🛠️Why Every Firm Should Create a Skill Library
1. Key Themes
Theme 1: AI Access Is Now Table Stakes — Differentiation Lives in Encoded Judgment
The commoditization of AI tools means that merely having access to frontier models no longer confers competitive advantage. The real moat is the firm-specific judgment encoded into how those tools are deployed.
"This year your fund will buy roughly the same AI as the fund that beat you on your last term sheet. Same frontier model, same sourcing platforms, same enrichment layers, same chat box. The capability you are paying a premium for is quietly becoming the capability everyone has."
"Not having access to these tools is negative alpha. It's a disadvantage. But for those firms that have access to the same cutting-edge tools, the alpha is somewhere else."
Theme 2: The Distinction Between a Prompt and a Skill Is a Strategic Inflection Point
The article draws a hard line between one-off prompts (tactical, disposable) and skills (durable, repeatable, judgment-laden). Firms that build skill libraries are essentially converting tacit partner knowledge into scalable institutional infrastructure.
"A prompt tells the model what to do once. A skill captures how your firm does a kind of work every time it comes up... A skill packages procedure and judgment together. The steps, the edge cases, the questions that always get asked, and the quality bar the partnership refuses to drop below."
"Skills make judgment repeatable."
Theme 3: The Skill Library as the New Institutional Asset
Just as code libraries, APIs, and workflow automation made prior forms of knowledge reusable, skill libraries represent the next evolution — making investment judgment itself reusable and compounding over time.
"Libraries made code reusable. APIs made services reusable. Workflows made business processes reusable. Skills make judgment repeatable."
"The second fund is a different firm. Its agents know how the partnership sources, screens, diligences, writes the memo, supports founders, and updates LPs — not perfectly, but consistently enough to compound."
Theme 4: Operationalized AI vs. Chat-Window AI — A Measurable Performance Gap
The article cites a data point from Retterath's own upcoming research showing a dramatic adoption gap between firms that have embedded AI into workflows versus those using it as a bolt-on chat tool.
"The funds that have operationalized AI into their actual workflows report full scale adoption at roughly 50%. The funds still treating AI as a chat window bolted onto the old process sit at roughly 3%. Same models available to both. Wildly different firms."
Theme 5: Most Firm Knowledge Is Invisible — and That's a Solvable Problem
The tacit, undocumented nature of investment methodology is framed not as inevitable but as a correctable gap. Firms are sitting on an encoded-knowledge deficit that skills can address.
"That knowledge got treated as background but in reality is a key asset. It's the taste of your firm. An agent is only useful when it understands more than the task. It has to understand the method behind the task."
"Every firm already has a method. Most of it is invisible, sitting in old memos, Slack threads, reference calls, and the heads of the people who know how the work really gets done."
2. Contrarian Perspectives
Perspective 1: Open-Source and Public AI Skill Marketplaces Will Be Largely Irrelevant for Serious Investment Firms
The consensus expectation is that shared AI resources and open-source tooling democratize capability. Retterath argues the opposite: the most valuable skills are inherently private and firm-specific, making public marketplaces a distraction.
"Public skill marketplaces are coming, and most of what they contain is generic. Not too relevant for investment firms. Too much noise, too little signal."
"I'm convinced that the most valuable skills will live inside firms, because the valuable methods are specific. They're the true secret sauce. Your pass criteria, your reference script, the exact shape of your IC memo, your portfolio triage logic, the voice of your LP letter. None of that is downloadable."
Perspective 2: Data Access Is Not the Hard Part of AI — It's the Easy Part
Most firms treat connecting AI to their data (CRM, deal notes, data rooms) as the central AI challenge. The article argues this is the easy and largely solved part; the hard and unaddressed problem is teaching the agent how the firm thinks.
"Most firms begin their AI effort with access, and it feels like real progress... But access does not produce good judgment. It produces a confident memo that misses the one thing your best partner would have caught on the first read. A model can ingest every note in the CRM and still not understand how your firm decides to pass."
Perspective 3: The Bottom-Up (Democratized) Skill-Building Path Outperforms the Top-Down Structured Path in Practice
The intuitive assumption is that a rigorous, top-down methodology-mapping exercise produces the highest quality output. Retterath's empirical experience suggests the messier, bottom-up approach actually delivers faster firm-wide efficiency gains.
