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Zylver Engineering Blog
Notes on agent architectures, production ML, cost observability, and the patterns that ended up in our product suite.
Reading an LLM bill: line items that actually matter
Most LLM bills get scanned for total cost. Seven line items carry the real signal. A 5-minute monthly review that turns the bill into a diagnostic.
Multi-tenant AI: what you can't fake when you have 50 customers
Single-tenant AI hides bad architecture. Multi-tenant AI exposes it. Six things that compound across a tenant set and cannot be deferred.
Financial services AI: four constraints that reshape the architecture
Generic AI patterns break in financial services. Four constraints (audit, residency, adversarial input, risk asymmetry) reshape architecture from day one.
Most multi-agent systems are sequential pipelines wearing a costume
Most 'multi-agent' systems are sequential pipelines with role-play prompts. Three diagnostic questions to tell the difference.
What to instrument when your AI degrades in production
Most AI systems fail silently. Latency dashboards say 200 OK while quality drifts. Here is the four-layer telemetry stack that catches it.
What Business Processes Can Be Automated with AI in 2026
A practical guide to identifying which business processes benefit most from AI automation, from document processing to customer operations, with real implementation considerations.
Why Your AI Gets More Expensive Over Time (And How to Reverse It)
AI costs often increase after deployment. Learn the engineering patterns for intelligent distillation, model routing, and cost optimization that reduce per-operation costs by 50-80%.
Beyond Demos: Building AI Systems That Actually Work
Most AI projects fail in production. Here's why the gap between demo and deployment is where real engineering begins, and what production AI actually requires.
How to Choose an AI Platform or Partner: A Practical Evaluation Guide
Evaluating AI vendors and platforms is difficult. Specific questions to ask, red flags to watch for, and criteria that separate products and firms that ship from ones that only advise.
AI Implementation Costs in 2026: What Companies Actually Spend
Realistic breakdown of AI implementation costs including infrastructure, development, API spend, and ongoing operations. What to budget and where companies overspend.
Beyond Chatbots: Multi-Agent Architecture Patterns for Production
Single-model AI hits a ceiling fast. Here are the architecture patterns we use to build multi-agent systems that coordinate hundreds of specialized agents in production.
The State of AI in Austin, Texas: Why the Capital City Is an AI Hub
Austin's AI ecosystem is growing fast. From enterprise adoption to the startup scene, here is what makes Austin a center for AI innovation and why it matters for local businesses.
How AI Is Reshaping Professional Services
A clear-eyed look at what AI does better than consultants, what it cannot replace, and how the consulting industry is transforming. Written by a team that used to sell consulting and now ships products.
The AI Observability Gap: What You Can't See Is Costing You
Most AI systems run without meaningful monitoring. Learn the four dimensions of AI observability and how to build the monitoring infrastructure that makes optimization possible.
AI for Small Business: When It Makes Sense (And When It Doesn't)
Small businesses are bombarded with AI promises. A practical framework for evaluating whether AI adoption is worth the investment for your company, and what to do if it is not.
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