The Agentic Artificial Intelligence Venture Co-Founder (AIVC): An AI Operating System for Lean Experimentation, Strategic Decisioning, and Responsible Scaling in Technology Startups

Amina Sambo-Magaji, Muyideen Dele Adewale
Proceedings of IndabaX Nigeria 2026: Building Scalable AI That Works: From Research to Deployment in Resource-Constrained Environments, PMLR 319:306-319, 2026.

Abstract

This paper introduces the Agentic Artificial Intelligence Venture Co-Founder (AIVC), a conceptual multi-agent system that senses markets and regulatory signals, designs and executes lean experiments, maintains causal traction models, allocates resources, and enforces governance-by-design. The framework defines five capability bundles: sensing, experimentation, decisioning, governance, and venture memory. A conceptual architecture specifies model classes, APIs, and latency budgets across three deployment tiers. AIVC is distinguished from the build-measure-predict-learn model and is supported by four testable propositions, advancing entrepreneurship and ML systems research by shifting focus to the quality of the founder–AI decision loop under Knightian uncertainty.

Cite this Paper

BibTeX
@InProceedings{pmlr-v319-sambo-magaji26a, title = {The Agentic Artificial Intelligence Venture Co-Founder ({AIVC}): An {AI} Operating System for Lean Experimentation, Strategic Decisioning, and Responsible Scaling in Technology Startups}, author = {Sambo-Magaji, Amina and Adewale, Muyideen Dele}, booktitle = {Proceedings of IndabaX Nigeria 2026: Building Scalable AI That Works: From Research to Deployment in Resource-Constrained Environments}, pages = {306--319}, year = {2026}, editor = {Folorunso, Sakinat and Ogundokun, Roseline and Oladipo, Francisca}, volume = {319}, series = {Proceedings of Machine Learning Research}, month = {11--14 May}, publisher = {PMLR}, pdf = {https://raw.githubusercontent.com/mlresearch/v319/main/assets/sambo-magaji26a/sambo-magaji26a.pdf}, url = {https://proceedings.mlr.press/v319/sambo-magaji26a.html}, abstract = {This paper introduces the Agentic Artificial Intelligence Venture Co-Founder (AIVC), a conceptual multi-agent system that senses markets and regulatory signals, designs and executes lean experiments, maintains causal traction models, allocates resources, and enforces governance-by-design. The framework defines five capability bundles: sensing, experimentation, decisioning, governance, and venture memory. A conceptual architecture specifies model classes, APIs, and latency budgets across three deployment tiers. AIVC is distinguished from the build-measure-predict-learn model and is supported by four testable propositions, advancing entrepreneurship and ML systems research by shifting focus to the quality of the founder–AI decision loop under Knightian uncertainty.} }
Endnote
%0 Conference Paper %T The Agentic Artificial Intelligence Venture Co-Founder (AIVC): An AI Operating System for Lean Experimentation, Strategic Decisioning, and Responsible Scaling in Technology Startups %A Amina Sambo-Magaji %A Muyideen Dele Adewale %B Proceedings of IndabaX Nigeria 2026: Building Scalable AI That Works: From Research to Deployment in Resource-Constrained Environments %C Proceedings of Machine Learning Research %D 2026 %E Sakinat Folorunso %E Roseline Ogundokun %E Francisca Oladipo %F pmlr-v319-sambo-magaji26a %I PMLR %P 306--319 %U https://proceedings.mlr.press/v319/sambo-magaji26a.html %V 319 %X This paper introduces the Agentic Artificial Intelligence Venture Co-Founder (AIVC), a conceptual multi-agent system that senses markets and regulatory signals, designs and executes lean experiments, maintains causal traction models, allocates resources, and enforces governance-by-design. The framework defines five capability bundles: sensing, experimentation, decisioning, governance, and venture memory. A conceptual architecture specifies model classes, APIs, and latency budgets across three deployment tiers. AIVC is distinguished from the build-measure-predict-learn model and is supported by four testable propositions, advancing entrepreneurship and ML systems research by shifting focus to the quality of the founder–AI decision loop under Knightian uncertainty.
APA
Sambo-Magaji, A. & Adewale, M.D.. (2026). The Agentic Artificial Intelligence Venture Co-Founder (AIVC): An AI Operating System for Lean Experimentation, Strategic Decisioning, and Responsible Scaling in Technology Startups. Proceedings of IndabaX Nigeria 2026: Building Scalable AI That Works: From Research to Deployment in Resource-Constrained Environments, in Proceedings of Machine Learning Research 319:306-319 Available from https://proceedings.mlr.press/v319/sambo-magaji26a.html.

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