Taking frontier models from flawless demo to dependable system: memory, orchestration, evaluation, and the governance that lets high-autonomy agents be trusted. I lead a regional AI engineering practice at Microsoft Services and build in the open as copilot-agents-dojo.
Memory, state, and orchestration: the architecture that makes an agent dependable, not just impressive in a demo.
Read more → 02The discipline that separates a demo from a system. Benchmarks, eval harnesses, traces, and the numbers that tell you it actually works.
Read more → 03Opt-in execution, verifiable guardrails, soul files, live controls. Engineering controls, not compliance theatre.
Read more → 04Hiring, coaching, and holding a uniformly high bar; executive advisory as a consequence of credibility, not the headline.
Read more →I lead the architects and engineers who turn the AI frontier into enterprise reality.
The work isn't only technical. It's translating ambition into platforms that are secure, resilient, and accountable — and building the world-class, diverse teams that can deliver them at the highest levels of customer impact.
Accelerated time-to-innovation, with AI moved safely from pilot to production.
Strengthened security postures across cloud and AI estates.
Platforms built to stay reliable under enterprise-scale load and scrutiny.
Cost optimization that holds up as platforms grow.
New business and revenue models unlocked by AI and cloud.
World-class, diverse teams capable of sustaining all of the above.
An agent that can't cite its source is just a confident stranger with opinions. Here's how I ground my fleet in truth with provenance — a governed Nexus Brain on Cosmos DB for work, and an Obsidian second brain you can build this weekend for yourself. Plus why Satya called the next discipline 'loop engineering' at Build 2026.
Read →Two teams. Same model. One ships an agent that runs your delivery practice; the other ships a chatbot that forgets your name. The gap isn't the model — it's the harness. Here's the discipline nobody named yet.
Read →The night-shift agents were drowning in their own history. Here's the compaction pass that more than halved token cost on long runs — and the one summary it silently corrupted before I added pinned invariants.
Read →What I'm building in the open — pulled live from github.com/andreaswasita.
A behavioral governance framework for GitHub Copilot agents — skills.md and instructions to make AI coding agents think like senior engineers.
View on GitHub →A skills & discipline framework for Microsoft 365 Copilot Cowork — for knowledge workers using AI as a coworker.
View on GitHub →A two-part session for UNSW students. First hour: an industry view of agentic AI, with Microsoft case examples, Responsible AI principles, and the tooling I use for proof-of-concept work. Second hour: live mentoring on student project ideas.
Mid-program feedback session. Reviewing student progress, unblocking technical decisions, and sharpening the path to the final showcase.
The capstone presentations — students share what they built, the design decisions behind it, and the lessons they took from the program.
I'm Regional CTO and Director of the Azure Cloud + AI Architecture practice at Microsoft Services, leading high-caliber architects, engineers, and cross-functional partners across APAC and beyond.
I'm an avid reader and a lifelong student of both technology and the financial industry, and I build in the open. copilot-agents-dojo and copilot-cowork-dojo are working frameworks for making AI coding agents behave with the discipline of senior engineers and collaborate as a team — where I prototype the agent patterns I bring to enterprise scale.
Always architecting the future — and deeply grateful for the teams and customers who make it possible.