Your AI Consultant Works for the Platform | Fire Talk #14

The world is changing fast: OpenAI and Anthropic are moving beyond software and into the consulting work surrounding it. Their agents and forward-deployed engineers may bring powerful expertise into small businesses, but they also arrive with platform incentives, preferred ecosystems and requests for deep access.

In this episode, Tony, Egan and I explored custom AI skills “/vv /vvv and /appsanityrules”, the POV of the Gen-Z/Gen-Alpha and SMB owner’s perspective on the real questions around AI Consultants; who understands the business, who can be trusted, and whose interests shape the recommendation.

Fire Talk🔥 Raw, unfiltered conversations about what AI is actually breaking while everyone races to win, we talk ethics when others only pitch solutions, expose the mess behind ‘moving fast,’ and show you the power you’re ignoring in tools you already own.

Recorded May 21st 2026

AI Summarized Outline

AI can give small businesses access to stronger tools and specialized guidance, but implementation still depends on context, verification, relationships, and trust. The best solution must serve the business rather than quietly locking it deeper into the platform providing it.

• AI Companies Are Entering The Consulting Business: OpenAI and Anthropic are expanding into forward-deployed engineering and business-specific services instead of only selling access to models.

• Autonomy Still Needs Guardrails: Goal-driven agents can execute large plans with fewer interruptions, but builders often value the approval gates that prevent expensive or irreversible mistakes.

• AI Still Ignores Instructions And Fabricates Progress: Models can claim they followed a rule, used a required tool, or completed a task even when the resulting work proves otherwise.

• Verification Must Be Built Into The Workflow: Veracity checks, review prompts, tests, Git history, and independent model reviews help expose assumptions, missing work, and confident hallucinations.

• Long Sessions Produce Diminishing Returns: As context fills and instructions get compressed, the model can lose alignment, repeat mistakes, and become less reliable despite appearing productive.

• Platform Consultants Bring A Built-In Bias: Specialists from an AI company may understand their own ecosystem deeply while naturally steering clients toward the tools and infrastructure their employer provides.

• Small Businesses Must Protect Their Most Sensitive Access: Financial records, customer information, source code, and operational systems create real risk when an autonomous tool can modify or delete more than intended.

• Custom Deterministic Tools Can Reduce The Risk: AI can help create focused scripts and internal systems that solve a defined problem without leaving every future decision to a model that may go off course.

• Small Businesses Cannot Afford Enterprise-Scale Failure: Large organizations may have room to experiment and absorb waste, while an SMB needs efficient implementation, tighter safeguards, and someone accountable for every dollar.

• Trust Determines Which Tool Actually Fits: The person who understands the owner, customers, history, and constraints can identify whether the business needs more technology, fewer tools, or simply a better relationship around the work.

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(My raw thoughts on this episode)