Field reports from the TechKis team.
Engineering notes, architecture deep-dives and honest takes on what we’re learning while shipping AI-first software.
Top highlights
- 9 min read·PerformanceCore Web VitalsSEO
A Lighthouse 100 doesn't mean your site is fast
Lighthouse is a lab simulation on a throttled mid-range phone. Google ranks on field CrUX p75 for LCP, INP and CLS. Here's why the two disagree, and what to measure instead.
Read post - 9 min read·AI EngineeringSEOContent
Getting cited by AI search — how to be the answer, not the tenth blue link
ChatGPT, Perplexity and Google AI Overviews cite sources instead of listing links. Here's how answer engines pick what to quote, and how to be the citation.
Read post - 11 min read·ArchitectureScalingBackend
Scaling from 10 users to 10 million — the decisions that matter at each stage
Scaling isn't one problem. It's a sequence of different problems that appear at different stages. Here's what actually matters at 10 users, 10,000 users, 100,000 users, and 10 million — and the mistakes that come from solving tomorrow's problem today.
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- 10 min read·AI EngineeringRAGRetrieval
RAG is not dead — you're just building it wrong
"Just use a bigger context window" doesn't kill RAG. Bad chunking, no reranking, and retrieval you never evaluate kill RAG. Here's what a retrieval pipeline that actually works looks like.
Read post - 9 min read·AI EngineeringMemoryArchitecture
AI memory explained — short-term vs long-term, and why the difference matters
"Memory" in AI apps means two very different mechanisms with different costs and failure modes. Here's what short-term (context) and long-term (retrieval/state) memory actually are, and how to design both.
Read post - 9 min read·AI EngineeringPrompt EngineeringTesting
Prompt engineering is becoming a software engineering problem
Clever wording was phase one. Production prompts now need versioning, tests, evals, regression tracking and CI — the same discipline as any other code. Here's what that looks like in practice.
Read post - 10 min read·AI EngineeringArchitectureBackend
How AI changes backend architecture — the parts that are genuinely different
Adding an LLM to your backend breaks assumptions that held for a decade: latency, determinism, cost per request, statefulness. Here's what actually changes and how to design for it.
Read post - 9 min read·AI EngineeringDeveloper ExperienceEngineering Practice
What AI coding agents actually change about shipping client software
AI coding agents make generation cheap and review expensive. What actually gets faster on client work, what doesn't, and verification discipline that keeps it safe.
Read post - 10 min read·AI EngineeringArchitectureEnterprise
The AI gateway pattern for enterprise applications
Letting every service call model providers directly is how enterprises lose control of cost, security and compliance. An AI gateway is the single seam where routing, auth, budgets, logging and guardrails live. Here's how to build one.
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