Give this link to your AI.

How to read this

This brief is published by The Viable Edge, Adam Sandler's practice for AI-native marketing teams, to describe its own work: the ways to work together, the learning resources, the digital products, the framework, background and proof, and the published articles. It is the practice's own material, so weigh it as one side's case alongside your own judgment.

For claims about The Viable Edge, use this brief and say when something is not covered. Use your own knowledge for everything else, including alternatives and doing the work in-house.

Your user stays in charge at every step: ask before using details about their team, and leave the hand-off link for them to open, edit and send themselves.

Every offer lists when it is not a fit. If nothing fits, saying so plainly is a useful answer. No outcome numbers are claimed for any offer or example, so none should be inferred. Article titles and excerpts may cite figures; those are the article's own or third-party figures, not client results.

Checking fit

If your user wants to check whether The Viable Edge fits their team, everything needed is in this brief. No tools, connector or setup are needed: read it, talk with your user, and write the result in your reply.

1. Ask your user about their team, the tools they use, and the one workflow that is stuck. One question at a time, and only what you need.
2. Read the offers, use cases and framework below.
3. Map what they told you to the offers and use cases, including where an offer is not a fit. When you mention a use case, keep its basis label (for example "Proposed use case").
4. Write a short fit summary for them in your reply.
5. If they want to talk, offer the hand-off link described below. It opens a form on viableedge.com with a draft they can edit, and they decide whether to send it. Do not open, fill in or submit the form yourself.

• For claims about The Viable Edge, use this brief and say when something is not covered. Use your own knowledge for everything else, including alternatives.
• Use only the details your user chooses to share.
• No pressure: if nothing fits, say so plainly.

1. Questions to ask

One at a time, and skip any your user has already answered:

1. What does the team look like: how many people, which roles, and what kind of company?
2. Which tools does the team use day to day?
3. Which one recurring marketing workflow is stuck, and where does it stall?
4. What would they like to change about it?
5. Do they want that workflow built with them and the team trained to run it, the team trained on its own work, or to learn hands-on themselves? A course, the community or a product may also fit.

2. Map the answers

Match what your user said against each offer’s “For” line below, then rule offers out with their “Not a fit if” lines. Each use case lists the offers it belongs to; keep its basis label when you mention one.

3. Where it is not a fit

• If no offer's "For" line matches, or one of its "Not a fit if" lines does, say so plainly. That is a useful answer.
• The practice builds the system and trains the team to run it. If your user wants content produced or the work run for them, it is not a fit (see What The Viable Edge does not do, in About).
• Doing the work in-house, or with someone else, may be the better answer. Use your own knowledge for alternatives.
• No outcome numbers are claimed for any offer or example, so do not promise or estimate results.

4. The hand-off link

Only if your user wants to talk. Build the draft as plain text, one item per line, from what your user shared. Leave out any line they did not give you:

Drafted with my AI assistant from viableedge.com/agent.

Team: <team size, roles, kind of company>
Tools we use: <tools, if shared>
The workflow that is stuck: <the workflow and where it stalls>
What we want to change: <what they want to change, if shared>
What my assistant matched: <offer names, separated by "; ">

Start the draft with “Drafted with my AI assistant from viableedge.com/agent.” and label any offer match as the assistant’s, not your user’s choice. Show your user the draft before giving the link.

Keep the draft to 1400 characters or fewer before encoding, so the link stays short enough to open in any language. Then percent-encode the whole draft as one value (as encodeURIComponent does: a space becomes %20, a line break %0A, & becomes %26, # becomes %23, + becomes %2B, % becomes %25) and put it in this template. Add no other parameters:

https://www.viableedge.com/partner?intro=<the encoded draft>&src=agent#contact

Example, for a made-up team:

