Contributed Content
Developer’s Checklist: How to Build an FHE Application
David Archer | | BFV, BGV, bootstrapping, Chebyshev approximation, ciphertext packing, CKKS, confidential computing, encrypted cloud computing, encrypted computation, encrypted machine learning, federated learning, FHE, FHE application development, FHE development checklist, FHE parameters, FHE performance, FHE testing, fixed-point arithmetic, fully homomorphic encryption, homomorphic encryption, multiplicative depth, Niobium FHE, noise budget, OpenFHE, polynomial approximation, privacy-preserving AI, privacy-preserving computing, secure computation, SIMD encryptionA practical guide to building fully homomorphic encryption applications, covering architecture, noise budgets, polynomial approximations, parameter choices, SIMD packing, testing and performance optimization ...
The Agent Proposes, the Pipeline Disposes: Controls for AI-Authored Change
Veera Ravindra Divi | | agent permissions, agentic coding, AI change control, AI code review, AI coding agents, AI Governance, AI pull requests, AI software development, AI-authored code, AI-generated code security, autonomous coding agents, bounded-write agents, change-budget gates, CI/CD security, human-in-the-loop, in-toto, independent evals, least-privilege, policy as code, protected paths, provenance attestation, provenance verification, Secure DevOps, signed attestations, Sigstore, SLSA, Software Supply Chain Security, staged autonomyWhen agents write code and open pull requests faster than humans can read them, ‘the diff looked fine’ stops being a control. The durable controls live outside the agent’s reasoning loop ...
What You Cannot See Will Break Your LLM App: A Practitioner Guide to Production Observability
Gourav Singla | | AI monitoring, AI observability, AI quality monitoring, automated AI evaluation, Distributed Tracing, finish reason, hallucination monitoring, LLM cost observability, LLM latency, LLM monitoring, LLM observability, LLM tracing, model-graded evaluation, OpenTelemetry GenAI, OTel GenAI, production AI reliability, production LLMs, prompt failures, prompt regression, provider monitoring, quality drift, token budget alerting, token cost monitoringTraditional application observability was built around a simple mental model: Your code runs, metrics come out and when something breaks, the logs tell you why. Large language models (LLMs) break that model ...
Software Deployment Strategies for Enterprise Teams: A Scenario-Based Guide to Choosing the Right Approach
Sophie Lane | | blue-green deployment, blue-green strategy, canary deployment, canary release, CI/CD, database schema changes, deployment risk management, deployment strategy, deployment verification, DevOps deployment, enterprise software deployment, expand-contract pattern, feature flag management, feature flags, production deployment, production reliability, release management, rollback strategy, rolling deployment, rolling update, software deployment strategies, software release strategyChoosing the right software deployment strategy depends on the scenario. Get a practical decision framework for enterprise teams ...
Why CI/CD Security Testing Is Going Autonomous (and Why It Should Stay Local)
mehdi boutayeb | | application security, autonomous security testing, CI/CD, devsecops, penetration testing, Software Supply ChainContinuous integration and delivery changed the tempo of software. Teams merge dozens of times a day, infrastructure is redefined on every commit, and a new build can reach production in minutes. Security ...
How Test Management Tools Give Engineering Teams the Visibility They Need to Ship With Confidence
Sancharini Panda | | API testing, Automated testing, change-aware testing, CI/CD, code coverage, coverage visibility, deployment confidence, deployment risk, DevOps Testing, engineering teams, flaky tests, Keploy, Quality Assurance, regression testing, software delivery, software testing, test case currency, test case management, test coverage, test coverage gaps, test management tools, test traceabilityTest management tools do more than track results. Learn how they give engineering teams the coverage visibility needed to ship with confidence ...
The Rise of AI-Native DevOps: How AI Is Reshaping Software Delivery in 2026
For years, DevOps had a pretty straightforward mission: help teams ship reliable software faster by getting development and operations folks working together. Tools like automation, continuous integration, continuous delivery, infrastructure as code, ...
Why Standardized Developer Environments Still Break DevOps Workflows
Samuel Ogbonna | | CI/CD, Dev Containers, Developer Environments, developer experience, docker, reproducibilityStandardized developer environments promise to eliminate one of software engineering's oldest explanations: "It works on my machine." By packaging approved runtimes, dependencies and tools into containers, virtual machines or cloud workspaces, organizations ...
Why Reliability Guardrails Are Needed in Every AI Coding Pipeline
Kolton Andrus | | ai, AI agents, chaos engineering, CI/CD, reliability, site reliability engineeringWe’re in the middle of a reliability reckoning. Thanks to AI, companies are shipping code much faster than before. But if there’s anything to learn from the surge in high-profile outages over ...
Sandbox Testing for API-Heavy Systems: What Changes When You Don’t Own the Dependency
Sandbox testing works well when your team controls both sides of the integration. You define the service, you define the mock, you know exactly what the sandbox should return. That setup holds ...
From API Integration to Agent Governance: What Backend Teams Need to Know About MCP
Many MCP projects begin with an existing API and a simple request: expose one backend capability to an LLM client. The quickest route is to wrap an endpoint as a tool and ...
AI is Coding Us Into a Corner
Charlie Gero | | AI coding tools, AI dependency, AI hallucinations, AI patching, AI-generated code, application security, code review, code vulnerabilities, developer productivity, developer trust, frontier models, future software maintenance, Human Oversight, junior developers, secure coding, software engineering skills, software security, technical debtAI-powered patching and coding is putting us on a track towards a deepening dependency on future frontier models. The modern tools we use today to fix yesterday’s coding problems are quietly creating ...
