Expert-built decision layer
Capability starts from expert decision logic captured in interviews and tightened through review, not from generic model summarisation.
For design partners who need protected, permissioned workflows shaped by production AI skills and reviewable decision overlays, not generic model output.
Selective design-partner engagement. Conversations stay relevant to your workflow and trust boundary.
Exploratory intro only. Booking does not create a contract, commitment, or commercial obligation.
What design partners get
Skillify packages expert tacit judgment as reviewable, reusable skills that can be inserted into a real partner workflow, with ownership, permissioning, and trust boundaries kept explicit.
Capability starts from expert decision logic captured in interviews and tightened through review, not from generic model summarisation.
Judgment is packaged into triggers, decision logic, and workflow-ready behavior that can travel with the partner’s operating context.
Expert IP and partner data stay permissioned. Nothing is publicly disclosed without approval, and use remains governed by agreement.
How Skillify works
Skillify starts by capturing expert judgment, validates that reasoning with the expert, then packages it as production AI skills and decision overlays for an agreed design-partner workflow.
Real decision moments are compressed into reviewable skills the expert can check and keep attribution over.
We capture real cases, judgment calls, and the reasoning behind them.
Skillify pulls out reusable decision logic, triggers, and edge-case handling.
The strongest skills are tightened, clarified, and checked with the expert.
A private skill artifact is returned for expert review, with participation when approved skills are deployed in live Skillify workflows.
The same skills move from expert-validated artifact into an agreed workflow used by a design partner.
Skills are structured into logic, overlays, and workflow-ready system behavior.
The capability is inserted into a real operating context rather than left as a memo.
The partner gets AI workflow output shaped by an expert-built decision layer, not generic AI summarisation.
New partner cases and expert review feed back into the system to improve the capability over time.
Why this matters
The most valuable part of expert performance is rarely written down. It sits in pattern recognition, exception handling, and what gets weighted when conditions change.
Foundation models can restate the obvious. They are less reliable when the job is to notice which assumption just broke and how that should update the decision.
If expert judgment is not captured, validated, and kept usable as a skill, partner workflows stay fragile, expensive, and hard to trust where edge cases matter most.
Design partner engagement
5–15 minutes to confirm fit, workflow relevance, and whether a design-partner track is worth starting. Exploratory only: no contract or commitment implied.
Identify one concrete operating context where skills-first capability would change output quality.
Deploy a permissioned skill package into that workflow and review outputs against expert standards.
Partner cases and expert review tighten the capability. Deeper involvement is possible, not assumed.
What partners influence
Help define how expert reasoning is structured for live partner workflows.
Push the system toward what matters in operating judgment, not generic model theatre.
See how validated skills translate into decision overlays and deployable workflow tools.
Work inside clear permissioning so expert IP and partner context stay governed.
“The days of people making decisions in their own heads are ending.”
Ray Dalio
Founder, Bridgewater Associates
“The vast majority of human knowledge is not expressed in text; it’s in the subconscious part of your mind.”
Yann LeCun
Chief AI Scientist, Meta
Together these capture Skillify’s thesis: more decisions are moving into systems, but the knowledge those systems need often lives in expert judgment rather than text alone.
Knowledge handling and trust
Interviews, case walkthroughs, partner context, and draft artifacts are treated as private unless a different agreement is made explicitly.
We care about where a skill came from, how it was derived, and what confidence belongs around it.
The goal is not extraction theatre. It is to structure expert judgment so it remains useful, reviewable, and only used where partners have agreed.
Skillify does not provide investment advice, trading signals, order execution, broker routing, client-asset management, or guaranteed outcomes. Public examples are illustrative, not live signals or automated trade execution. Experts should not share employer-confidential or client-confidential material. Interviews, partner data, and draft artifacts remain private by default and are only used where permissioned. Nothing is disclosed publicly without explicit agreement. See Disclaimer, Privacy, and Terms.
Who is behind this
Skillify is being developed within Blackkite Ventures as a focused effort to convert tacit expert judgment into validated AI capability.
Founder
Former macro PM with 10 years of experience building and evaluating macro research processes, including at BFAM Partners and ExodusPoint.
The best workflows often depend on judgment that is real, valuable, and largely undocumented. Skillify is an attempt to preserve and operationalise that layer without pretending generic AI already solved it.
Design partners evaluating skills-first capability, and experts whose judgment is difficult to replicate with generic AI. We keep outreach selective.
Expert judgment is packaged as production AI skills with triggers, decision logic, and workflow behavior, including reviewable decision overlays, not as a loose prompt library or generic chatbot wrapper.
A standard flow starts with a 5–15 minute intro call, then moves into workflow scoping or an expert session only if there is clear mutual fit. The intro is exploratory. Booking does not create a contract or commitment.
No. Intro calls are exploratory conversations to check fit. No paid engagement, exclusivity, or commercial obligation is implied unless a separate written agreement is made later.
Confidential by default. Expert IP and partner data stay permissioned. Nothing is published or shared publicly without agreement. See our Privacy page for more detail.
No. Skillify does not provide investment advice, trading signals, order execution, broker routing, client-asset management, or guaranteed alpha. Illustrative examples on this site are not live signals. See the Disclaimer.
Not by default. Attribution and public reference only happen with explicit agreement. Raw expert logic and private partner context are not exposed on the public site.
If your workflow depends on judgment that generic systems do not reliably capture, we would value the conversation.
Exploratory intro only: no contract, commitment, or commercial obligation is implied by booking.