Latest AI and tech news
We’re relaunching Build with Claude Code, a 2-day intensive cohort-based course taught by John Kim, who has trained hundreds of engineers at Meta to use Claude Code in real production workflows....
Agents can generate code. Getting it right for your system, team conventions, and past decisions is the hard part. You end up wasting time and tokens in the correction loops....
If you’re shipping AI agents without offline validation, your users are the ones doing the testing. Get the practical framework for evaluating production-grade AI agents before they hit production....
Goldfish get a bad rap. Turns out they actually remember things for months, not seconds. Your agent, on the other hand, forgets everything the second the context window fills up....
Most online courses never get finished (~4% completion). Live cohorts get ~40%, roughly 10x higher. Live courses are the only courses people actually finish....
Imagine a simple scenario where an e-commerce web application calls an API endpoint that returns information about a customer order....
Agents can generate code. Getting it right for your system, team conventions, and past decisions is the hard part. You end up wasting time and tokens in the correction loops....
Authentication is often the least-tested part of an app. Live environments need network access and real credentials, while mocks miss the failures that break production....
Writing code is fast, shipping it is still hard. Railway’s push-button compute, storage, and networking is built for both small and hyperscale software....
Getting a CX agent live is only the first step. The harder work starts once real customers are using it....
Imagine a bank account with $100. Let’s assume that two separate withdrawal requests of $10 each arrive at the same moment. However, after the two withdrawals are made, the account still ends up $90....
The CIO of GlobalFoundries had a straightforward view of it: you don’t get AI agents until the data underneath them is real-time and governed....
Datadog’s free guide shows how to connect AI spend, infrastructure, and model performance into a single view, so you can correlate cost increases to the architecture changes that caused them before they show up on your cloud bill....
Agents can generate code. Getting it right for your system, team conventions, and past decisions is the hard part. You end up wasting time and tokens in the correction loops....
Consider what can happen when someone uploads a profile photo to a web application....
Every agent already runs a loop. Loop engineering adds a loop around the agent itself, enabling it to evaluate its output, try again when the work falls short, and refine its instructions when the same mistakes recur. Today, you perform that role: re...
Securing AI usually requires hardcoding permissions into application code for every MCP server, or using static API tokens for all-or-nothing access (and hoping your LLM doesn’t drift from intended actions)....
Give an agent an access token and it spreads: into the context window, into tool call logs, into notes it keeps between steps. Each copy works from anywhere, long after the fact....
Many teams over-provision containers, underuse spot instances, and have no visibility into which pods are burning budget. Get the eBook from Datadog, which covers five practical optimizations for Kubernetes and ECS environments with specific techniqu...
A schema change is usually one of the most difficult types of change for a software system. However, it might look quite small and simple in review. For example, it might be something as simple as a column being renamed, or a new field being added to...
Turning new models into systems that work inside real customer operations is still hard....
AI coding agents can generate code quickly, but CI checks often happen after the agents finish their work. Sonar Vortex changes this pattern. Sonar Vortex operates inside the agent’s coding loop, giving agents architectural context before they write ...
Designed and assembled in America, Matic is the world’s first robot built to understand you. Its new feature, Matic Cues, lets you interact with it like you would anyone else....
This isn’t a conference you sit through. AWS re:Invent includes 2,200+ sessions, and 70% are interactive; workshops, code talks, AWS Jams, GameDays, and the Architecture Rodeo, built for engineers who’d rather work through a problem than watch a slid...
In a service-based architecture, a single product screen showing a user profile, that user’s five most recent orders, the delivery status of each order, and a short list of recommendations requires data from four separate services. Each service store...
GLM-5.2 is Z.ai’s flagship long-horizon coding model, featuring a usable 1M-token context window that reliably maintains API contracts and engineering intent where others fail. Stop managing GPU clusters. With Crusoe Serverless Fine-Tuning, you custo...
Free masterclass: Learn practical strategies for predictable low-latency writes at scale...
Agents are hitting your signup flow and bouncing off a browser login built for humans. Every one that gives up is a signup you never see....
Every application built on stored data performs two kinds of operations against it....
AI is in your engineering workflow. While the token spend shows it, the throughput doesn’t. The human is very much still in the loop, and that’s a context problem....
On-call shouldn’t feel like constant firefighting. This guide from Datadog breaks down how high-performing SRE teams reduce alert fatigue, streamline incident response, and design rotations that don’t burn engineers out.You’ll learn how to:...
Try Matic, backed by their 6 month money back guarantee....
We’re hiring a part-time instructor for “𝐖𝐫𝐢𝐭𝐞 𝐏𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐆𝐫𝐚𝐝𝐞 𝐂𝐨𝐝𝐞 𝐰𝐢𝐭𝐡 𝐀𝐈”. This is a live, cohort-based course for software engineers....
What happens when a service sends a request to charge a customer, but the request times out with no response? The burning question is whether the charge went through. Or should it be retried?...
GPU-hour billing charges for the entire time a machine is reserved — setup, idle time, queueing, and failures — so your cost depends on infrastructure efficiency you don’t control. Crusoe Serverless Fine-Tuning bills per token processed during traini...
Users expect apps and agents to reach the tools they already work in. Every integration that gets you there is a different OAuth flow, a different token lifecycle, weeks of infrastructure before you write a line of product code....
Define tasks with Render’s lightweight SDK and chain them into long-running, distributed workflows. Launch your agents and batch jobs on demand. Render Workflows handles queuing, orchestration, and retries....
Why does something as simple as reading the time become a hard problem for distributed systems?...
AI is in your engineering workflows. While the token spend shows it, the throughput doesn’t. The human is very much still in the loop, and that’s a context problem....
An incident hits and you pull up the logs, only to find string based console output that tells you something broke but not why. That’s the problem with unstructured logging: it eats your quota and still leaves you guessing....
As AI agents take on decision-making, they need awareness of real-world conditions....
Every software company that builds an application serving more than one customer has to answer this question....