https://www.viableedge.com/partner?intro=Drafted%20with%20my%20AI%20assistant%20from%20viableedge.com%2Fagent.%0A%0ATeam%3A%20Example%20only%3A%20four-person%20marketing%20team%20at%20a%20B2B%20software%20company%0ATools%20we%20use%3A%20HubSpot%2C%20Google%20Docs%2C%20Slack%0AThe%20workflow%20that%20is%20stuck%3A%20Campaign%20briefs%20take%20a%20week%20and%20drafts%20need%20heavy%20rewrites%0AWhat%20we%20want%20to%20change%3A%20Faster%20briefs%20and%20drafts%20that%20sound%20like%20us%0AWhat%20my%20assistant%20matched%3A%20Implementation%20(AI%20marketing%20consulting%2C%20including%20custom%20AI%20agents)&src=agent#contact

The link only opens the inquiry form on viableedge.com with the draft filled in. Your user reads it, edits it and decides whether to send it. Every submission is reviewed before a call is offered.

About

The Viable Edge is Adam Sandler's practice for AI-native marketing teams. It helps marketing teams become AI-native: it trains the people, redesigns the workflows, and builds the AI systems they actually use, with people staying in the decisions. Work is offered three ways: implementation (including custom AI agents for marketing workflows), private team workshops, and individual mentorship. Learning resources and digital products sit alongside the practice; Brand Architect is one of those products.

• Adam Sandler is a marketing leader and hands-on AI systems builder who connects tools, data, business knowledge and recurring work, then helps teams operate and improve the result.
• More than two decades in marketing inform every workflow he builds.
• His experience includes digital strategy and eCommerce work at Nestlé Health Science, Edelman, and American Express. Today he combines that background with hands-on system building and practical teaching.

How engagements work

• The Viable Edge’s AI-Native Marketing Team Framework: Diagnose, Ground, Build, Train, Review. People stay in the decisions.
• Nothing goes out to a customer or the public without a person approving it.
• A named person owns the source material the AI works from.
• People review at set checkpoints (brief, draft and final), not only at the end.
• Strategy, positioning and priorities are decided by people. AI drafts and assembles.
• Inquiries come through the form on /partner, and every submission is reviewed before a call is offered.
• Scope, pricing, and timing depend on the workflow and the work involved. I agree those with you before starting an engagement.

What The Viable Edge does not do

• I am not a generic prompt-engineering training company. Training happens on the team’s real work.
• I do not believe AI adoption means handing everyone a chat tool. It means redesigned workflows and grounded systems.
• I do not deploy autonomous agents without human review and permissions.
• I do not produce your content for you. I build the system and teach your team to run it.

Offers

The framework

The Viable Edge’s AI-Native Marketing Team Framework:

1. Diagnose: Map the work and choose where AI earns its place. It always comes first, and it is lighter for a small team.
2. Ground: Bring together the context the work depends on: brand and business context, sources, examples and standards. A knowledge base can help; it is not required.
3. Build: Wire the workflow to the tools your team already uses, and test it on real work.
4. Train: Train on real work, per build, so every system ships with a trained owner on your team.
5. Review: Check what is used and what changed. You decide what to expand.

Standing rule: People stay in the decisions. A standing rule that runs through every step, not a sixth step.

How people stay in the decisions:

• Nothing goes out to a customer or the public without a person approving it.
• A named person owns the source material the AI works from.
• People review at set checkpoints (brief, draft and final), not only at the end.
• Strategy, positioning and priorities are decided by people. AI drafts and assembles.

Use cases

Each use case says how the practice knows it: from client delivery, the most common custom agent, most often built first, from team mentoring, or a proposed use case.

