I have been developing Agentic Systems for around two years now. The same patterns keep emerging again and again, regardless of what kind of systems are being built.
I have learned them the hard way and many do so as well. The first project is not a great success, but you learn from the failures and apply the learnings in the next one. Then you iterate.
Today, I am sharing my system of how to approach development of LLM based applications from idea to production. Use it if you want to avoid painful lessons in your own projects. — Read More
Daily Archives: May 23, 2025
Anthropic’s new Claude 4 AI models can reason over many steps
During its inaugural developer conference Thursday, Anthropic launched two new AI models that the startup claims are among the industry’s best, at least in terms of how they score on popular benchmarks.
Claude Opus 4 and Claude Sonnet 4, part of Anthropic’s new Claude 4 family of models, can analyze large datasets, execute long-horizon tasks, and take complex actions, according to the company. Both models were tuned to perform well on programming tasks, Anthropic says, making them well-suited for writing and editing code.
Both paying users and users of the company’s free chatbot apps will get access to Sonnet 4 but only paying users will get access to Opus 4. — Read More
Forget IPs: using cryptography to verify bot and agent traffic
With the rise of traffic from AI agents, what’s considered a bot is no longer clear-cut. There are some clearly malicious bots, like ones that DoS your site or do credential stuffing, and ones that most site owners do want to interact with their site, like the bot that indexes your site for a search engine, or ones that fetch RSS feeds.
Historically, Cloudflare has relied on two main signals to verify legitimate web crawlers from other types of automated traffic: user agent headers and IP addresses. The User-Agent header allows bot developers to identify themselves, i.e. MyBotCrawler/1.1. However, user agent headers alone are easily spoofed and are therefore insufficient for reliable identification. To address this, user agent checks are often supplemented with IP address validation, the inspection of published IP address ranges to confirm a crawler’s authenticity. However, the logic around IP address ranges representing a product or group of users is brittle – connections from the crawling service might be shared by multiple users, such as in the case of privacy proxies and VPNs, and these ranges, often maintained by cloud providers, change over time.
… Today, we’re introducing two proposals – HTTP message signatures and request mTLS – for friendly bots to authenticate themselves, and for customer origins to identify them. In this blog post, we’ll share how these authentication mechanisms work, how we implemented them, and how you can participate in our closed beta. — Read More
The AI Engineering Stack
“AI Engineering” is a term that I didn’t hear about two years ago, but today, AI engineers are in high demand. Companies like Meta, Google, and Amazon, offer higher base salaries for these roles than “regular” software engineers get, while AI startups and scaleups are scrambling to hire them.
However, closer inspection reveals AI engineers are often regular software engineers who have mastered the basics of large language models (LLM), such as working with them and integrating them.
So far, the best book I’ve found on this hot topic is AI Engineering by Chip Huyen, published in January by O’Reilly. Chip has worked as a researcher at Netflix, was a core developer at NVIDIA (building NeMo, NVIDIA’s GenAI framework), and cofounded Claypot AI. She has also taught machine learning (ML) at Stanford University. — Read More
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