The AI Tool Stack: What Actually Works in 2026
After 3 years of testing every AI tool on the market, here's what stuck in our production workflow. The tools, how we use them, and what we dropped.
Kathy Slowinski
CEO, Trilogy | The AI Boss
We’ve tested dozens of AI tools over three years. Most didn’t stick. Here’s what survived into our daily production workflow and why.
The Foundation: Enterprise Chat AI
ChatGPT Enterprise and Claude are the backbone of our AI operations. Every employee has access to both. The key insight: don’t pick one. Different models excel at different tasks.
We use ChatGPT for brainstorming, data analysis, and general-purpose tasks. We use Claude for longer documents, nuanced analysis, and tasks that require careful reasoning.
Enterprise plans are non-negotiable. Don’t rely on free tiers. The data privacy protections, longer context windows, and team management features are worth every dollar.
Code: AI-Assisted Development
GitHub Copilot for code completion. Claude and ChatGPT for code review, architecture decisions, and debugging complex issues.
The combination reduced our codebase from 3M lines to 125K. Not by deleting code, but by rewriting it more efficiently with AI assistance. The AWS bill dropped proportionally.
Customer Support
Our AI support system handles 80% of customer inquiries. Built on a combination of fine-tuned models and our internal knowledge base (the Second Brain).
The remaining 20% gets escalated to humans, but those humans have AI assistance too. The result: faster resolution, higher satisfaction, lower cost.
Content and Communication
AI assists with every piece of written content: emails, product specs, board decks, marketing materials, internal documentation. Not by writing everything from scratch, but by drafting, editing, and reformatting.
Board deck prep went from a full day to 90 minutes. Product specs went from multiple days to one hour.
What We Dropped
- Specialized AI writing tools: Enterprise ChatGPT and Claude handle this better than niche tools
- AI meeting transcription services: Useful but not transformative enough for the cost
- Custom-built internal models: Maintenance overhead was too high. Use the frontier models.
The Principle
Buy enterprise subscriptions to the best general-purpose models. Build custom workflows on top of them. Don’t build from scratch unless you have a very specific reason.
The tool stack matters less than the culture of usage. The best tool in the world is useless if people don’t use it daily.
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