Karin Vedia

CTO of Composio, specializing in AI agent infrastructure and automation.

Claims

As speaker

Mentioned in

Key positions and views

Frontier AI models are becoming interchangeable commodities when provided with well-defined, abstracted 'skills', reducing the risk of vendor lock-in.

Automated, agentic pipelines are superior for building and maintaining software integrations, and are economically viable even when their token costs exceed the payroll of the human teams they augment.

The future of software interaction is agentic, a shift that will fundamentally disrupt the user interface layer of incumbent SaaS providers.

Real-time, self-improving toolsets are critical for reliable agent performance, addressing real-world problems like incorrect API documentation and inefficient execution paths.

A platform-level abstraction layer is essential for enterprises to manage multi-agent systems, ensure reliability when switching between AI models, and optimize operational costs.

Podcast consensus on Vedia

Points of consensus

▶Vedia consistently argues that intense automation is economically viable, citing both the high token costs ($100k/month) and the fact that these costs exceed the payroll of the team they replace, demonstrating a core strategic belief in AI-driven development.Apr 2026

▶The theme of model interchangeability is supported by multiple claims, stating that frontier models are proficient enough to be swapped and that skills transfer between Anthropic and OpenAI models with high fidelity, which underpins Composio's value proposition of avoiding vendor lock-in.Apr 2026

▶Vedia emphasizes the concept of self-improving systems through several mechanisms, including real-time tool regeneration when an agent fails and the conversion of inefficient agent execution traces into optimized, reusable 'skills'.Apr 2026

▶The strategic importance of Composio's agentic pipeline is consistently highlighted, as it is used to build all internal tool integrations and is leveraged by major tech companies like AWS, Zoom, and Airtable for their core agent products.Apr 2026

Points of debate

▶Vedia champions model interchangeability but also notes specific performance differences, such as Anthropic models being better at polling tasks than GPT models, suggesting that while models are largely swappable, nuanced differences still exist that require strategic selection.Apr 2026

▶Vedia highlights the extreme token cost of Composio's agentic pipeline while simultaneously positioning the platform as a way to make agent tasks more 'token-efficient' by creating skills, indicating a constant tension between the high cost of development automation and the efficiency gains it produces.Apr 2026

▶Vedia claims users can get '99% reliability with the switch' between models, but also states Composio is developing 'meta skills' to translate between them, implying that perfect, cost-free interoperability is not yet a reality and requires additional engineering effort.Apr 2026

▶Vedia describes a small, three-person team managing the agentic pipeline, yet this pipeline incurs costs greater than their payroll and serves major enterprise clients like AWS, raising questions about the scalability and management overhead of such a system.Apr 2026

Key themes

▶The Economics of Agentic AutomationApr 2026

Vedia details Composio's heavy investment in an automated, agent-driven pipeline for building software integrations. This pipeline's token costs, amounting to $100,000 in a recent month, now exceed the payroll for the human team managing it, signaling a major shift in operational expenditure from human capital to AI computation.

The high token cost represents a new form of COGS (Cost of Goods Sold) for AI-native companies, suggesting that success will depend on managing token efficiency and leveraging automation to achieve a scale unattainable by human teams alone.

▶AI Model Interoperability and AbstractionApr 2026

Vedia argues that as frontier models become more proficient at following instructions, they become largely interchangeable. Composio is built on this premise, offering a platform that allows users to switch between providers like Anthropic and OpenAI with 99% reliability by abstracting away model-specific 'skills'.

This positions Composio as a key middleware provider in the AI stack, betting that customers will prioritize flexibility and avoiding vendor lock-in over the marginal performance differences between top models.

▶Self-Improving Agentic SystemsApr 2026

Vedia describes Composio's platform as a dynamic, self-healing system. It can detect when a tool fails for an agent, automatically invoke its internal pipeline to generate a fix in real-time, and optimize inefficient agent workflows into reusable 'skills'.

This moves beyond static tool usage to a meta-level of AI-driven software development and maintenance, suggesting a future where AI systems not only perform tasks but also continuously improve their own capabilities with minimal human intervention.

▶The Agentic Interface as a SaaS DisruptorApr 2026

Vedia predicts that the primary user interface for many SaaS applications will be replaced by agentic interfaces. This shift creates a significant opportunity for startups to build new, more intuitive front-ends that compete directly with established SaaS companies.

Investors should watch for startups focused on building these new agentic UIs, as they could capture significant market share by offering a superior user experience, even if they rely on the incumbent's backend APIs.

Source episodes

Sentiment over time

Not enough data for timeline

Changes over time

Foundational Strategy

Vedia describes the initial decision to build all of Composio's tool integrations using an internal, automated agent pipeline, establishing the company's core operational model.

System Development

The team develops a sophisticated system where an 'orchestrator agent' manages fleets of specialized agents and the platform learns to optimize inefficient workflows into reusable 'skills'.

Economic Realization

The agentic pipeline becomes so central to operations that its monthly token bill ($100,000) surpasses the human payroll costs for the team managing it, marking a significant financial milestone.

Market Validation

Major tech companies, including AWS, Zoom, Glean, and Airtable, begin using Composio to build their core agent products, validating the platform's approach in the enterprise market.

Future Vision

Vedia articulates a forward-looking strategy, predicting the rise of agentic interfaces that will disrupt SaaS and positioning Composio as the key infrastructure to avoid model provider lock-in.

Suggested prompts

How does Composio's strategy of absorbing high token costs for its internal pipeline scale, and what is the break-even point compared to traditional engineering costs? &nearr;If frontier models are becoming interchangeable commodities as Vedia suggests, what will be the primary basis for competition among model providers in the long term? &nearr;What are the security and reliability implications of a system that can automatically generate and deploy new code (tools) in real-time in a production environment for clients like AWS? &nearr;Vedia predicts agentic interfaces will disrupt SaaS incumbents; what specific moats do incumbents like Salesforce or Workday have that might resist this disruption? &nearr;

Key concepts

AI Agents 1 ep Tool Integration 1 ep Model Interoperability 1 ep Token Economics 1 ep Agentic Pipelines 1 ep Self-Improving Systems 1 ep SaaS Disruption 1 ep Anthropic 1 ep OpenAI 1 ep Composio 1 ep

Notable quotes

“for the team that manages Composio's own agentic pipeline, a token bill that exceeds human payroll.”

Karin Vedia · Your Agent's Self-Improving Swiss Army Knife: Composio CTO Karan Vaidya on Building Smart Tools

“we have aws using and building their core agent product on top of us. Zoom doing the same, Glean doing the same, Airtable.”

Karin Vedia · Your Agent's Self-Improving Swiss Army Knife: Composio CTO Karan Vaidya on Building Smart Tools

“in real time that agentic pipeline is invoked and a new version of that tool gets created and the newer improved tools had added and is added into the LLM's context”

Karin Vedia · Your Agent's Self-Improving Swiss Army Knife: Composio CTO Karan Vaidya on Building Smart Tools

“we actually position Composio as a one-shot way to being not locked in essentially to a model provider... you can just have like all your auth all your skills at just a single place and make that switch and get 99% reliability with the switch.”

Karin Vedia · Your Agent's Self-Improving Swiss Army Knife: Composio CTO Karan Vaidya on Building Smart Tools

Report last updated: Apr 21, 2026

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