Most of what you hear about AI is either breathless hype or so technical it needs a translator, and neither one helps you actually use it. We started this newsletter to fix that. Every issue takes one real pattern we're seeing in how companies put AI to work, explains it in plain language, and shows you what to do with it. We also share what we've built at TigerTiger that you can put to use right away. Our whole job is to make this stuff understandable and genuinely useful, so you can get value out of AI without becoming an engineer to do it.

You've probably noticed your AI has amnesia. You explain your business on Monday, and by Wednesday it's a stranger again, asking who your customers are as if you'd never told it. Every session starts from zero, and that turns out to be the whole reason most AI at work quietly goes nowhere.

There's a number on this now. MIT's NANDA initiative studied more than 300 enterprise AI deployments this year, and 95% of them delivered zero measurable return. The striking part is why. It wasn't that the AI wasn't clever enough, it was that nobody ever gave it a place to keep what it learned about the specific business it was working for. It stayed a brilliant consultant who forgets every meeting the moment it ends.

The fix is to give it that place, which is really just what any new hire needs before they're useful to you. A new person has to learn what the company does and how it makes money, how the work actually gets done as opposed to how the org chart says it does, and where their judgment ends and they need to check with someone. Your AI needs exactly those same things, and once it has them it stops being a confident stranger and starts behaving like someone who has been on the team for a year. That accumulated store of knowledge is what we mean by a brain.

The encouraging part is that you already own the raw material for it. The knowledge of how your business runs is sitting in your Google Drive and your OneDrive, in your call recordings and your inboxes, in the folders on everyone's laptops and the procedures that live in one person's head. You are already paying for all of it every month. It's just scattered across a dozen places, and none of it is anywhere your AI can actually reach. Building the brain is mostly the work of pulling that material into one place your AI can draw from, so that the knowledge which usually walks out the door with a departing employee, or never gets written down at all, finally has somewhere to live.

This is worth doing at two levels, and they build on each other. The first is personal: a brain on your own laptop, so your AI remembers who you are and what you're working on instead of forgetting you between sessions. That's the level our free Memory tier handles, and it's where everyone should start, because it costs nothing and you feel the difference the same day. The second level is the one that actually moves the number in that MIT study: a shared company brain that your whole team draws from, so your ops lead, your sales lead, and you all get answers built on the same picture of the business. That one you build once, deliberately, and then everyone inherits it. It's more work than flipping on a setting, and it's the real prize.

So start with the free tier this week to get your own AI to stop starting from scratch every morning. Then, when you're ready to give the whole company one shared brain rather than a dozen forgetful assistants, that's the project worth taking seriously, and it's the one we're here to help you build.

Every product page and feature we build lives in your Claude Code setup as a tool you can just ask for by name. Here's what's new.

Use-Case Discovery: Scoping an AI project used to be a guessing game: someone says "automate the reports" and three different jobs turn out to be bundled inside that one sentence. This tool interviews the person who actually does the work, one question at a time, and catches the moment a single project turns out to secretly be two. Fifteen minutes with the right person beats a week of guessing. Trigger it with /use-case-discovery, or just tell your AI you want to scope out an AI project.

Document Process: Every team has at least one process that only lives in someone's head. This tool interviews that person and turns their answers into a written procedure a new hire could follow on day one, without anyone shadowing them or filming a screen. Trigger it with /document-process.

Spring Cleaning: A rule you wrote in March to patch one bad output is probably still firing in June, quietly contradicting something newer. Nothing breaks loudly, your setup just gets slower and vaguer. This tool audits your whole Claude Code instruction stack, flags what's outdated or conflicting, and hands you a report to approve before anything changes. Run it quarterly. Trigger it with /spring-cleaning.

Three new planning coaches: /rockefeller-tuneup is a quarterly habit check-in that ends with a concrete 90-day rollout plan. /time-audit looks at three weeks of your calendar and hands you three named moves: what to delegate, what to cut, what to decide on later. /year-as-story turns next year's priorities into a plan you'll actually reopen in June instead of writing once and forgetting.

All four are part of the Pro pack ($49/mo). The free Memory tier sets your AI up with a working knowledge of your business, your people, your voice. Everything that acts on that knowledge, including these four tools, lives in Pro.