Every agent action is logged
What each agent read, drafted and sent, with who approved it.
How we work · What we build · Step 04
Self-improving AI starts below the prompt
A pile of prompt corrections will steer your AI off a cliff. It improves when it can see all your data, understands how your business works, and is judged on results.
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Why corrections alone don't work
Plenty of teams are correcting their AI. They fix a draft, tweak a prompt, add a rule. Each fix feels like progress. But if the AI can't see most of your data, or sees it without understanding what it means, the corrections have nothing solid to land on. They pile up, contradict each other, and drift.
There's a big difference between a couple of markdown files and a real model of how your business works. The model teaches AI how a function actually runs: your journey stages, your definitions, what a qualified opportunity is, which signals matter. Corrections only make the system better when they land inside that model, and when they're checked against what happened to buyers. That read is step 4 of our process.
The layers self-improvement depends on
In order. Each one rests on the one before it.
| Layer | What it gives the AI | Where we build it |
|---|---|---|
| 1. Reliable access to all your data | Every touch, call, email, deal and outcome, not one tool's slice | GTM data warehouse |
| 2. A model of how your business works | What the data means: stages, definitions, how your funnel runs | GTM data warehouse · Your GTM brain |
| 3. GTM knowledge and strategy | Signals, accounts, personas, positioning, built on top of that model | GTM strategy · Custom signals and intent |
| 4. Repeatable skills | Your best way of doing a task, written down so it runs the same every time | Skills |
| 5. A workspace for people and agents | One place where your team and its agents do the work | AI workspace |
| 6. Agents doing it consistently | The work done the same way, every day | Agents |
| 7. Reporting on top | A read on what happened to buyers, against a comparison | AI reporting and analysis |
What runs today, and what's in progress
A person approves what buyers see
Every play keeps its approvals. Nothing changes that.
The lift on every play
Each play read against comparison accounts, the result that tells you whether a change helped.
Changes proposed from resultsIn progress
When a play's read says something isn't working, we propose the change to the skill, the argument or the model, with the evidence attached.
The model kept currentIn progress
New definitions, stages and signals added as the business changes, so corrections have something accurate to land on.
Where to start
AI operating partnership
Self-improvement runs inside the AI operating partnership: 6+ months, working with your team to drive more pipeline and revenue. It starts with the data and the model a bootcamp puts in place.
Before you book
Is this running for clients today?
Logging, approvals and comparison reads run today. Proposing changes from results is what we're building now.
Can't we just keep correcting our prompts?
You can, and it helps for a while. Without the data and a model of your business underneath, the corrections start contradicting each other. That's when the drafts get worse.
Where do we start if we have none of the layers?
With the first two: your data in one place and a model of what it means. That's week one of the bootcamp, and it's what RevOps teams and executives usually ask us to fix first.
Where's your line stuck?
See which layer you're missing
30 minutes. We'll tell you where your AI is losing the thread.
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