Loops are replacing prompts. Verification is about to be your biggest problem.
Something shifted in the AI coding discourse this month. The argument is no longer about whether agents can write production The post Loops are replac…
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Agentic development hinges on verification. For cloud-native software, that is a runtime problem.
Async agents are only useful if you can trust what they hand back. In a distributed system, that trust comes The post Agentic development hinges on ve…
Git real: AI agents aren’t just for solo developers anymore
In the first week of June, three vendors pushed coding agents past the single-developer loop. The three launches sit at The post Git real: AI agents a…
Microsoft’s pitch to enterprises: Ditch Azure Repos for GitHub, despite its rocky reliability record
GitHub hasn’t had an easy year. The platform has been hit by repeated outages affecting core services — including the The post Microsoft&#…
Netlify CTO Dana Lawson: Writing code is no longer the job
“I’ve been doing this since the ’90s — decades of building guardrails to prevent humans from breaking production. We’re …
From Jupyter Notebook to production: How to ship AI systems that actually work
Moving from experimentation to production in AI requires a transformation of mindset, architecture, and engineering discipline. There’s no API w…
Debugging the undebuggable: building observability into probabilistic AI systems
Debugging used to be straightforward: A service failed, you checked the logs, followed the stack trace, and fixed the bug. The post Debugging the unde…
What Anthropic and OpenAI launched in 72 hours has Wall Street paying attention
Within 72 hours in this month, Anthropic and OpenAI each launched enterprise deployment arms, announced major financial services partnerships, and The…
CI wasn’t built for coding agents. Here’s what comes next.
For years, integration tests have lived inside CI pipelines, triggered on push and answered ten, twenty, or thirty minutes later. The post CI wasnR…
AWS found bugs in 60% of software requirements. Its fix isn’t more AI — it’s a 50-year-old logic engine.
The most expensive bugs in software aren’t in the code. They’re in the requirements that guide the code’s construction. That’s…
How to build a skills library for your engineering team
A few months ago, we realized that every engineer on our team was running a different version of their AI The post How to build a skills library for y…
Why agent harnesses fail inside cloud-native systems
Coding agents perform better with a harness that gives them the tools, guidance, and feedback signals to know what to The post Why agent harnesses fai…
The agent code explosion is here. We need to rethink our pipelines, fast.
GitHub recently published an update on availability following a couple of rough incidents in April. The article opened with a The post The agent code …
A nine-point checklist for shipping production-ready AI
Starting from square one Most teams can build an AI prototype. A notebook answers a few prompts, a demo agent The post A nine-point checklist for ship…
Anthropic wants to be the AWS of agentic AI
Earlier this month, Anthropic launched Claude Managed Agents in public beta. Two weeks later it added persistent memory. From this The post Anthropic …
“Developer loyalty is at zero right now”: Google doesn’t care which AI coding tool you use
“Developer loyalty is at zero right now,” Richard Seroter, Google Cloud’s Senior Director and Chief Evangelist, told The New Stack T…