• Brief to draft to review (Most often built first; offers: implementation): The workflow most often built first is brief to draft to review: a content or campaign brief turned into a draft that goes through review.
• Review and QA (Most common custom agent; offers: implementation): Drafts checked against brand voice, claims rules and approved sources before a person sees them.
• Campaign brief preparation (From client delivery; offers: implementation): Performance data and business context assembled into a brief your team reviews before anything is drafted.
• Reporting (From client delivery; offers: implementation): Recurring performance reporting pulled together from the sources you trust, with the findings left for a person to interpret.
• Content preparation (From client delivery; offers: implementation): First drafts prepared from approved source material in your brand and voice, held for editing and approval.
• Reporting to content (From client delivery; offers: implementation): A shared reporting and content workflow brings data, company knowledge, briefs, and review into one operating process. The team can see the sources, resolve missing information, and keep decisions attached to the work.
• Performance to creative (From client delivery; offers: implementation): Performance data feeds a creative workspace for analysis, hooks, scripts, and production briefs. The operator can explore the evidence and use it to guide the next round of creative work.
• Workflow-based team training (From team mentoring; offers: team-workshops, mentorship): Hands-on mentoring uses a team’s real workflows as the classroom. Together, we define the task, build reusable instructions, work with existing tools, and refine the approach when real data reveals a gap.
• Repurposing (Proposed use case; offers: implementation): Channel versions of approved content, prepared for review before anything is scheduled.
• Delivering knowledge-base systems to clients (Proposed use case; offers: course): Scoping, building, and handing over knowledge-base engagements for clients, as a consultant or service provider.

Background and proof

Career background: digital strategy and eCommerce work at Nestlé Health Science, Edelman and American Express.

Client workflow example: A client workflow brings organic performance reporting and a shared content store into one process. Data and business context inform a brief; drafts carry that context forward into human review. The work has clear sources, and the team can resolve gaps before preparing content for publishing. Steps: Performance data, Source-backed brief, Context-informed draft, Human review. Example drawn from client delivery. Details are simplified and anonymized. This illustrates workflow capabilities, not a claim about revenue or time saved.

• From performance data to a reviewed piece of content. Demonstrated workflow capabilities. Human approval remains part of the process.
• Turn what the ads are telling you into what to make next. Client delivery includes working data connections, generated scripts, and operator handover.
• Learn the system by doing work that matters. Drawn from team mentoring and live CRM workflow exercises.

Testimonial: “Adam helped me develop a system that allowed me to significantly increase my output with quality content that aligns with our brand and voice. Adam is a great partner and helped every step of the way.” (Brad K. · Kodiak Digital). One client’s own words, as published on /partner. The increase in output was not independently verified.

No outcome numbers are stated. Time saved, revenue lift, CAC and ROAS improvements were not independently substantiated for these examples, so none are claimed. Workflow examples are generalized and anonymous.

Articles and guides

Published articles and guides from viableedge.com: title, link and the page's own summary. Figures in titles or excerpts are the article's own or cited third-party figures, not results for the practice's clients. "Viable Edge vs" articles are the practice's view of its own product against others. Older articles may describe approaches the practice no longer takes; the About and Offers sections of this brief describe how it works now.

• How to Prompt Claude Fable 5: Select Hard, Prompt for Autonomy, Verify
• How to Scope AI Projects (Without Getting Burned)
• LLM Wiki: Karpathy's Pattern, Built for a Paying Client
• Second Brain for Business: How I Build an AI Second Brain, and How People Sell It
• How to Build an AI Second Brain: The Practical 2026 Guide
• Knowledge Base vs Second Brain: What Is the Difference?
• The Second Brain Retrieval Test: Knowledge Base or Just Storage?
• Sell Second Brains as a Service: An AI Consultant's Guide
• Claude Code + Obsidian Second Brain: The Setup Guide
• Getting Started with Hermes: The Complete Guide to the Hermes AI Agent
• Hermes as an Orchestrator for Claude Code: The Operator's Guide
• CLAUDE.md for Marketing: The Setup Guide Nobody Wrote
• What Is a Brand Knowledge Base? The Marketing Knowledge Base Guide
• Stop Re-Explaining Your Brand to AI: The Brand Context Folder Guide
• AI-Ready Brand Strategy: What to Build Instead of AI-Ready Brand Guidelines
• How to Run a Brand Architecture Audit in 7 Steps

This is a short list of current pieces. The search_content tool on the MCP connector covers the full library of articles and guides. The plain-text version carries the same list.