Allen Helton (@AllenHeltonDev) header
Allen Helton (@AllenHeltonDev) profile picture

Dad | AWS serverless hero | farmer | web dev | enterprise architect | product @momentohq

McKinney, TX
Joined February 2012
I've been building an adventure role-playing game for kids, and the amount of code I've pushed (ok, many coding agents have pushed) in the past couple of months is ridiculous. 🧵 Sponsored by @Faros_AI
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According to the report, teams heavily using code review agents are seeing first-review times drop almost 11%, compared with a 114% increase reported for first-review waits more broadly. There's something there, but I'm hesitant to say that's the full solution.
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We're incredibly good at generating code. Our next challenge is scaling how we validate it. The Faros report has some really interesting data, especially if you've switched to full-time agent coding like I have. fandf.co/3URa1VJ/
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You don't know patience until you explain client-side asset caching to an 8 year old 🫠
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It took about 10 turns, but I was able to get the @HomeDepot chatbot to write some code for me to determine an objective score for rating power drills 🤣 Remember people, guardrails aren't perfect! Where there's a will, there's a way.
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Adding a vector store will make your agent's memory dramatically better, right? Not necessarily. I recently did some benchmarks on retrieval methods and am genuinely surprised at the results because they contradict every talk I've seen on production RAG 🧵
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My main takeaway is to not add AI components because that's what articles on the internet or speakers at conferences say to do. Benchmark them. Every reranker, model call, and retrieval stage needs to justify its latency and complexity.
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Full benchmark, thoughts, and code: readysetcloud.io/agent-memor… Sponsored by @Oracle and @oracledevelopers. Opinions are my own.
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I learned last week you can run code in the chrome debugger in the console tab. For over a decade I've thought that was a read-only tab
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The amount of wasted tokens from repeated tool calls, metadata lookups, and semantically-equivalent messages in AI agents today is staggering. In 2025, I demonstrated how to build idempotent tools and how to design cacheable APIs for agent use. But that wasn't enough. 🧵
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My friends at @betterdbhq recently released two packages on npm and PyPI that make this dead-simple to add to your agent logic with only a few lines of code.
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I wrote up why caching is more important than ever and how you can add this to your apps in an afternoon. 👇 rdyset.click/c/ktoSJI/
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