# Muthukrishnan (Muthu) Bommiah

> Taking AI from pilot to production in regulated banks, with the controls built in.

Executive Director and Distinguished Engineer at Wells Fargo. Over two decades building enterprise AI, data and cloud platforms across financial services and global industry. I write about governed AI, the AI-native software lifecycle and the platforms that make both work.

## Featured initiatives

- [AI-Augmented Software Development Lifecycle](https://muthub.org/initiatives/ai-augmented-sdlc.md): Coding agents brought into a large bank's software lifecycle behind one governed platform: curated context, maker/checker controls and a single gateway for every model call.
- [Architecture-as-Code Control Plane](https://muthub.org/initiatives/architecture-as-code.md): An executable, policy-aware governance engine that checks designs automatically before they reach production, so architecture keeps pace with AI-speed delivery.
- [Enterprise Generative AI Architecture](https://muthub.org/initiatives/enterprise-genai-architecture.md): An enterprise-grade Generative AI reference architecture: a governed path from experiment to production, adopted as the reference model across business lines.

## Latest writing

- [Six runs, one canary: what it takes to let a model touch a knowledge graph](https://muthub.org/writing/six-runs-one-canary-governed-extraction.md) (Oct 18, 2026): Adding LLM entity extraction to my public knowledge graph took six CI runs. Five failed, and four of the failures looked like success. The fix was not a better model. It was a build that refuses to report a result it cannot prove.
- [Self-describing knowledge: why the Open Knowledge Format matters, and what enterprises must add](https://muthub.org/writing/self-describing-knowledge-open-knowledge-format.md) (Sep 15, 2026): In June, Google Cloud published the Open Knowledge Format, and July's v0.2 added provenance, verification and freshness. It is the right foundation. Regulated enterprises still need to add ownership, classification and a policy for how much trust an agent needs before it acts.
- [Passive capture: knowledge that writes itself, with humans who approve it](https://muthub.org/writing/passive-capture.md) (Aug 18, 2026): Documentation fails because it is a second job. The knowledge we need is already produced as a by-product of work: commits, tickets, incidents, reviews and decisions. Capture it passively, distill it, and keep a human approval gate before anything becomes trusted.
- [The AI-native SDLC: when typing code stops being the bottleneck](https://muthub.org/writing/the-ai-native-sdlc.md) (Jul 28, 2026): AI has made writing code cheap. Verification, trusted context and human judgment are now the scarce resources, and teams that redesign their lifecycle around them will pull away from teams that only add assistants.
- [Not another data lake: context needs curation, not collection](https://muthub.org/writing/not-another-data-lake.md) (Jul 21, 2026): The tempting answer to fragmented context is to pour everything into one place. We tried that with data, and many lakes became swamps. A context layer has to be a curated overlay: retrieval-first, owned, and pointing back to the systems that hold the truth.

## Profiles

- [LinkedIn](https://www.linkedin.com/in/mbommiah/)
- [GitHub](https://github.com/muthub-ai)
- [Medium](https://medium.com/@muthukrishnanb)

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Muthukrishnan (Muthu) Bommiah · https://muthub.org · Views are my own and do not represent my employer.