FIELD NOTE 01 / AUTHORITY

Distributed systems architect · Co-founder, Aegis Works

I build AI systems that earn the right to act.

More than 20 years designing scalable systems across payments, banking, telecoms and messaging—now applied to AI with explicit authority, failure controls and evidence.

Portrait of Thomas Bhatia
Thomas Bhatia Distributed systems architect / Bangkok · Dubai · London
20+years in critical systems
Paymentsbanking & telecoms
Message brokersreal-time rails & messaging
AegisAI workers for critical operations
01 The operating principle

Authority before autonomy

Intelligence is useful.
Authority makes it safe to use.

When software can change a booking, move a payment or alter a record, a persuasive answer is not enough. The system must know what it is allowed to do—and prove what happened afterwards.

01

Intelligence proposes.

Models interpret language, retrieve context and suggest the next useful action.

Probabilistic
02

Authority decides.

Explicit permissions, business state and deterministic checks decide whether that action may happen.

Controlled
03

Evidence proves.

Intent, decision and outcome remain traceable so people can audit, recover and improve the system.

Recorded
02 Current work

Systems judgment, applied to AI that acts.

I work at the boundary where a model’s suggestion becomes a real-world action: the permissions, state, failure modes and evidence that make the difference between a demo and an operation.

Design the action boundary.

Define where the model can interpret, where deterministic software must decide, how authority is granted, and how failures are contained and recovered.

  • LLM / deterministic system boundaries
  • Permission and approval architecture
  • Event-driven reliability and recovery
  • Audit, observability and operational proof
Discuss the architecture

Governed AI operations

Aegis Works

AI workers that communicate, coordinate and act inside the boundaries a business sets—beginning with customer conversations and booking through Hana.

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Action trace Governed path
  1. 01Request interpretedmodel
  2. 02Facts groundedstate
  3. 03Authority checkedallow / deny
  4. 04Action executedeffect
  5. 05Outcome recordedevidence
03 Experience, with scope

Where the judgment came from

Built in systems where failure has consequences.

Payments

Real-time payment infrastructure

Work spanning systems supporting Thailand’s PromptPay and Vocalink / Mastercard payment rails.

Messaging

RabbitMQ at operational scale

Architecture and high-performance messaging systems across banking and telecommunications.

Now

Governed AI operations

Applying explicit authority, fault tolerance, observability and recovery to AI workers at Aegis Works.

04 Field notes

Notes from the action boundary.

Payments, distributed systems and the practical work of making AI controllable, observable and recoverable.

05 About Thomas

Engineering discipline for a new class of system.

I’m a distributed systems architect and co-founder of Aegis Works. My background spans more than 20 years across banking, telecoms, payments and RabbitMQ systems.

Today I focus on AI that does more than answer: systems that can communicate and take useful action without losing human authority, operational control or a trustworthy record of what happened.

“The person accountable when an AI action goes wrong should understand exactly why it was allowed.”

Have an AI system that needs to act?

Let’s find its authority boundary.

Discuss an AI system