Practical observations, lessons learned, and technical notes from the field, captured as they happen.
AI code review became useful only after we made it policy-aware, evidence-led, and subordinate to human ownership.
Financial services teams need AI partners who can leave governed systems behind, not black-box dependency or slideware.
AI-generated identity documents require evidence-led detection, human escalation, and replayable checks inside the KYC workflow.
Multi-agent financial crime systems need role separation, shared evidence, and a deterministic orchestration layer to stay defensible.
A credit decisioning platform reached production by narrowing domains, using event contracts, and making every decision explainable.
GitOps can satisfy regulated change control when every environment change is reviewed, replayable, policy-checked, and reversible.
Agentic AI in tier-1 banking works when autonomy is constrained by domain boundaries, event records, and human escalation paths.
A Gemini 2.5 Pro upgrade caused a regression in our evidence extraction pipeline. Context adherence dropped. Structured outputs degraded. The benchmarks said it was better. Our production data said otherwise.
Engineering agents helped on production work only after we narrowed scope, encoded boundaries, and measured integration quality.
Discover how a major UK bank's screening platform leveraged AI governance in financial services to reduce commercial customer onboarding from 10 days to under 12 hours, with vendor-agnostic architecture and zero unplanned incidents.
Production prompts need versioning, tests, ownership, and rollback because they change system behaviour as surely as code.
Re-engineering CI/CD for a regulated UK bank's 25+ microservice platform: parallel deploys, immutable artefacts, Helm, GitOps, fix-forward branching.
How we built an internal developer platform that shipped 20 microservices to a UK neobank in 4 months: 12-15 deploys/day, 47-minute lead time, zero incidents.
Master building governed AI delivery pipelines with AI engineering methodology. Bugni Labs' proven approach delivers 4-month concept-to-production for financial services, with zero incidents and 3-5x velocity.
How we built a regulated UK retail bank's GCP platform with LEGO-style Terraform: independent modules, per-module CI, InSpec policy gates, three-tier pipelines.
An exploratory field note: prototyping LLM-powered fraud-relevant extraction from call transcripts, comparing local Mistral and Qwen against Gemini.