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The following article originally appeared on Arize’s blog and is being reposted here with the author’s permission. This week the AI community was in uproar about Jev from TypeSafe, not just a new model but a new kind of model: one that classifies, scores, and routes but can’t write a sentence. The reason for the […]
Will TypeSafe’s Jev Change How We Build AI Applications? Read More »
Ask most engineers what MCP is and you’ll get the same answer: a way to plug tools into an LLM. Fair enough, as far as it goes. But that description treats MCP like plumbing, and after months building MCP-based integrations for large enterprise platforms, I don’t think plumbing is the right metaphor. Plumbing moves water
AI is no longer just a feature you add to software. In a growing class of products, AI is becoming the foundation the entire product is built around. That changes almost everything. The architecture changes. The user experience changes. Data becomes an active product layer. Software needs to handle probabilistic outputs. Agents can perform actions
What Is AI Native Product Engineering? A Complete Guide Read More »
As a software engineer with more than seven years of experience before the coding-agent era, I never liked the idea of vibe coding. But I knew there was a clear line between it and using coding agents to generate clean, maintainable code. That line, where good software principles meet coding agents, is defined by software
You’re wrong. Clients don’t sign off on documents. They sign off on things they can see. Every extra call you schedule to “align on requirements” is another chance for the client to lose confidence that you actually understand their business, because right up until you show them something real, you’re just another vendor with a
Still think five rounds of requirement gathering calls are what get you the deal? Read More »
The following article originally appeared on Addy Osmani’s blog and is being republished here with the author’s permission. I cowrote a Google whitepaper about how AI is changing the software lifecycle. I’m not going to summarize the whole thing. Instead, here are the handful of ideas in it I think actually matter, plus six figures
Omio integrates OpenAI models across its engineering operations to accelerate travel product development and launch booking interfaces. The multimodal travel platform coordinates operations with over 3,000 transportation providers across 47 countries. Omio explicitly rejects the superficial addition of technology to outdated internal processes. The company’s CTO, Tomas Vocetka, requires all internal functions to completely redesign
Omio scales travel product development using OpenAI models Read More »
As syntax becomes cheap and abundant, architectural control becomes the scarce resource. Effective governance starts upstream, where intent, constraints, and threat models shape the agent’s working context before generation begins. The goal isn’t better prompting but build-time boundaries that prevent structurally invalid code from entering the system. The Frankenstein factories The dark factories (as Dan
Since its announcement in April this year, the proposed changes to billing methods on GitHub Copilot were a source of much speculation: how much more or less would a pay-a-you-use AI cost an organisation or individual compared to a flat-rate, monthly subscription? Just a day into the changeover to token-based billing for the LLM-based service,
GitHub Copilot users see token-based price hikes Read More »
Student retention has become a board-level metric for universities, bootcamps, and enterprise learning platforms. Yet many EduTech companies still struggle with fragmented LMS data, unreliable adaptive models, and FERPA compliance issues that slow releases and increase risk. This is where ADLC changes the conversation. An AI-driven software development lifecycle gives EduTech teams a structured framework
Predictive Analytics in EduTech Through an AI-Driven Software Development Lifecycle Read More »
