📰 Dev.to · Bala Paranj

Jen Easterly correctly identified that cybersecurity is an aftermarket for software quality failures. Then she celebrated an AI that makes the aftermarket faste

A completeness law — independently confirmed by engineering, cybernetics, and economics — names the five elements any viable system must contain. The current AI

We are uncovering better ways of building software with AI agents. Through this work we have come to value certain things over others.

Cloud has engines (Lambda, Kubernetes), transmission (CI/CD, IaC), and tools (APIs, admission controllers). What it's missing is the control unit — the part tha

Vivek Trivedy's 'Anatomy of an Agent Harness' is the clearest statement of how the industry thinks about AI agents. A NIST mathematical proof just demonstrated

CSPM, CNAPP, SIEM, SOAR, IaC scanners, ML detection — we applied TRIZ Function-Failure Analysis to each. The missing function is the same in all six. It's also

Resource tagging is the engineering bridge between human intent and mathematical verification. A tag turns subjective purpose into a state variable that automat

Some cloud security problems are structural, not behavioral. For those, a few lines of declarative constraints outperform thousands of lines of scanner code.

Nuclear power, medicine, law, aerospace, military operations, and aviation each faced the same contradiction software is struggling with now. They solved it dec

Adding agents without specifications is like adding nodes without protocols. Distributed systems learned this 40 years ago. The coordination mechanisms are the

Guardrails, LLM-as-judge, AI code review — they all share one structural problem. The verifier has the same failure modes as the thing it's verifying. Here's wh

APIs got a standard format and an ecosystem followed. Properties, contracts, and rationale have no standard. AI generates code at scale without consuming the sp

David Parnas proved that human cognitive capacity is the hard bottleneck of software engineering. 53 years later, AI coding agents are proving him right — and h

Google, Spotify, Netflix built internal platforms that make misconfiguration impossible. It cost them thousands of engineers and years of investment. The next e

Nuclear submarines, microprocessor design, aviation, medicine, law, and Google's monorepo each faced the same crisis: systems too complex for humans to understa

AI-generated code that compiles, passes tests, and reads well can still be wrong in ways no human will catch by reading it. Plausible is not correct. Here's wha

Eight assumptions every team building with AI is making right now. Each one sounds true. Each one leads to an architectural failure. Each one has already been s

Generative AI creates cognitive debt through six structural contradictions. Braking isn't the answer. TRIZ shows how to eliminate the conflicts entirely.

Fowler's 9 GenAI patterns wrap a non-deterministic engine with non-deterministic layers. There's another move: change the architecture so the failure mode can't

ThoughtWorks put 'MCP by default' in their Caution ring. We agree — and here's the architectural pattern that makes the decision easy.

The CrowdStrike July 2024 outage — the largest IT incident in history — wasn't caused by a bug. It was caused by a MISSING INVARIANT. The bug (out-of-bounds mem

The Technology Radar's case against LangGraph-as-default is that rigid graphs with massive shared state are hard to reason about, test, and debug — and that sim

Wiring a new infrastructure source into a security policy engine used to mean writing a custom extractor. We replaced it with a YAML contract per asset type and

Every boundary in Stave's pipeline has a machine-verifiable contract. We built them for solo...