Agent-first architecture
Can an AI agent work with your systems?
An agent can only act within the access your systems provide. We assess whether your architecture enables the next step – and where it sets limits.
The short answer
At AI SHIFT, agent first means considering in every new software decision whether AI agents can read, write and act within business processes through suitable interfaces. We assess data access, permissions, process logic and operations together. The AI & Change Audit examines the existing stack and identifies the foundations still needed for collaboration with agents.
Your next software decision has lasting effects.
A new CRM, ERP or specialist system must work today and support an AI-enabled organisation tomorrow. When access, ownership and interfaces are considered only later, every new connection becomes a special project. Agent first makes these questions selection criteria from the outset.
- Can agents reliably read relevant data and write results back?
- Which actions can they take themselves, and which need approval?
- Does this collaboration fit our existing processes and operations?
Assessment criteria
Four checks before the first autonomous action.
Access & interfaces
Which data and functions are available through documented interfaces? We examine read and write capabilities, integration limits and dependencies on manual handovers.
Identity & permissions
Which identity does an agent use, and which actions are permitted? Access should fit the task and be revocable when necessary.
Processes & approvals
What triggers an action, who reviews its outcome and when does a person decide? These rules belong in the process before an agent acts within it.
Operations & traceability
How are actions, failures and changes traced? Owners need a clear approach when a connection fails or a result needs correcting.
Deliverables
A basis for selection and integration.
- An assessment of agentic interoperability in the existing software stack
- Requirements for data access, interfaces and permissions
- A target model for collaboration between people, agents and systems
- Prioritised architecture measures as part of the AI roadmap
Approach
From the existing stack to a viable target model.
Choose a process
We start with a specific task and its value. The process determines which systems and access are relevant.
Assess system boundaries
During the audit, we review existing interfaces and dependencies with your IT team and business owners.
Design ownership
We clarify tasks, approvals and operational responsibilities and translate them into architecture requirements.
Implement step by step
The roadmap prioritises necessary foundations and useful applications. Your partners or our expert network handle technical implementation.
Common questions
What does agent first mean when selecting software?
Alongside today’s user requirements, assess whether agents will be able to read the relevant data and execute functions. This includes suitable interfaces, controllable permissions and clear operating conditions. An AI feature in the product does not answer these questions on its own.
Do we need to replace our legacy systems?
That is not a prerequisite. We first assess existing interfaces and realistic integration options. Whether to extend, adapt or replace a system depends on the use case, technical limits and economics.
Is connecting a chatbot to our documents enough?
Read access can be sufficient for search and question answering. If an agent is to process transactions or change data, write access, approvals, error handling and ownership also need to be defined.
Who is responsible for implementation?
AI SHIFT provides architecture, audits and oversight. Your existing IT partners or our expert network can implement technical connections and applications. Business decisions and operational ownership are agreed with your company.
Which system boundary is holding AI back?
Bring a planned software decision or a specific process. In an introduction, we discuss which architecture questions need to be answered next.