Your experts are more productive. Is everyone else?
Your best people are building skills and getting real value from AI. They know what to ask, which evidence matters, and when an answer misses the point.
Sharing those skills is a useful start. The people using them also need access to the judgment that makes them effective.
The AI reviewer misses what the expert would catch.
An AI reviewer follows the instructions but misses what the expert would catch.
Individual systems create shared operational problems.
Two teams build systems that work individually but create problems for shared operations.
A polished recommendation hides unresolved assumptions.
A polished recommendation leaves someone else to discover the assumptions holding it together.
See how expert judgment changes the work.
Follow the evidence, draft recommendation, expert correction, and revised output.
The walkthrough illustrates a correction within one case. The governing judgment system establishes how that judgment applies across cases: which evidence is allowed, which checks must pass, where exceptions apply, and who has authority to accept the result.
The walkthrough uses fictional data to illustrate the workflow; it isn’t a live AI session. The product interface is under active development.
Authorized accounts only. Working prototype for invited users. Opens in a new tab.
Enterprise technology advisory
The workflow covers:
- Evidence intake
- Methodology-guided generation
- Expert corrections
- Recorded review history
An expert correction does not automatically change the shared methodology.
Bring the skills you already use.
A skill can gather evidence, analyze a problem, or prepare a recommendation. It can be the foundation of a Knerd AI case.
A skill performs work. The governing methodology determines how that work is judged. Knerd enforces the requirements governing that judgment.
A finished-looking output doesn’t establish that those requirements have been met.
Make expert judgment a shared organizational capability.
Experts bring a method for deciding which questions matter, what the evidence supports, where exceptions apply, and what determines done.
Knerd makes that governing structure explicit.
Practitioners can bring different evidence and reach different conclusions. They should be able to explain those conclusions using the same underlying language and standards.
An expert correction doesn’t automatically become organizational policy. Changes to the shared methodology require separate evaluation and approval, including consideration of earlier judgments that may need another look.
Start with one recurring judgment.
Choose a judgment that people across your organization need to use. Bring the expert, existing guidance, representative cases, and any skills already supporting the work.
We work with you to codify the expert’s methodology. We examine where recommendations succeed, where the expert corrects them, and which distinctions change the outcome.
Then we apply DAPM to structure the judgment system, configure its requirements in Knerd, and evaluate it against representative cases.
The pilot measures whether people can use the expert’s judgment more effectively in their own work. We agree on measures suited to the use case, such as assessment quality, rework, and time to an acceptable result.
Discuss a pilotGrounded in the work of Layer2C.
Layer2C is our research and advisory practice. It began with one expert applying a judgment-heavy methodology across a changing technology market.
AI accelerated the assessments. Consistency depended on explicit standards for which evidence counted, which conclusions were supported, and what determined done.
That work established the methodological foundation for Knerd AI. It also exposed the limits of relying on an expert’s personal attention to enforce the method.
Knerd puts that governing approach into software so more people can work with the expert’s judgment.
The Layer2C case study explains what the process demonstrated and how that experience informs the product.
Read the Layer2C case studyWhere does your organization need expert judgment?
Marketing teams need reviews that reflect their editorial standards. Architects need a common basis for evaluating different designs. Sales teams need experienced commercial judgment. Operations teams need consistent criteria for readiness and escalation.
Each has its own methodology. Each needs a way to make that methodology usable beyond the expert who developed it.
Bring us a judgment your organization needs to apply.
Let’s discuss how your experts make it today, who needs access to it, and what it would take to put that judgment to work across your organization.
Start a conversationKeith Townsend
Co-founder, Common Knerd
Keith on LinkedInCommon Knerd is the company behind Knerd AI. Talk with co-founder Keith Townsend about your organization’s judgment system.