Developer Voices

Author: Kris Jenkins

Deep-dive discussions with the smartest developers we know, explaining what they're working on, how they're trying to move the industry forward, and what we can learn from them.You might find the solution to your next architectural headache, pick up a new programming language, or just hear some good war stories from the frontline of technology.Join your host Kris Jenkins as we try to figure out what tomorrow's computing will look like the best way we know how - by listening directly to the developers' voices.
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Language: en

Genres: News, Tech News, Technology

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What's Worth Knowing In AI Right Now? (with Henry Garner)
Thursday, 26 March, 2026

AI is changing the way we all build software — that much seems clear. But the landscape is moving so fast that even the people paid to keep up are struggling. MCP or skills? Fine-tune or just prompt? LangChain or let a thousand agents loose? With almost 70 competing technologies and a shelf life of maybe six months on any advice, how do you figure out what's actually worth your time?Henry Garner is CTO of JUXT, a consultancy with about 150 senior engineers working at the coalface of AI-assisted development, including building AI platforms for tier-one banks. JUXT publishes a quarterly AI Radar — 68 technologies rated and reviewed — and Henry's been watching his own team go through the full adoption arc, from "spicy autocomplete" skepticism through to building Byzantine-fault-tolerant distributed systems over a weekend with Claude. Along the way we cover MCP vs skills, Conway's Law for LLMs, neurosymbolic AI and the unexpected return of Prolog, the "Ralph Wiggum loop" for getting agents to converge on correct implementations, and Allium — a new behavioral specification language Henry's co-authored that sits between human prose and TLA+, aiming to give LLMs just enough structure to pin down what a system should do without falling into waterfall thinking.If you're trying to make sense of the AI tooling landscape, or you've hit that wall where your agents keep drifting away from what you actually wanted, Henry's thesis — velocity through clarity of intent — might well help out yours.--Support Developer Voices on Patreon: https://patreon.com/DeveloperVoicesSupport Developer Voices on YouTube: https://www.youtube.com/@DeveloperVoices/joinJUXT: https://www.juxt.pro/JUXT AI Radar: https://www.juxt.pro/ai-radar/Allium on GitHub: https://github.com/juxt/alliumAllium Documentation: https://juxt.github.io/allium/Composition at a Distance (Henry's blog post): https://www.juxt.pro/blog/composition-at-a-distance/A New Vocabulary for an Old Problem (Henry's blog post): https://www.juxt.pro/blog/new-vocabulary-for-an-old-problem/Model Context Protocol (MCP): https://modelcontextprotocol.io/LangChain: https://www.langchain.com/LangGraph: https://www.langchain.com/langgraphGas Town (Steve Yegge): https://github.com/steveyegge/gastownKiro (spec-driven AI IDE): https://kiro.dev/Phoenix (LLM observability): https://github.com/Arize-ai/phoenixTemporal: https://temporal.io/Taalas (LLM-on-a-chip): https://taalas.com/Kris on Bluesky: https://bsky.app/profile/krisajenkins.bsky.socialKris on Mastodon: http://mastodon.social/@krisajenkinsKris on LinkedIn: https://www.linkedin.com/in/krisjenkins/