{"slug": "on-jev-and-athletics", "title": "On Jev and Athletics", "summary": "A developer has integrated Jev, a decision-making tool from TypeSafe, into The Pipeline Framework (TPF) to handle small, fast, cheap decisions over supplied data rather than relying on a single large model to automate an entire process. The developer argues that daily AI use gives a misleading impression of how easy full automation is, since reliability degrades across many steps and small problems compound. Jev returns structured, typed results from a defined set of possible decisions, which TPF uses to connect AI decisions, ordinary code, human input and real-world actions.", "body_md": "I think using AI every day has given us a slightly misleading idea of how easy automation is becoming.\n\nModels have improved incredibly quickly. Give an AI a browser, some skills and a bit of context and it can do impressive things.\n\nSo it’s easy to think: surely automating the whole process is next.\n\n**I’m not so sure.**\n\nWe’ve been running 100 metres with 30” hurdles — and still hitting a few — and now we’re talking about running 400 metres hurdles at the Olympics.\n\nA skill that works while you’re watching is very different from something that has to work hundreds of times on its own.\n\nSmall problems multiply. A slow AI call repeated ten times becomes a slow process. Something that’s reliable 98% of the time doesn’t look nearly as good after twenty steps. Websites change, logins expire, bot protection gets tougher. And giving an AI access to everything it might need brings its own obvious problems.\n\nThis is one reason I’ve decided to integrate Jev into The Pipeline Framework.\n\nJev doesn’t try to solve all of that. It does something much narrower: make small decisions over supplied data very quickly and very cheaply.\n\nAnd that compounds beautifully.\n\nData leads to a small decision, which produces more data, which informs another decision, and eventually the software does something.\n\nThat’s much more interesting to me than asking one enormous model to figure out the whole process.\n\nHere’s the lovely coincidence I only noticed after integrating Jev.\n\nThe company behind it is called TypeSafe.\n\nAnd strong typing is also one of the ideas at the heart of The Pipeline Framework (as is the case with many programming languages).\n\nThat’s not just a naming coincidence: Jev doesn’t return some prose and hope the application interprets it correctly. You give it a defined set of possible decisions and get a structured result back.\n\nTPF takes the same idea further through the rest of the application: typed data goes into steps, typed data comes out, and those types connect AI decisions, ordinary code, human input and real-world actions.\n\nJev makes the decision faster and cheaper.\n\nTPF makes the process around the decision something you can actually build software on.", "url": "https://wpnews.pro/news/on-jev-and-athletics", "canonical_source": "https://dev.to/mbarcia/on-ai-and-athletics-2ghf", "published_at": "2026-09-25 12:42:47+00:00", "updated_at": "2026-09-25 13:01:37.072291+00:00", "lang": "en", "topics": ["ai-agents", "ai-tools", "developer-tools", "artificial-intelligence"], "entities": ["Jev", "TypeSafe", "The Pipeline Framework"], "also_reported_by": [], "alternates": {"html": "https://wpnews.pro/news/on-jev-and-athletics", "markdown": "https://wpnews.pro/news/on-jev-and-athletics.md", "text": "https://wpnews.pro/news/on-jev-and-athletics.txt", "jsonld": "https://wpnews.pro/news/on-jev-and-athletics.jsonld"}}