Signal Notes

When AI Agents Lie: Production Guardrails That Actually Work

Nick Creighton — Sat, 25 Apr 2026 21:43:33 -0400

BUILD LOG 046 why your ai agent keeps hallucinating nick walks us through the night his client's inventory went 847% over reality. twenty minutes from a $2.3 million disaster. it wasn't the model—it was the guardrails. this is production-level thinking. after running thirteen sites with live AI agents, nick learned that even gpt-4 makes stuff up roughly one time out of every five in complex workflows. nobody ships prepared for that. most teams just pray. the fix? three layers of defense that actually catch hallucinations before they hit your database, your customers, your bottom line. layers of output validation, semantic checks, and external truth-testing. unglamorous. unsexy. essential. a meditation on the gap between ai demos and systems that won't cost you six figures. listen in: Build Log on Transistor

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Context Windows vs Parameters: What Actually Makes AI Smart

Nick Creighton — Sat, 25 Apr 2026 21:43:32 -0400

In this episode of Signal Notes, host Nick takes you on a heart-pounding journey through the unpredictable world of AI deployment. Reflecting on a chaotic experiment with a new content management model, he shares the raw adrenaline of high hopes clashing with stark realities. Explore the often-overlooked importance of rigorous testing as Nick reveals why many AI projects falter and how to turn those failures into lessons learned. Join us as we unravel the intricate dance between anticipation and unpredictability in the future of AI. Dive deeper in our [companion blog post](#) and experience the rush—listen now!

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Why 70% of AI Models Fail in Production

Nick Creighton — Sat, 25 Apr 2026 21:43:31 -0400

In this episode of Build Log, host Nick dives into the realm of AI coding tools as we forecast the future: Claude Code, Cursor, and Windsurf battle it out. With a staggering 70% of AI models faltering before they reach production, the conversation delves into the urgent need for mastery over data and the art of effective implementation. Hear real stories of transformation as tools like Claude Opus pivot stagnation into success, illustrating the delicate dance between technology and strategy. Can these AI titans truly change the landscape of coding in 2026? Join us for insights that blend urgency with innovation. Listen now: [Companion Blog Post](#)

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The Hidden Cost of AI Automation: What My 13-Site Empire Actually Costs

Nick Creighton — Sat, 25 Apr 2026 21:43:30 -0400

# The Hidden Cost of AI Automation: What My 13-Site Empire Actually Costs Tuesday morning, October 15th. I'm reviewing my monthly AWS bill when a Slack notification pings. One of my automation pipelines just processed its ten thousandth article across my 13 sites. The notification says "milestone reached." The bill says three thousand, two hundred and forty-seven dollars. Everyone told me AI automation would be cheap. They weren't wrong about the APIs. Claude Haiku costs fifteen cents per million input tokens. The automation I built saves me twelve hours a week. What they didn't mention was everything else. Listen to Signal Notes wherever you get your podcasts.

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