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AI Coding Agents · Designers and PMs vibe code functional prototypes, blurring engineering boundaries

now playing · AI Coding Agents

SaaS Business Modelsmixedscore 9/10john melissinos keryazo

AI erodes switching costs, forcing SaaS to rely on network effects and data moats

AI lowers software creation and migration costs, collapsing traditional switching cost moats; defensible SaaS must now compound network effects and proprietary datasets.

AI Agentstailwindscore 8/10john melissinos keryazo

AI agents become technical co-pilots for VC diligence and portfolio management

AI agents dramatically accelerate technical due diligence from weeks to hours and automate portfolio reporting workflows, with humans in the loop for verification.

Enterprise AI Adoptiontailwindscore 8/10john melissinos keryazo

VC firms deploy AI agents for sourcing, diligence, and LP reporting automation

Firms use LLMs for qualitative sourcing signals, iterative memo critique, and agent-orchestrated portfolio workflows, moving beyond quantitative signals to automated operations.

AI Coding Agentstailwindscore 8/10john melissinos keryazo

Designers and PMs vibe code functional prototypes, blurring engineering boundaries

AI coding tools like Cursor and Claude Code enable non-engineers to build working prototypes and contribute code, increasing velocity and cross-functional collaboration.

Venture Capitaltailwindscore 7/10john melissinos keryazo

Data-driven VC operations shift from cottage industry to automated alpha generation

Private market investors historically lacked software; platforms now centralize portfolio data, enable benchmarking, and automate reserve allocation decisions to generate alpha beyond initi…

AI Economics & Business Modelstailwindscore 7/10john melissinos keryazo

AI automates valuation workflows combining benchmarks, comps, and proprietary data

AI analysts can run DCF models and valuation frameworks using structured private market data, public comps, and benchmarks, though auditability and multiple models are needed.

AI Infrastructuretailwindscore 7/10john melissinos keryazo

Model Context Protocol enables agent-to-API interoperability, creating headless software paradigm

MCP allows LLMs to dynamically use APIs without rigid programming, enabling creative multi-tool workflows and shifting software to headless data interfaces.