Engineering

Technical writing by named senior engineers.

Real architectures we ship. Real trade-offs we evaluate. Real code that runs in production. By engineers under their own bylines, not vendor evangelism.

Posts: 7 published
Authors: Senior engineers
Cadence: Bi-weekly

Engineering directory

Sixteen technical tracks.

AI engineering, platform, distributed systems, databases, performance, security: every domain a senior engineering audience reads on, written by engineers under their own bylines.

Tracks: 16
Authors: Senior engineers
Cadence: Bi-weekly

01 · CORTEX1 post
AI Engineering
Production LLM systems: RAG, agents, evals, fine-tuning, vector retrieval, and the engineering decisions that decide whether AI ships.
Browse track
02 · FORGESOON
Platform Engineering
Internal developer platforms, golden paths, paved roads, Backstage, and the developer-experience discipline that turns ten teams into one.
Browse track
03 · FOUNDATION1 post
Cloud Native & Kubernetes
Kubernetes deep dives, service mesh, eBPF, operators, multi-cluster topologies, GitOps, and the operating discipline production K8s requires.
Browse track
04 · FOUNDATIONSOON
Observability & SRE
OpenTelemetry, distributed tracing, SLOs, error budgets, incident response, on-call discipline, and chaos engineering.
Browse track
05 · FORGESOON
Database Engineering
Postgres deep dives, schema design, zero-downtime migrations, query tuning, replication topology, and vector database architecture.
Browse track
06 · FORGESOON
Distributed Systems
Consensus protocols, sharding, event-driven architecture, CQRS, sagas, CRDTs, and the consistency trade-offs distributed systems force.
Browse track
07 · SKYWAY1 post
Infrastructure as Code
Terraform, Pulumi, OpenTofu, Crossplane, policy-as-code, drift detection, and IaC at team scale without DynamoDB state lock contention.
Browse track
08 · FORGESOON
Performance Engineering
Profiling, latency budgets, memory engineering, caching strategy, AI inference performance, and the load-testing discipline that catches regressions.
Browse track
09 · CITADELSOON
Security Engineering
Software supply chain, secrets management, zero-trust architecture, threat modelling, SBOM, sigstore, and secure-by-design discipline.
Browse track
10 · CANVASSOON
Frontend Engineering
React Server Components, Next.js, edge runtimes, Web Vitals, hydration strategy, and the frontend architecture decisions that scale.
Browse track
11 · FORGESOON
Backend & API Design
REST, gRPC, GraphQL, async patterns, queue topology, idempotency, rate limiting, and API contract design that ages well.
Browse track
12 · FORGESOON
Data Engineering
Data pipelines, dbt, lakehouse architecture, Kafka, Flink, streaming vs batch, and the data-quality discipline production analytics requires.
Browse track
13 · CORTEXSOON
MLOps & ML Infrastructure
Feature stores, model serving, training infrastructure, drift monitoring, GPU scheduling, and the MLOps stack that holds up to audit.
Browse track
14 · FORGESOON
Languages & Runtimes
Rust, Go, TypeScript, Python, Bun, Deno: language deep dives, runtime internals, and performance comparisons grounded in production.
Browse track
15 · FORGESOON
Architecture & System Design
Domain-driven design, event sourcing, modular monolith vs microservices, and the architecture decision frameworks that hold up under scale.
Browse track
16 · ATLAS4 posts
Enterprise Platforms
Microsoft (D365, Power BI, Fabric), Salesforce, ServiceNow, SAP: platform implementation engineering, integration, and customisation discipline.
Browse track

16 tracks · scroll to browse

Library

All engineering posts.

