Sure Valley Ventures (SVV) says it shared the AI workflows it uses internally on AgenticInvestor because it expects generic prompts and workflows to become widely available—and believes lasting venture-capital advantage comes instead from data, judgment, access and founder trust. The playbook’s stated purpose is to make practical AI use more accessible while freeing investors to focus on decisions and relationships.
What SVV says it shared
In a 29 September 2026 article for The AI Journal, Barry Downes, SVV’s managing partner, describes opening up internal workflows used on AgenticInvestor for three areas: evaluating companies, preparing investment materials and managing the investment process.
The article does not identify a public code repository or an open-source license, and it provides no implementation instructions. “Give away” therefore describes SVV’s stated decision to share its playbook; the article alone does not establish that readers can download or run the workflows.
Why share workflows that help investors?
Downes’s case is that practical AI infrastructure can raise productivity across the venture ecosystem. If repeatable administrative and analytical tasks take less time, investors can devote more attention to assessing opportunities and supporting founders. Sharing the workflows is presented as a way to spread that practical capability rather than keep it as a private advantage.
Quick wins for a faster PC:
Clear out junk files and repair common Windows errorsFree Scan →Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →The strategy rests on a distinction between tools that can be copied and advantages that are harder to reproduce. Downes argues that prompts and workflows will become commoditized, while accumulated data, judgment, access and trust with founders will remain important differentiators. That is his thesis, not an independently demonstrated finding about the whole venture-capital industry.
Where AI fits in SVV’s investment process
The article describes AI as part of repeatable, multi-step work—not just a chatbot answering an isolated question. The named tasks span company discovery, diligence, communications and recordkeeping:
- Finding and screening opportunities: identifying relevant deals and screening companies.
- Preparing for diligence: summarizing diligence materials and assembling diligence packs.
- Managing the process: supporting founder follow-ups and keeping CRM records accurate and consistent.
These examples show the kind of work SVV says its approach addresses. They do not establish that each workflow is fully automated, or explain how its agents, data sources, integrations or review steps are configured.
What SVV reports—and what the evidence establishes
SVV reports that company screening is completed twice as quickly, and describes substantial time savings in preparing diligence packs and managing founder follow-ups, along with marked improvements in CRM accuracy and consistency. The article gives no baseline timings, sample size, study design or measurement method, so these should be read as SVV-reported outcomes rather than independently verified benchmarks.
Recommended Free Tools
The article also attributes figures of 34% for European venture firms using AI to summarize due-diligence materials and 26% for using AI to identify relevant deals. It does not name the original source or state the year of the underlying data. Without those details, the percentages cannot be treated as verified industry-wide adoption statistics.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What the playbook’s argument means for investors
SVV’s position is not that AI should make investment decisions in place of people. Downes writes: “I firmly believe that AI is here to support, not replace, human judgement and to clear the path to focus on the decisions that actually generate outsized returns.” The intended role for AI is to handle or streamline repeatable work while humans remain responsible for consequential judgments and founder relationships.
Rank #4
For readers evaluating a similar approach, the useful questions are practical: does a tool support a single task or a connected workflow; how are its outputs checked; does it fit existing CRM and follow-up processes; and does it leave investment judgment with the people accountable for it? SVV’s article offers examples and a rationale, but not enough implementation detail to answer those questions about AgenticInvestor itself.
Quick Recap
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
