Platform engineering - Composio: Agent connectivity is the new infrastructure challenge
This is a guest post for the Computer Weekly Developer Network written by Soham Ganatra, founder of Composio – the company provides infrastructure for connecting AI agents to external tools, APIs and services with enterprise-grade security and observability.
Ganatra has experience in product management and engineering across multiple startups and enterprises.
He founded Composio in June 2023 and works with organisations to optimise AI agents’ interactions with software applications and writes as follows…
Agents hit a wall
LLM agents are moving from proofs-of-concept into production systems, but we’re hitting an infrastructure wall that most teams aren’t prepared for.
Your sales agent needs read access to Salesforce and write access to Slack.
Your support agent requires connections to Zendesk, your knowledge base and billing systems.
The bottleneck isn’t the capability of the AI model, a problem that can’t be solved by simply waiting for a smarter one. The true challenge is the development, deployment and management of secure, reliable and observable agent toolkits.
Cascading error effect
Remember, errors in agentic systems have cascading effects.
For a simple 5-step task where each action has an 80% chance of success, there’s only a ~32% chance the agent gets it right on the first try. This inherent fragility means that tool connectivity, reliability and security are fundamental, cross-cutting concerns for infrastructure.
Why old rules don’t apply
We’ve spent years optimising deployment patterns for stateless microservices. AI agents are fundamentally different – they make autonomous decisions about which APIs to call and their usage patterns are difficult to predict.
The connectivity approaches that work for traditional applications break down when agents make real-time decisions about external service interactions.
This new paradigm creates familiar platform engineering problems, but at a frightening new scale. Consider what happens when your organisation has 50 agents across 10 teams, each needing access to different combinations of 20+ SaaS tools and internal services.
This leads to:
- Credential sprawl: Each team manages their own API keys, OAuth flows and service accounts.
- Access control chaos: There’s no unified way to audit which agents can access what data.
- Rotation nightmares: When a key leaks or expires, teams scramble to update hardcoded credentials across tens of production agents.
- Compliance gaps: Security teams can’t track or control agent permissions across the organisation.
This is a landscape of security incidents waiting to happen, observability black holes and compliance nightmares.
A paved road for agents
What’s needed is a “paved road” for agent connectivity: infrastructure that handles tool authentication, rate-limiting and monitoring consistently across all agent tools. This lets developers focus on agent logic rather than becoming experts in secure tool integration.
In practice, this “paved road” acts as a service mesh designed for agent workloads – infrastructure that mediates between AI agents and external services. A proper platform approach addresses these challenges systematically across four key pillars:
Standardised tool development
Provide developers with tooling templates that enforce security and reliability patterns, machine-readable schemas so agents can understand tool semantics, input/output sanitization for security and sandboxed environments to test agent-tool interactions safely.
Centralised authentication & authorisation
Establish a single source of truth for all service credentials. This system should handle automated credential rotation with zero downtime and provide fine-grained permissions, with a complete audit log for all tool usage.
Unified observability
Implement end-to-end tracing from the initial prompt to the final API response. This allows for clear cost attribution by agent and team, anomaly detection for unusual agent behaviour and performance metrics that matter for AI workloads (token usage, reasoning time, success rates).
Self-Service developer experience
Create an internal marketplace where teams can discover and reuse proven tool integrations. Support this with declarative configuration for agent permissions, clear documentation and examples for common patterns.
As agent adoption scales, platform teams must prepare for challenges that extend beyond basic connectivity. Fine-grained data governance becomes critical as agents access increasingly sensitive information. Furthermore, we will need new monitoring approaches that provide visibility into the reasoning chains that lead to API calls, helping us understand why agents make specific choices.
The platform engineering opportunity
This is the next frontier for platform engineering. Just as we tamed the complexity of microservices, we must now bring the same discipline to agent infrastructure. The teams that succeed will build platforms that enable their developers to focus on agent logic, rather than wrestling with OAuth flows.
By centralising control, they will ensure security and compliance without slowing down innovation. Ultimately, this creates a decisive competitive advantage, enabling them to ship reliable, scalable AI automation while others struggle to move beyond fragile proofs of concept.
At Composio, we’ve done the hard work of building and securing tool infrastructure for you.
We provide a library of production-ready agent toolkits where the complex authentication, fine-grained permissioning and deep monitoring are already handled. This means your platform team can stop firefighting and start providing developers with the reliable “paved road” they need for agent development, right now.