01
EnterpriseServiceNowITSMITOMHRSDATLAS
ITSM vs ITOM vs HRSD: Starting on ServiceNow.
Honest comparison of ServiceNow's three foundational modules: when each wins, the buyer profile that fits, and the order most successful programs ship them in.
Michael Reyes · ATLAS
9 min
Apr 26, 2026
Read the post
02
EnterprisePower BISemantic ModelsEnterprise PlatformsATLAS
Power BI Semantic Models: The Foundation Skipped.
Why semantic-model-first discipline is the single biggest factor in Power BI estate health, and the seven patterns that turn a chaotic 100-dataset tenant into a governed analytics foundation.
Michael Reyes · ATLAS
12 min
Apr 22, 2026
Read the post
03
EnterpriseSalesforceEnterprise PlatformsCRMATLAS
Sales vs Service vs Marketing Cloud: Decision Guide.
Honest comparison of Salesforce's three flagship clouds: when each wins, where each falls down, and the patterns most enterprises get wrong on day one.
Michael Reyes · ATLAS
10 min
Apr 18, 2026
Read the post
04
EnterpriseDynamics 365Enterprise PlatformsImplementationATLAS
Dynamics 365: Realistic Timeline & Cost.
What a Microsoft Dynamics 365 implementation actually takes: phase-by-phase timeline, realistic cost ranges by company size, and the trade-offs that decide go-live success.
Michael Reyes · ATLAS
11 min
Apr 15, 2026
Read the post
05
AI EngineeringAIRAGRetrieval
Hybrid retrieval: dense + sparse + filters.
Pure-vector RAG is rarely the right answer at production scale. Here's the hybrid retrieval pattern we ship, dense embeddings + BM25 + metadata filters with reranking, and the failure modes it solves.
James Carter · CORTEX
9 min
Apr 14, 2026
Read the post
06
Cloud NativeAWSCloud ArchitectureCompliance
Multi-account AWS that survives audit.
Single-account AWS estates eventually hit a regulatory wall. Here's the multi-account topology we ship to enterprises: account purposes, transit gateway, IAM Identity Center, and policy-as-code, designed to survive SOC 2 / HIPAA / PCI audits.
Olivia Bennett · CITADEL
11 min
Mar 30, 2026
Read the post
07
IaCTerraformIaCPlatformAWS
Terraform at team scale, no DynamoDB locks.
Why we moved off DynamoDB-backed state locks for a 40-engineer Terraform monorepo, and what we replaced them with.
Emma Thompson · NEXUS
7 min
Mar 22, 2026
Read the post

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AI Engineering

Platform Engineering

Cloud Native & Kubernetes

Observability & SRE

Database Engineering

Distributed Systems

Infrastructure as Code

Performance Engineering

Security Engineering

Frontend Engineering

Backend & API Design

Data Engineering

MLOps & ML Infrastructure

Languages & Runtimes

Architecture & System Design

Enterprise Platforms

All engineering posts.

ITSM vs ITOM vs HRSD: Starting on ServiceNow.

Power BI Semantic Models: The Foundation Skipped.

Sales vs Service vs Marketing Cloud: Decision Guide.

Dynamics 365: Realistic Timeline & Cost.

Hybrid retrieval: dense + sparse + filters.

Multi-account AWS that survives audit.

Terraform at team scale, no DynamoDB locks.

Want to write under your own byline?

AI Engineering

Platform Engineering

Cloud Native & Kubernetes

Observability & SRE

Database Engineering

Distributed Systems

Infrastructure as Code

Performance Engineering

Security Engineering

Frontend Engineering

Backend & API Design

Data Engineering

MLOps & ML Infrastructure

Languages & Runtimes

Architecture & System Design

Enterprise Platforms

All engineering posts.

ITSM vs ITOM vs HRSD: Starting on ServiceNow.

Power BI Semantic Models: The Foundation Skipped.

Sales vs Service vs Marketing Cloud: Decision Guide.

Dynamics 365: Realistic Timeline & Cost.

Hybrid retrieval: dense + sparse + filters.

Multi-account AWS that survives audit.

Terraform at team scale, no DynamoDB locks.

Want to write under your own byline?