Choosing your stack

The ecosystems compared, the subscription math, data controls, and an opinionated shortlist by job.

5 lessons · For: Anyone assembling or auditing their AI lineup — which ecosystems to live in, what to pay for, and how to keep the whole thing current. · Product details last reviewed July 2026

Most people's AI lineup is an accident: whatever they tried first, plus whatever work pays for. This course makes it a decision. We compare the ecosystems honestly, do the subscription math, treat privacy settings as the professional obligation they are, and end with the discipline that outlasts every product cycle: re-evaluating on a schedule instead of on hype.

A dated caveat, worn proudly: this is the most perishable course in the library. The judgment framework is permanent; the specific picks were last reviewed on the date stamped at the top of this page, and they will change. That is not a flaw — knowing that is the lesson.

1. Lesson 1

   The ecosystems, briefly

   OpenAI ships the broadest consumer product: ChatGPT is where new capabilities tend to land first, and its ecosystem — voice, images, video, agents, custom GPTs — is the widest. Anthropic's Claude has the strongest reputation for writing quality, careful handling of long and nuanced work, and agentic coding; its center of gravity is professionals with words and code at stake. Google's advantage is distribution and price-performance: Gemini lives inside Gmail, Docs, Android, and Search, NotebookLM is category-defining, and the free tiers are the most generous going.

   Microsoft packages frontier models (OpenAI's, and increasingly Anthropic's too) into the tools work already runs on — for many organizations, Copilot is simply the AI that is allowed. xAI's Grok trades polish for immediacy: wired into X's live firehose, opinionated, lightly filtered — strongest on what is happening right now. Meta gives AI away inside WhatsApp and Instagram, ambient rather than professional. And the open-weight world — Llama, Mistral, Qwen, DeepSeek — is less an ecosystem than an escape hatch: control and cost for those who can host their own. Note what shapes the choice: bundle gravity. Where your email, files, and employer already sit pulls harder than any benchmark.

   Try it this week

   Write down which ecosystems you already inhabit — Workspace or Microsoft 365, iPhone or Android, X user or not, employer-approved tools. Circle where you already pay. Your realistic shortlist is usually two names, and the bundle just wrote it for you.

2. Lesson 2

   The subscription math

   The tiers are consistent across the industry. Free gets you a real product with caps — the right place to start and, for light use, to stay. The ~$20 tier (ChatGPT Plus, Claude Pro, Google AI Pro, Perplexity Pro, SuperGrok) is the professional workhorse: best models by default, higher limits, deep research, and it earns its keep the week AI becomes part of how you work. The $100–250 tier (ChatGPT Pro, Claude Max, Google AI Ultra) buys near-unlimited access to the most capable models — justified for people whose entire day runs through the tools, theater for everyone else.

   Two audits keep the spend honest. Overlap: two ~$20 subscriptions doing the same job is the most common waste — differentiate them by task or cut one. And bundles: before adding a subscription, check what your Workspace, Microsoft 365, or existing plan already includes; many professionals discover they are paying separately for a capability their employer already licenses. The "Working economically" guide's stance applies to dollars exactly as to tokens: spend where stakes and volume concentrate, and be able to say why.

   Try it this week

   Total your actual monthly AI spend, including your share of bundles. Map every dollar to the job it does. Cut one overlap or upgrade one bottleneck — but do one of them deliberately this week, with the reason written down.

3. Lesson 3

   Privacy, data, and what never leaves

   Consumer AI products differ sharply on one default: whether your conversations train future models. Every major product now has a data control that answers it — ChatGPT's data controls, Claude's privacy settings, Gemini's activity controls — and a professional sets these deliberately on day one rather than discovering them in an incident. Business and enterprise tiers exist substantially because they change the answer: contractual no-training defaults, retention controls, and admin oversight.

   The workplace rules come straight from the "Keeping it safe" guide and gain teeth here: confidential material goes only into tools your organization has approved for that class of data — the tier matters, not just the brand, because the same product under a consumer login and an enterprise agreement is two different privacy propositions. Regulated data belongs in enterprise agreements or on local models, full stop. And the personal analogue: other people's secrets — a friend's medical situation, a colleague's salary — deserve the same restraint in your personal chats that customer data gets at work.

