt like this:

"Using the Statement of Work below, write a friendly and professional follow-up email to the client. Attach the SOW. The email should briefly recap our great conversation, state that the attached document outlines our proposed plan, and suggest a brief call to review it together. Create a draft in my Gmail account."

The Zap will place a perfectly drafted email, with the new document attached, directly into your Gmail drafts folder. All you have to do is review, edit, and hit send.

Why This Hustle Works:

* Eliminates Blank-Page Syndrome: It converts your raw thoughts directly into a structured first draft, saving you 1-2 hours of painful, from-scratch writing for every new project.

* Closes Deals Faster: It removes the "follow-up friction" that kills momentum. Sending a professional SOW within hours of a meeting shows you're organized, efficient, and ready to get started, increasing your win rate.

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🚀 The AI Pulse: 3 Signals to Watch This Week

Goldman Sachs Moves AI from the Lab to the Back Office

Goldman Sachs is deploying Anthropic's Claude AI for complex operational work like trade accounting and client onboarding. Instead of just using AI for coding assistance, they're targeting the messy, document-heavy "edge cases" where traditional rules-based software fails. AI is used to apply contextual reasoning to tasks like verifying identities with slightly mismatched documents—augmenting human teams rather than replacing them. The goal is to increase processing capacity and resolve exceptions faster without hiring more staff.

The Hustle Take: The biggest opportunity for most businesses isn't a futuristic AI replacement. It's using AI to handle the 10% of work that causes 90% of your operational headaches. Look at your own workflows. Where do things require manual review due to minor discrepancies or unique situations? That's your starting point. Use AI to pre-process these exceptions so your team can focus on making the final judgment call, not the tedious comparison work.

Debenhams Tests 'Agentic Commerce' Inside PayPal

UK retailer Debenhams is piloting a new way to shop where customers never have to leave the PayPal app. An AI agent lets users describe what they're looking for in natural language ("I need a blue dress for a summer wedding under £100"). The agent asks clarifying questions and then facilitates the entire checkout process—payment and shipping—within the chat window. This "agentic commerce" model aims to slash mobile cart abandonment by removing friction.

The Hustle Take: This is a masterclass in meeting customers where they are. Instead of fighting to pull traffic to your own website or app, embed your sales process inside the platforms your customers already use and trust. For e-commerce, this could be payment apps. For B2B services, it might be a Slack or Teams integration. The strategy is to compress the sales funnel by putting your products and checkout right in the path of high-intent users.

AIG's 'Orchestration Layer' is Supercharging its AI Agents

Insurance giant AIG is reporting massive efficiency gains from AI in its core underwriting and claims processes, far exceeding initial projections. Their secret is an "orchestration layer"—a system that coordinates multiple specialized AI agents to work together on a single workflow. These agents act as "companions" to human teams, extracting data, summarizing information, and analyzing risk in a fraction of the time. This system allowed them to integrate the entire portfolio of another company by building a unified data "ontology" and having AI agents prioritize the most valuable accounts.

The Hustle Take: The next level of AI in business isn't about using one monolithic tool; it's about building a team of specialized AI agents. Think of it like a human team: one agent is great at extracting data from PDFs, another excels at summarizing it, and a third is skilled at drafting reports. The "orchestration layer" is the project manager that assigns tasks and ensures the workflow runs smoothly. Start thinking about your complex processes not as single tasks to automate, but as a series of sub-tasks that a team of AI agents could tackle together.

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