GUIDES

75 articles · page 4 of 5

Insights.

Straight answers for business owners and entrepreneurs planning software — what it costs, how long it takes, who to hire, and when an off-the-shelf tool is the smarter call. Written by founder Nick McCandless and the Eltherion team.

black flat screen computer monitor

Software EconomicsMay 20, 20266 min read

Usage-based pricing: when to adopt and how to model revenue

Usage-based pricing is not a growth lever — it's a product-fit probe that doubles your operational complexity. Usage-based pricing requires instrumentation, billing plumbing, and forecasting discipline; done wrong it costs you $150k–$600k in engineering and tooling in year one and erodes churn instead of revenue.

a woman sitting at a table in front of a laptop computer

Build vs. BuyMay 19, 20266 min read

Feature store build vs buy: a practical TCO framework

Feature store build vs buy is the first architecture decision that determines whether your ML stack is a product or a prototype. The wrong call costs you months of data-engineer time, $0.5M–$2.5M over three years, and a migration that destroys model reliability.

cable network

SaaS & Platform EngineeringMay 18, 20266 min read

Data residency compliance: architecture, costs, and tradeoffs

Data residency compliance forces architectural choices that most engineering teams underprice. Data residency compliance is not a checkbox — hosting a single EU region instead of a global fallback typically raises infra and ops costs by 10–40% and adds at least 1–3 full-time engineering equivalents over three years.

gray and black laptop computer on surface

App & Web EngineeringMay 17, 20266 min read

Microfrontend architecture: split the frontend or keep a monolith

Microfrontend architecture is usually proposed as the cure for slow releases — but splitting the frontend often increases operational cost by 20–40% while delivering far less than expected velocity gains. This piece gives a clear threshold: when independent deploys justify the added latency, CI cost, and complexity.

Colleagues collaborate while examining computer designs.

Build vs. BuyMay 16, 20267 min read

Audit logging platform: build vs buy decision

Audit logging platform is one of those infrastructure decisions that looks trivial until it shows up on a regulator’s checklist or your legal team asks for a 24‑month eDiscovery export. Build when volume, unique immutability, or latency requirements exceed vendor economics; buy when you need speed, integrations, and predictable 12–36 month retention costs.

A MacBook with lines of code on its screen on a busy desk

AI Engineering PracticeMay 15, 20267 min read

Model selection at runtime: cost-aware routing for production AI

Model selection at runtime is the single production decision that separates cheap prototypes from sustainable AI features. When you route requests across models by cost, latency, and confidence, you can cut inference spend by 40–70% while preserving quality SLOs — but only if you build per-request scoring, caching, and fallback logic.

black and silver laptop computer

SaaS & Platform EngineeringMay 14, 20266 min read

Billing observability: architecture for accurate metered SaaS billing

Billing observability matters more than raw billing features. Billing observability is the set of telemetry, reconciliation, and ledger guarantees you need to keep metered revenue correct, reduce customer disputes, and avoid multi-month GAAP restatements — starting with a ledger you can reconcile in under 24 hours.

yellow built text illustration

Build vs. BuyMay 13, 20266 min read

Feature flag platform: build vs buy decision framework

Feature flag platform decisions are habitually framed as 'simple toggles' — they're not. A wrong choice costs you months of outages, $200k+ in engineering, and audit headaches when compliance or scale arrives.

a laptop computer sitting on top of a white table

Build vs. BuyMay 12, 20267 min read

Search as a Service vs Build: a 3‑year TCO framework

Search as a Service is the fastest route to production search, but it becomes expensive and inflexible above certain scale and feature needs. This piece gives a 3‑year TCO framework — with concrete numbers for Algolia, Elastic/OpenSearch, Pinecone-style vector providers, and the engineering effort to run your own.

AI Engineering PracticeMay 11, 20266 min read

Agent orchestration: scalable patterns for production agents

Agent orchestration determines whether tool-using agents are a product liability or a scalable differentiator. Agent orchestration is the coordination layer that runs planners, executes tools, enforces safety, and controls cost — and the right pattern reduces latency and cost by orders of magnitude compared with naïve per-request orchestration.

a computer screen with a bar chart on it

Software EconomicsMay 10, 20266 min read

Outsourced engineering costs: compare T&M, fixed-bid, retainers

Outsourced engineering costs are rarely lower than hiring until you factor time-to-market and hiring risk. Vendors sell velocity and risk transfer; you pay for predictability. Compare offers using three-year TCO, ramp months, and explicit switching costs before you sign a retainer.

person writing on white board

Build vs. BuyMay 9, 20266 min read

Identity platform build vs buy: when to roll your own

Identity platform build vs buy is the question every CTO hits when auth becomes product-facing. The right choice depends on three numbers: expected MAUs, annual SaaS spend you’ll tolerate, and the 3‑year cost of owning security and compliance.

a laptop computer sitting on top of a wooden desk

AI Engineering PracticeMay 8, 20266 min read

Production RAG architecture: vector store, evals, cost

Production RAG architecture is primarily an engineering trade-off about data topology and cost, not just model choice. Published May 8, 2026 — this piece shows why vector stores, chunking, and retrieval evals drive 60–80% of your RAG TCO and production risk.

Person using a smartphone with a green screen.

App & Web EngineeringMay 7, 20268 min read

Cross-platform mobile strategy: React Native vs Flutter vs native

Cross-platform mobile strategy is not a Microsoft-oracle choice between ‘write once’ and ‘rewrite later’ — it’s a product strategy decision that changes your roadmap velocity, 3-year TCO, and hiring profile. Choose the wrong axis and you pay 2x in engineering headcount and 9–18 months of launch delay.

man in gray sweater standing beside wall

SaaS & Platform EngineeringMay 6, 20267 min read

Multi-tenant architecture: schema-per-tenant vs row-level isolation

Multi-tenant architecture decisions — schema-per-tenant or row-level isolation — determine whether your platform scales or becomes a cost sink. Pick the wrong isolation model and you’ll pay an extra $300k–$1.2M over three years in engineering and infra bills, or lose customers to noisy neighbors.

graphs of performance analytics on a laptop screen

Software EconomicsMay 5, 20266 min read

Custom AI feature cost: how to budget and decide

Custom AI feature cost is not a single line item — it's a multi-year liability that lives on your balance sheet as people, cloud spend, and product complexity. Mis-budgeting a single feature can turn a $150k experiment into a $1.2M maintenance burden inside 18 months.

a computer screen with the words nothing great is made alone

Brand & Design Systems for SoftwareMay 4, 20267 min read

Design system adoption: engineering cost, rollout, and ROI

Design system adoption changes from a productivity play into a liability when teams treat components like a checkbox. Design system adoption demands a product-minded rollout, measurable adoption metrics, and a clear 3-year cost/return math.

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Build vs. BuyMay 3, 20268 min read

SaaS billing platform: build vs buy for B2B products

SaaS billing platform is the purchase decision that founders mistake for a solved problem — but the wrong choice blows up margin, ops, and product differentiation. You should treat billing as an architectural decision with explicit thresholds, not a checkbox to outsource.

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