Understanding how Core Java really works can help you write simpler, faster applications.
I have a Spec Driven Project with 674 documents incl 181 specs, 429 tasks, and 40 project docs. About 1/3 of these are an acceptance sub-project to show the root project meets fit-for-purpose requirements. I used Fable to convert these to and from AsciiDoc, Markdown, and HTML. From this, I tried to draw some conclusions about which format is better than the others for AI specifications. TL;DR:…
Optimising your memory allocations in Java could make far more difference than your choice of Garbage Collector and may even change which is the best garbage collector. In this post I look at a simple event to response latency benchmark, MarketDataSnapshot to NewOrderSingle at 50K/s for 30 minutes using JLBH to test Chronicle-FIX. The goal is to compare a system which is doing redundant work (in…
While I am sceptical of using AI for release code, it has plenty of uses that previously weren’t practical, such as determining how easy your software is to use. If an AI can “figure it out” with a few hints, then you are on the right track. For me, the value of AI is what you learn using it. For more Techincal Information on Chronicle-FIX What AI Does Well and What It Doesn’t Claude and Codex are…
Peter Lawrey is an Australian/British software engineer and entrepreneur best known for work on ultra-low-latency Java systems and for leading the open-source OpenHFT libraries. He is the founder and chief executive of Chronicle Software, a London-based company whose technology is used in trading and market-infrastructure workloads. Lawrey is also a recognised Java community figure: he was named a…
In a previous article I looked at one-shoting a solution to optimise code to show the variation in different AI. Thsi is the not the best way to get what you want however. More often you need to either refine the prompt or give feedback. After one-shoting the same prompt on multiple AI, I have created a refined prompt based on the various concerns with previous results. The prompt Based on the…
As different AIs are implemented differently, they don't all provide the same answer, nor do they consistently outperform one another. The best approach is to use multiple AI and pick the one you like best. My goal here is not to declare a winner based on one example, but instead to show the variety of answers you can get with different AI. I asked each AI to Suggest how to implement this more…
TL;DR Human-in-the-loop is essential; AI offers probability, not certainty. AI excels at word-smithing , so spend more time on documentation and context. Leverage diverse AI models for varied research, improvements, and analysis. Be wary of deskilling : if AI makes a task trivial, agents may soon replace it. You should feel like you are testing the boundaries of what AI is capable of for at least…
A functional interface can extend a marker interface, functional interface, non-functional interface, and an annotation. A recent X poll suggested 25% of those responding didn't know that.
Table of Contents Introduction Superhuman Intelligence Is Already Here ATMs Didn t Replace Bank Tellers About Me Multidimensional Growth Areas of Career Development Scope of Consideration Roles Where All Areas Are Important The Range of a Founder s Role How Will AI Change Development? How You Ask the Question Changes the Result Some key terms in understanding how Generative AI works Estimating the…
As many have observed, at best, AI generates either: Mundane, repetitive documentation or code that most experts already know or If an expert doesn t know it, they can ask an AI to explain it anyway. Is it the case that if an AI can generate it, it s not worth adding to your documentation or code? While this is usually the case, there is still value in reading AI-generated documentation as a means…
One of the first challenges developers might face is getting generative AI to produce accurate documentation. Once you are comfortable doing this, the next challenge is creating enough documentation to be helpful without overwhelming the reader. Until generative AI came along, it might have seemed like there could never be too much documentation. Now, the challenge is to provide just enough detail…
This article was AI-generated using this project as context. AIDE Project . The purpose of this project is to see how much an AI could generate given enough context, and in this project, all the "source" code is generated using the requirements and unit tests as context. This follows the Next-Level Development: Harnessing AI with AIDE approach. The main parts are: Requirements Documents in .adoc…
If it s worth doing by hand, it s worth automating. Just because not everyone is (yet) a world-class developer; that doesn t mean we can t step closer to that expert-level space. In this post, I will introduce AIDE (Artifical Intelligence Development Environment), a powerful workflow that merges AI-driven code generation with a sharp focus on documentation-driven development. With AIDE, I tap into…
