Grace Ashiru
The loudest conversations in tech right now are about intelligence. Bigger models. Faster inference. Products that can reason, write, search, and act. But beneath the excitement sits a quieter crisis, one that doesn’t show up in demos or keynote slides.
As software systems become more autonomous, the real bottleneck is no longer capability. It is trust.
This is the problem Ijeoma Eti has been working on, often invisibly, across backend systems, open-source infrastructure, and AI-enabled platforms. While much of the industry races to ship smarter products, Eti is focused on a more uncomfortable question: what happens when those systems fail, misbehave, or are exploited at scale?
The Hidden Cost of Intelligence Without Trust
AI systems don’t exist in isolation. They sit on top of complex backend infrastructure, databases, APIs, orchestration layers, identity systems, and cloud networks. As soon as AI is introduced, that infrastructure inherits new risks.
Models hallucinate. Inputs are unpredictable. Outputs can trigger real actions. Attack surfaces expand. Compliance requirements tighten. Yet many teams still treat reliability, security, and compliance as implementation details to “figure out later.”
The result is software that appears intelligent but behaves unpredictably under pressure. Systems that work in controlled environments but collapse when faced with real-world traffic, adversarial inputs, or regulatory scrutiny. Eti argues that this isn’t a tooling problem. It’s a mindset problem.
Infrastructure Trust as a Product Feature
Coming from a background in industrial chemistry, Ijeoma approaches systems the way scientists approach experiments: with hypotheses, controls, and an expectation that things will go wrong.
In backend engineering, this translates into designing for failure from day one. Clear service contracts. Strong access controls. Observability that explains why something happened, not just that it happened. Fallbacks that degrade gracefully instead of catastrophically.
Trust, in this framing, is not an abstract value. It is something engineered into the system. If users cannot predict how software behaves, or operators cannot explain its decisions, then intelligence becomes a liability rather than an advantage.
Open Source and the Reality of Shared Infrastructure
Ijeoma’s work as a maintainer on the CNCF project Meshery exposes her to a global truth about modern software: most of the internet runs on shared infrastructure built by people who may never meet.
In open source, trust failures propagate quickly. A misconfiguration, ambiguous abstraction, or undocumented edge case doesn’t just affect one company; it affects entire ecosystems. This is why Ijeoma’s contributions focus on making infrastructure legible: tools that help engineers visualise, reason about, and audit complex systems before they break.
When infrastructure is invisible, trust erodes. When it is understandable, teams can secure it, govern it, and comply with external requirements.
AI, Compliance, and the Expanding Attack Surface
As AI becomes embedded into products, compliance is no longer just a legal concern; it is an architectural one. Data provenance, access boundaries, traceability, and abuse prevention now have to be enforced at the system level.
Ijeoma sees backend engineers evolving into AI system designers, responsible not just for performance but for deciding when AI should be invoked, how its outputs are validated, what data it can access, and how decisions are logged and audited.
Without this discipline, organisations risk deploying systems they cannot explain to regulators, customers, or even themselves. Intelligence without accountability does not scale.
Security and Reliability in the Age of Autonomous Systems
One of Ijeoma’s core beliefs is that many modern systems are built for ideal conditions rather than reality. Clean inputs. Predictable traffic. Honest users. AI breaks those assumptions.
Latency spikes, model drift, prompt injection, and cost volatility all introduce new failure modes. Backend systems must absorb this instability while maintaining guarantees around uptime, data protection, and user safety.
This is why Ijeoma insists that reliability and security cannot be bolted on. They must be treated as core product features, designed, tested, and measured with the same seriousness as user-facing functionality.
Building for the World That Actually Exists
Looking ahead, Ijeoma is paying close attention to the rise of cross-functional AI agents, systems that move across tools, teams, and workflows with minimal human intervention. These systems promise speed and efficiency, but they also concentrate risk.
In that future, the most valuable engineers will not be those who chase novelty fastest, but those who build systems that hold under pressure.
While the industry celebrates intelligence, Ijeoma Eti is working on something less glamorous and more enduring: infrastructure people can trust. In the long run, that may be the difference between AI that merely impresses, and AI that lasts.
