Articles.
Actionable strategies for $500k+ operators building AI systems into their business.
No fluff. No hype. Every article answers a specific question and ends with something you can act on.
- AI Readiness
AI automation audit: encode your judgment in 90 days
AI automation audit for founders: run a 5 domain diagnostic in one week, then ship working agent prototypes in a 90 day program built with Claude Code.
Read articleJKJames Killick12 min read - Agentic AI
Build AI agent guardrails in 90 days with durable approvals
AI agent guardrails, explained for founders: where the four checks belong, how durable human approvals survive a restart, and how to prove yours actually hold.
Read articleJKJames Killick11 min read - Agentic AI
AI Agent Governance: A 90-Day Playbook for CISOs
AI agent governance in 90 days: name an owner for every agent, add runtime checks that stop bad actions mid-run, and build an audit trail that holds up.
Read articleJKJames Killick11 min read - AI Implementation
AI Agent Observability: Stop Hidden Token Burn in 90 Days
AI agent observability stops hidden token burn. Trace every step with OpenTelemetry, track cost, latency and success rate, then fix what the traces show.
Read articleJKJames Killick10 min read - AI Orchestration
Multi-Agent vs Single Agent: Measure Before You Build
Start with one agent. Add more only when you hit a wall you can measure, and can prove the extra cost is worth it.
Read articleJKJames Killick9 min read - AI Implementation
LLM cost optimization: three levers that cut your bill
LLM cost optimization comes down to three levers. Routing, caching and batching, in that order, with the measurement that tells you which one is working.
Read articleJKJames Killick9 min read - Agentic AI
AI agent security needs layers, not a single lock
AI agent security works in layers. Scope every tool tightly, sandbox the whole agent loop, and let deterministic checks catch what a fooled model lets through.
Read articleJKJames Killick10 min read - AI Implementation
PII in AI: what it means and how to stop it leaking
PII in AI leaks through prompts, embeddings, RAG and agent calls. How data privacy in AI actually works: detect by meaning, mask at delivery, prove lineage.
Read articleJKJames Killick11 min read - Agentic AI
AI policy development: rules that keep your agents on-brand
Develop effective AI policies to ensure your agents protect your brand, maintain quality, and prevent shadow AI. Start today!
Read articleJKJames Killick11 min read - AI Implementation
How AI systems handle edge cases in production
Learn effective strategies for handling edge cases in AI systems, ensuring reliable outputs and minimal risks in production environments.
Read articleJKJames Killick12 min read - AI Orchestration
The real benefits of multi-agent AI systems for founders
Split the work across specialist agents and you get parallel throughput, independent checks and a system that survives one part failing. Here is when that trade is worth making, and when one good agent still wins.
Read articleJKJames Killick11 min read - AI Implementation
What is AI model fine-tuning for founder-led businesses?
What is AI model fine-tuning for a founder-led business? It means prompts, agents and small task datasets that encode your decision rules, not model weights.
Read articleJKJames Killick8 min read
Showing 12 of 238 articles. Page 6 of 20
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