"While the first path has higher signal to noise ratio, the second drives more creativity and inspiration, and based on my own experience a shorter time to efficiency across the firm."
3. Companies Identified
- Description: AI-first CRM platform for private capital / VC firms
- Why mentioned: Newsletter sponsor; cited as a tool for connecting live deal pipeline data to frontier AI models via a hosted MCP server
- Quote: "Affinity's new hosted MCP server connects your live CRM directly to Claude, ChatGPT, Copilot, and Gemini. Your AI assistant can now read from and write back to your pipeline in natural language."
- Description: Partner organization collaborating with Data Driven VC on VC-specific AI skills
- Why mentioned: Co-creator of vcskills.com, a curated library of VC-relevant AI skills
- Quote: "In our DDVC Slack group, we started collecting and curating VC-related skills, and made it available with our partner OverDrive here: https://www.vcskills.com/"
- Description: European VC firm (Andre Retterath's firm)
- Why mentioned: Used as a real-world example of a firm that has already built an internal wiki capturing process, assessments, deep dives, and post-mortems — an analogue to a skill library
- Quote: "At Earlybird, we have an internal wiki that contains majority of our process, assessment, deep dive, post-mortem, and other knowledge."
4. People Identified
Andre Retterath
- Description: Partner at Earlybird Venture Capital; author of the Data Driven VC newsletter
- Why mentioned: Author of the piece; draws on first-hand experience building AI-enabled workflows at Earlybird and running the DDVC community
- Quote: "Hi, I'm Andre and welcome to my newsletter Data Driven VC which is all about becoming a better investor with data and AI."
5. Operating Insights
Insight 1: Build Your Skill Library Using Both Top-Down and Bottom-Up Paths — But Bias Toward Bottom-Up for Speed
Two concrete implementation paths exist. The top-down path (map workflows → shadow partners → codify into skills) yields higher signal quality. The bottom-up path (individuals create skills freely → central reviewer screens for security/privacy → firm-wide rollout) yields faster adoption. The article recommends Git repos or enterprise managed settings for distribution.
"While the first path has higher signal to noise ratio, the second drives more creativity and inspiration, and based on my own experience a shorter time to efficiency across the firm. In either case, the skills can be rolled out via shared Git repos or enterprise managed settings and org-wide rollout plans."
Insight 2: Encode the Specific, Not the Generic — Skills Must Capture Edge Cases and Quality Bars, Not Just Process Steps
Generic process documentation has existed in VC for decades and hasn't compounded. The operative difference in a skill is that it captures the judgment layers: edge cases, the questions that always get asked, and the quality thresholds the partnership won't compromise.
"It is the qualification lens a partner applies before they will take a meeting. It is the diligence checklist that exposes a coached reference, and the memo structure that forces the bear case onto the page whether the deal lead wants it there or not."
Insight 3: The Transition Point Is When the Playbook Stops Being a Document and Becomes a Worker
The article identifies a specific inflection in AI maturity: the moment a firm's methodology moves from passive documentation to an active agent that can load the playbook, pull data, run analysis, and execute — without human initiation at each step.
"With skills, the playbook stops being a document and becomes a worker."
6. Overlooked Insights
Insight 1: The DDVC Landscape Data — A Forthcoming Dataset on VC AI Adoption Worth Watching
The 50% vs. 3% adoption figures cited in the article are previews from an upcoming DDVC Landscape report. This data set, once published, could be a high-signal benchmark for how the VC industry is actually (not theoretically) deploying AI — and may inform investment theses around VC infrastructure tooling.
"This is exactly the split showing up in the data for our upcoming DDVC Landscape. The funds that have operationalized AI into their actual workflows report full scale adoption at roughly 50%. The funds still treating AI as a chat window bolted onto the old process sit at roughly 3%."
Insight 2: The Security/Privacy Review Step in Bottom-Up Skill Creation Is an Unspoken Risk Vector
In describing the democratized path, Retterath casually mentions that a central reviewer must screen submissions to ensure "no personal information or structural vulnerabilities get introduced." This implies that ad hoc skill creation carries real information security and data governance risks — a concern that is underweighted in the broader AI-in-VC conversation.
"If individuals feel that specific skills might be useful for others in their firm, they can submit it to a central reviewer (to ensure no personal information or structural vulnerabilities get introduced) who then makes it available for the broader firm."