Diogo Almeida and team released Jev, a new frontier AI model trained using RLCD methodology, which outperforms Astra, Fable, and Opus on radiofrequency engineering tasks with claimed 20-200x faster performance.
An engineer from Pune reflects on his 14-year career path, beginning with a two-year gap after leaving his degree to work assembling computers. He describes how this detour—working with his friend building and selling PCs, and witnessing his sister's IT career—ultimately led him to software engineering, shaped by family influence and early mentors.
Craft is a collection of design engineering essays by Gustavo covering practical concepts across performance, typography, color, layout, motion, sound, and data visualization. The resource presents short guides on design tricks and useful ideas rather than comprehensive documentation, with most articles marked as coming soon.
An article exploring how AI agents can automate software development work. While agents have shown promise in specific tasks, most real software work still requires human engineers; the field is moving past initial hype to identify where agents excel (bug fixes, debugging) versus where human creativity matters most (killer features, architecture decisions).
This article outlines 10 foundational pillars for building codebases that enable AI agents to work more competently and efficiently, including end-to-end types, static analysis, context-enriched logging, test isolation, runtime mutability, programmable orchestration, modularity, terseness, documentation, and strategic comments. The principles mirror best practices for human engineers but have amplified benefits for agents by providing structural enforcement and reducing runtime errors.
Artificial Analysis released Capability Indices v1.1, updating domain-specific AI model evaluations across finance, legal, healthcare, engineering, and other sectors. The update incorporates stronger evaluations from Intelligence Index v4.3, adds agentic tool use benchmarks, and removes customer interaction metrics across most domains.
Weave is experimenting with using AI agents on a prediction market exchange to price the impact and utility of code pull requests, leveraging a central limit order book where agents can buy and sell based on their assessments of a PR's value relative to engineering time investment.
A Hacker News user asks about assembling technical engineering teams, noting that while recruiting experienced developers they've worked with is straightforward, finding additional candidates becomes time-consuming and exhausting. They seek advice from others who have successfully built high-performing technical teams on what challenges they faced and what strategies they changed.
A new book titled 'The Secret Life of Circuits' has been published and is now available for order. The book serves as a practical reference guide to electronics and circuit design, featuring over 300 diagrams and illustrations in a full-color hardcover format, with orders shipping directly from the publisher and through major retailers including Barnes & Noble and Amazon.
The US Strategic Petroleum Reserve uses salt caverns in salt domes along the Gulf of Mexico to store hundreds of millions of barrels of crude oil. This solution elegantly meets key requirements: long-term storage capacity, security against attacks, rapid release capability, and low maintenance costs over decades. Salt caverns offer advantages over alternatives like external floating roof tanks or underground concrete facilities in terms of scale, cost, and protection.
Security engineering is fundamentally changing as automation makes vulnerability investigation—historically the time-consuming core of the work—increasingly feasible to automate. While human expertise in understanding business logic and complex systems remains valuable, the economic advantage of experienced engineers' intuition about where to look for vulnerabilities is diminishing as machines can cheaply explore multiple hypotheses simultaneously.
The square–cube law, first described by Galileo in 1638, is a mathematical principle stating that as an object's size increases, its volume grows faster than its surface area. This has significant real-world applications in engineering and biology, explaining phenomena from heat dissipation in mammals to structural limits in buildings and vehicles.
CodeRabbit Triage helps engineering teams prioritize pull requests by scoring them from P0 to P3 based on urgency, risk, and ownership context, addressing the challenge that AI agents can now generate code faster than human teams can review it. The tool recognizes that while code generation is cheap, review capacity remains limited and human judgment is still essential for architectural decisions, so teams need deliberate prioritization rather than simple FIFO queues.
The article examines how Large Language Models amplify the Dunning-Kruger effect by enabling users to generate expert-sounding content without foundational expertise. LLMs, trained to be agreeable through RLHF, function as echo chambers that validate half-baked ideas with polished prose, eliminating the traditional friction that kept overconfidence in check and replacing hard-earned competence with an illusion of mastery.
AI agents are making the surgical team model economically viable by replacing support roles, but the article warns this could recreate the problematic 'rockstar engineer' culture if organizations forget that the nine support roles served purposes beyond code output.
The article argues that while tech companies like Netflix shaped industry practices through transparent blog posts enabling informed decisions, GenAI vendors like OpenAI and Anthropic embed practices in products with proprietary reasoning, creating a different dynamic where vendor revenue depends on adoption rather than on sharing knowledge.
The author argues that companies are adopting AI without outcome-driven justification, driven by investor pressure and hype. Two anecdotes illustrate how employees face career risk for questioning AI initiatives and how organizations pursue AI indiscriminately, wasting resources on failed projects. The piece advocates for building cultures that reward challenging assumptions rather than enforcing silence around poorly conceived strategies.
An article about engineered bacteria being developed as cancer therapies, though the full content failed to load due to technical issues.
Engineers often face pressure to choose between technical and management tracks for career advancement, but the author argues the best approach is alternating between both roles like a pendulum. This requires leaving behind engineering skills while managing and vice versa, as both roles demand full attention and cannot be mastered simultaneously.
Dan, an engineer in Los Angeles, discusses his experience building reliable AI agents for consumer use. He highlights the challenges of working with LLMs that fail unpredictably despite appearing capable, requiring constant monitoring and workarounds to constrain their behavior in production systems.