Introduction Java’s annotation system has come a long way since its introduction in Java 5. At first glance, annotations appear to be mere metadata markers on classes and methods. However, annotations can do much more than that. You can nest types within them, incorporate fields that reference helper classes, and even embed logic via static singletons. These capabilities provide a powerful…
I find time fascinating and surprisingly complex. Time zones and calendars change from place to place over time. There are a number of interesting websites on the subject. Time is one of those concepts that appears deceptively simple on the surface yet becomes increasingly intricate the more we examine it. As software developers, we often face scenarios where we must handle dates and times and…
Artificial Intelligence (AI) has long promised to transform software development. Yet, as many experienced engineers discover, initial enthusiasm often settles into a more subdued reality. This is the "Trough of Disillusionment" within the Gartner Hype Cycle—where inflated expectations give way to measured assessments. In this phase, teams confront the practical limitations of AI-driven tools,…
This is the first in a series of posts supporting a talk I will be giving online at JChampionConf 27th January 27th 2025. Lessons learnt from founding my own company, and over 30 years hands on coding In these posts, I am looking to provide some theory as well as practical examples. One way to try to predict what is possible in the future is to look at the past. One of may favourite ways to look…
Not surprisingly, the system prompts for “o1” are restricted, but it can provide a hypothetical answer. Understanding the Role of System Prompts System prompts serve as the invisible backbone of an AI’s reasoning process. They define core objectives, ethical boundaries, and operational tactics well before the user asks a question. In older models, these prompts were often implicit or…
Introduction Measuring an object’s size in Java is not straightforward. The platform encourages you to consider references and abstractions rather than raw memory usage. Still, understanding how objects fit into memory can yield significant benefits, especially for high-performance, low-latency systems. Over time, the JVM has introduced optimisations like Compressed Ordinary Object Pointers…
Standard Java libraries and idioms may only sometimes suffice in high-performance and low-latency Java systems. This article explores unconventional yet practical techniques that push Core Java to its limits, focusing on performance, diagnostics, and determinism. Drawing on experiences from building ultra-low-latency libraries and infrastructure, we will highlight patterns such as capturing stack…
TL;DR Problem: Java’s standard serialisation can be slow due to scattered object fields and reflection-based overhead. Approach: Emulate C++-style trivially copyable objects by restricting fields to primitives, enabling bulk memory copies. Result: Near C++-like serialisation performance, dramatically reducing latency and improving throughput. Trade-offs: Requires careful design, limited…
Distributed unique timestamp identifiers provide a powerful means of generating globally unique, human-readable 64-bit values at sub-microsecond speeds. By embedding a host identifier directly into a nanosecond-resolution timestamp, you gain a simple, chronologically sortable, and intuitive scheme for correlating events across multiple hosts. This approach offers significant benefits in…
This article explores a subtle Java conversion puzzle that challenges assumptions about how arithmetic operations, implicit casting, and floating-point conversions interact. Inspired by complexities often encountered in low-latency and high-performance environments, it demonstrates why a keen understanding of Java’s type system is essential for building reliable and efficient applications.…
1. Defining the Problem In many numerical computations, one would reasonably expect that rounding 0.499999999999999917 should yield 0 , since it appears to be slightly less than 0.5 . Yet, in Java 6, calling Math.round() on this value returns 1 , a result that may initially seem baffling. This seemingly minor discrepancy stems from the interplay of binary floating-point representation, rounding…
Peter Lawrey is the CEO of Chronicle Software, which counts multiple Tier 1 banks among its clients. He is a Java Champion who has provided the highest number of Java and JVM-related answers on stackoverflow.com. He also architected low-latency Java trading libraries downloaded 13 million times in October 2024. In this video, Peter examines how trading systems are designed to support…