Needs & problems
Start from the job you need done. Each page gives the stack, the steps and the traps.
Access many AI models from one platform · Add voiceover to content · Analyze customer feedback at scale
36 entriesSearch a need, a question, a service or a model. Every page explains how it works, what it is good for, where it falls short and which stack it fits, with sources and the date we last checked.
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186 wiki entries · 122 tools · 9 stacks
Start from the job you need done. Each page gives the stack, the steps and the traps.
Access many AI models from one platform · Add voiceover to content · Analyze customer feedback at scale
36 entriesOne specific question each, answered first in a few sentences, then explained.
Automate with GitHub Actions · Can I run AI models on my own computer or server? · Can I track my ranking in ChatGPT the way I track Google rankings?
63 entriesCategories of service, how to choose within them, and every tool we track.
Agent platforms · AI app builders · AI assistants
21 categories · 122 toolsModel families: lineup, access, fit and limits, with a dated spec table.
Amazon Nova models (AWS) · Claude (Anthropic) · Cohere models (Command, Embed, Rerank)
12 entriesPlain-English definitions with the business consequence of each term.
Affiliate and sponsorship disclosure · Agent harness · Agent skills (SKILL.md)
54 entriesPaired tools for each business function, with the data flow between them.
9 stacksKeep numbers in the systems that create them. Have an automation hub copy a few key metrics into one sheet on a schedule, then let an AI assistant read that sheet and write the summary. Start with three metrics. The agent reads one clean table, so its claims are easy to check.
Make sure AI answer engines can find, understand and repeat accurate facts about your business, and that the third-party sources they cite mention you. It's SEO fundamentals plus consistent facts and earned mentions. Measure with a fixed prompt set over time.
Use AI to read each new form fill or inbound email, enrich it with company data, score it against your ideal customer profile, and route it to the right person or sequence within minutes. Keep the scoring rules visible and review a sample weekly so good leads don't get filtered out.
Let AI answer common questions from your help content and draft replies for the rest, with a clear hand-off to people for anything sensitive. Success depends on good documentation, strict grounding and weekly review of answers.
Start onboarding from the payment event: create the CRM record, send a personal welcome, collect intake details, invite to support channels, and chase only what's missing before the kickoff call. Automation handles logistics; people handle the relationship.
Record the process once, as a screen recording or call. Have AI draft the SOP from it, have the owner correct it, and store it where people and agents can both read it. Then turn the most-used SOPs into shared custom assistants, so the process gets followed, not just filed.
Use an answer engine or research agent that searches the live web and returns sources, rather than a model answering from memory. Give it a fixed brief (competitors, questions, date range), require citations and dates, and check the key claims yourself before they reach a deck.
Design permissions before prompts. Give the agent its own scoped credentials, a test or staging area where mistakes are cheap, an automatic way to check its work, and a hard boundary it cannot cross. Start with read-only access, and require human approval for anything that sends, pays or deletes.
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