   Try it this week

   Open the data controls on every AI product you use — tonight, it takes fifteen minutes — and set each one deliberately. Then write your three data classes (public, personal, confidential) and which tool each is allowed in. That one-page policy is E1 safety, done properly.

4. Lesson 4

   The shortlist, by job

   What follows is the opinionated part: current defaults by purpose, chosen for a professional starting fresh today. Runner-up thinking is in each note, because the gap behind the leader is usually one product cycle wide. Purposes not spotlighted below, briefly: meeting capture — Granola or Otter, or whatever your platform bundles; slides — Gamma for speed, your judgment for content; voice synthesis and music — ElevenLabs and Suno lead; automation — Zapier first, n8n when data must stay home; coding — Claude Code or Cursor for engineers, Replit for everyone else (the Building course covers all of these in depth).

   Hold the list loosely. Every pick below has been leapfrogged before and will be again — the durable skill is the picking pattern: name the job, trial the leading two on your real work, keep the one that wins, and re-check on a schedule rather than on headlines.

   In the toolbox

   • Long-form and high-stakes writing — Claude

     Anthropic · Free tier; Pro ~$20/mo

     The prose-quality leader, with Artifacts as the editing surface. Runner-up: ChatGPT with Canvas, which closes most of the gap and adds breadth.

   • Everyday generalist — ChatGPT

     OpenAI · Free tier; Plus ~$20/mo

     The widest capability spread in one product: chat, voice, images, research, data analysis. The default when you want one subscription to cover the most ground.

   • Inside a Google life — Gemini

     Google · Generous free tier; AI Pro ~$20/mo

     If Gmail, Docs, and Drive are your habitat, Gemini's integration beats a better model in another tab. Deep Research and image editing are legitimately front-rank.

   • Mastering a body of material — NotebookLM

     Google · Free; higher limits on AI plans

     Unrivaled for source-grounded study: your documents, cited answers, audio overviews. No real runner-up at what it does.

   • Quick cited answers — Perplexity

     Perplexity · Free tier; Pro ~$20/mo

     The fastest route to a sourced answer. Runner-up: AI Mode in Google Search, which is free and closing fast.

   • What is happening right now — Grok

     xAI · Free tier on X; SuperGrok ~$30/mo

     Live X data gives it the edge on breaking news, sentiment, and the discourse. Treat its lighter filtering as a feature and a caution in equal measure.

   • Images with specific content — ChatGPT · aesthetics — Midjourney · edits — Gemini

     OpenAI · Midjourney · Google · Varies; Midjourney from ~$10/mo

     The three-way split that currently holds: instruction-following and text, beauty, and targeted editing respectively. Firefly when commercial licensing is the constraint.

   • Video generation — Veo (Gemini/Flow) or Sora

     Google · OpenAI · Paid tiers, evolving fast

     The most volatile category in this library — capabilities and access change quarterly. Trial both with your actual use case before subscribing to either.

   Try it this week

   Find the one job where your current tool is habit rather than choice. Run this week's real work through the shortlist pick alongside your incumbent, and keep the winner. One deliberate swap teaches the picking pattern better than any comparison table.

5. Lesson 5

   Staying current without churning

   The product cycle is now faster than any curriculum: models leapfrog each other every few months, features cross-pollinate within weeks, and this course's specifics will age accordingly. The two failure modes are symmetric — chasing every launch (expensive, distracting, and mostly noise) and never re-checking (running last year's stack against this year's competition). The professionals who stay current cheaply do it with a ritual, not a feed.

   The ritual: keep three benchmark prompts drawn from your real work — your hardest recurring analysis, your most representative writing task, your most common quick question. Once a quarter, spend one hour running them against the current leaders and your incumbents, and switch only on a clear win. That is the whole system. And it rests on the deeper point this library keeps returning to: products are the volatile layer; the six competencies — asking, context, checking, combining, delivering, safety — are the durable one. Master those and every new product is a Tuesday, not a reinvention. That durable layer is what the Emeri exam certifies.

   Try it this week

   Write your three benchmark prompts today and save them with this quarter's outputs from your current stack. Put one hour on the calendar three months out. You have just replaced AI-news anxiety with a system.

The products above change; the judgment the exam scores does not. The study guides teach that durable layer, and the free check scores you on it in about fifteen minutes.