# Brian Jenney Practical and actionable things you can do to get hired, stay hired and learn to code. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## How Software Developers Can Use Career Risk to Their Advantage DevFeed: [How Software Developers Can Use Career Risk to Their Advantage]() Original publisher: [Read original article]() Author: Brian Jenney Published: 2026-06-14T23:22:06Z Content type: opinion Language: en Sources: [Brian Jenney]() Topics: [Development](), [Job](), [Software]() Tags: [career](), [developer](), [engineering](), [job](), [junior-developer](), [money](), [software-developer](), [startup](), [stress](), [work]() ### AI overview The article argues that software developers should distinguish between types of career risk and use calculated moves to improve their skills and opportunities. It draws on the author's experience leaving a secure job, becoming a junior developer, and later moving to a startup where learning and salary increased. ### Source excerpt And It's Quietly Killing Your Career ## How AI-Assisted Development Uses Reviewed Design Documents and Extensive Testing DevFeed: [How AI-Assisted Development Uses Reviewed Design Documents and Extensive Testing]() Original publisher: [Read original article]() Author: Brian Jenney Published: 2026-05-30T17:42:50Z Content type: article Language: en Sources: [Brian Jenney]() Topics: [Artificial Intelligence](), [Code](), [Testing](), [Documentation](), [Kubernetes](), [Terraform](), [Mocking](), [Boilerplate](), [GitHub API](), [Figma]() Tags: [ai](), [api](), [boilerplate](), [code](), [documentation](), [figma](), [github](), [kubernetes](), [mocking](), [terraform](), [testing]() ### AI overview The author describes an AI-assisted development workflow in which reviewed, versioned design documents provide context for coding agents. Agents handle implementation and testing boilerplate, while developers decide expected behavior and test coverage. The author connects this process with frequent deployments and confidence in changes. ### Source excerpt AI writes basically all of my code now. ## How AI Is Changing Coding Interviews in 2026 DevFeed: [How AI Is Changing Coding Interviews in 2026]() Original publisher: [Read original article]() Author: Brian Jenney Published: 2026-04-28T16:21:33Z Content type: opinion Language: en Sources: [Brian Jenney]() Topics: [coding](), [AI Engineering](), [Artificial Intelligence](), [HackerRank](), [LeetCode]() Tags: [2026](), [ai](), [career](), [coding](), [interviews](), [software-engineer](), [technical-interview]() ### AI overview This opinion article argues that coding interviews in 2026 remain disconnected from day-to-day software work, while AI has changed how developers write code. It describes traditional data-structures-and-algorithms assessments and other interview formats developers may encounter. ### Source excerpt Coding interviews have been notoriously tone deaf for years. ## AI coding tools can increase code output without improving delivery outcomes DevFeed: [AI coding tools can increase code output without improving delivery outcomes]() Original publisher: [Read original article]() Author: Brian Jenney Published: 2026-04-11T16:09:44Z Content type: opinion Language: en Sources: [Brian Jenney]() Topics: [Artificial Intelligence](), [ai-coding](), [human review](), [Code review](), [Testing](), [telemetry](), [Claude](), [cursor](), [React]() Tags: [ai](), [ai-coding](), [claude](), [code-review](), [cursor](), [engineering](), [human-review](), [pull-requests](), [telemetry](), [testing]() ### AI overview The author argues that AI coding tools may increase code output and task completion without improving delivery velocity or business outcomes. The article combines industry reports with personal experience, describing longer code review and debugging times, higher bug rates, and cleanup work after rushed AI-assisted development. ### Source excerpt I've flip-flopped on this issue more times than a politician up for re-election. ## How Malicious Instructions in Retrieved Content Can Manipulate LLM-Powered Agents DevFeed: [How Malicious Instructions in Retrieved Content Can Manipulate LLM-Powered Agents]() Original publisher: [Read original article]() Author: Brian Jenney Published: 2026-03-30T15:28:41Z Content type: opinion Language: en Sources: [Brian Jenney]() Topics: [Artificial Intelligence](), [Large Language Model](), [trust](), [API](), [Code]() Tags: [ai](), [api](), [formatting](), [llms](), [payload](), [repo](), [trust]() ### AI overview This opinion article describes an experiment in which an agent searched a knowledge base, called an API, and answered questions. The author inserted unrelated, concealed instructions into an otherwise normal document, and reports that the model followed them. The article argues that malicious instructions embedded in webpages, PDFs, or GitHub repositories can pose a risk when retrieved by LLM-powered systems. ### Source excerpt "Humans wrote bad code way before AI." ## How to Improve Coding Interview Performance with Personal Stories and Targeted Technical Practice DevFeed: [How to Improve Coding Interview Performance with Personal Stories and Targeted Technical Practice]() Original publisher: [Read original article]() Author: Brian Jenney Published: 2026-03-24T15:05:22Z Content type: opinion Language: en Sources: [Brian Jenney]() Topics: [coding](), [Development](), [Code](), [JavaScript]() Tags: [approach](), [career](), [coding](), [interviews](), [javascript](), [manager](), [recursion](), [software-engineer]() ### AI overview The author describes struggling with coding interviews despite being able to do the underlying job. They recommend cataloging personal work stories for recurring behavioral questions and focusing practice on recurring technical gaps. ### Source excerpt Five years ago, during an interview for a senior dev role, I had a panic attack. ## What Practical Skills Do AI Engineers Need? DevFeed: [What Practical Skills Do AI Engineers Need?]() Original publisher: [Read original article]() Author: Brian Jenney Published: 2026-03-14T15:44:42Z Content type: opinion Language: en Sources: [Brian Jenney]() Topics: [Artificial Intelligence](), [Building AI Systems](), [Retrieval Augmented Generation (RAG)](), [Full-Stack](), [Web app]() Tags: [ai](), [ai-engineer](), [building-ai-systems](), [full-stack](), [rag](), [software]() ### AI overview The author reflects on designing interviews for an AI engineering replacement role and argues that the job is mainly about integrating AI into practical software. The article emphasizes full-stack development, agents, workflows, RAG pipelines, vector databases, and evaluation systems rather than model training or research. ### Source excerpt Last year I quit an AI startup. ## The AI Multiplier: Where Developers Actually Get Leverage DevFeed: [The AI Multiplier: Where Developers Actually Get Leverage]() Original publisher: [Read original article]() Author: Brian Jenney Published: 2026-03-07T21:57:25Z Content type: opinion Language: en Sources: [Brian Jenney]() Topics: [Artificial Intelligence](), [AI-assisted coding](), [coding assistant](), [coding](), [Software]() Tags: [ai](), [autocomplete](), [coding](), [coding-assistant](), [context](), [developers](), [refactor](), [tests]() ### AI overview This commentary describes how software developers can gain leverage from AI through progressively more advanced usage. It outlines coding-assistant tasks such as generating functions, refactoring code, writing tests, and explaining errors, then discusses using AI as a planning partner to analyze systems, identify risks, and propose plans before code is written. ### Source excerpt Last night I met up with Alex Lau, the author of Keep Calm, Code On, while he was in San Francisco. ## The Cyrano de Bergerac Strategy for Software Developers in the AI Era DevFeed: [The Cyrano de Bergerac Strategy for Software Developers in the AI Era]() Original publisher: [Read original article]() Author: Brian Jenney Published: 2026-02-21T17:04:34Z Content type: opinion Language: en Sources: [Brian Jenney]() Topics: [coding](), [Artificial Intelligence](), [Software](), [Retrieval Augmented Generation (RAG)](), [Large Language Model](), [Fine-tuning]() Tags: [ai](), [code](), [developers](), [fine-tuning](), [llm](), [rag](), [software]() ### AI overview This commentary argues that software developers can gain leverage in the AI era by translating ambitious or poorly defined AI proposals into practical, safe implementations. It uses examples involving retrieval-augmented generation, existing large language models, and the limits of general-purpose agents. ### Source excerpt Your job as a developer is changing and you might have more leverage than you think ## Five AI Engineering Skills for Full-Stack Developers DevFeed: [Five AI Engineering Skills for Full-Stack Developers]() Original publisher: [Read original article]() Author: Brian Jenney Published: 2026-02-19T17:03:06Z Content type: article Language: en Sources: [Brian Jenney]() Topics: [AI Engineering](), [Full-Stack](), [Large Language Model](), [Retrieval Augmented Generation (RAG)](), [Back end]() Tags: [ai-engineering](), [backend](), [cost](), [developers](), [full-stack](), [latency](), [llm](), [rag]() ### AI overview This article argues that AI application development is primarily product engineering around models rather than model research or training. It introduces skills including choosing models intentionally, managing token costs and latency, and using retrieval to ground LLM applications in company data. ### Source excerpt 5 Skills That Give Developers an Unfair Advantage ## Data Is the Bottleneck in Many AI Projects DevFeed: [Data Is the Bottleneck in Many AI Projects]() Original publisher: [Read original article]() Author: Brian Jenney Published: 2026-02-07T16:25:26Z Content type: opinion Language: en Sources: [Brian Jenney]() Topics: [data](), [Web Scraping](), [Structured-data](), [Artificial Intelligence]() Tags: [ai](), [data](), [data-pipeline](), [grounding](), [web-scraping]() ### AI overview The article argues that data collection and preparation, rather than wiring together AI components, are often the main bottlenecks in AI projects. It discusses messy real-world data, data pipelines, vector databases, and web scraping as ways to ground useful AI outputs. ### Source excerpt This is the first Saturday I've had off in a few weeks. ## No One Meant to Be Toxic: Inside an AI-First Startup DevFeed: [No One Meant to Be Toxic: Inside an AI-First Startup]() Original publisher: [Read original article]() Author: Brian Jenney Published: 2026-01-31T17:02:26Z Content type: opinion Language: en Sources: [Brian Jenney]() Topics: [Artificial Intelligence](), [AI Development](), [ChatGPT](), [data]() Tags: [ai](), [chatgpt](), [company](), [leadership](), [startups]() ### AI overview An account of how an AI-first startup's shifting leadership, reliance on AI as a substitute for planning, and urgency without clear requirements contributed to a toxic work environment. The article argues that AI tools cannot replace strategy, technical judgment, or defined goals. ### Source excerpt They say the path to hell is paved with good intentions. ## Learning to Code After 30 Requires Sustained Self-Study and Tolerance for Struggle DevFeed: [Learning to Code After 30 Requires Sustained Self-Study and Tolerance for Struggle]() Original publisher: [Read original article]() Author: Brian Jenney Published: 2026-01-24T16:01:58Z Content type: opinion Language: en Sources: [Brian Jenney]() Topics: [Learning](), [coding](), [Bootcamp](), [Software Engineering]() Tags: [careers](), [code](), [learn](), [learning]() ### AI overview This opinion article argues that adults over 30 switching into tech need structured self-directed learning, persistence through confusion and repetition, and realistic expectations about coding careers. It recommends filtering resources, reading documentation, asking better questions, using spaced repetition, and recording gaps in understanding. ### Source excerpt When's the last time you really learned something? ## Learning to Code in the Age of AI DevFeed: [Learning to Code in the Age of AI]() Original publisher: [Read original article]() Author: Brian Jenney Published: 2026-01-18T00:21:19Z Content type: opinion Language: en Sources: [Brian Jenney]() Topics: [Artificial Intelligence](), [coding]() Tags: [ai](), [coding](), [learn]() ### AI overview An opinion article argues that learning to code remains valuable even as AI generates code. It says coding knowledge helps developers verify, reason about, debug, and architect software systems rather than blindly trusting LLM output. ### Source excerpt If you're trying to become a developer in 2026, it probably feels like you showed up to the party five minutes after it ended. ## Interview Horror Stories (And What You Can Learn From Them) DevFeed: [Interview Horror Stories (And What You Can Learn From Them)]() Original publisher: [Read original article]() Author: Brian Jenney Published: 2026-01-09T16:02:05Z Content type: opinion Language: en Sources: [Brian Jenney]() Topics: [Job](), [Data structures]() Tags: [career](), [developer](), [google](), [interview](), [job-hunt](), [learn]() ### AI overview A developer recounts three interview horror stories, including an unprepared Google interview and a poor culture-fit experience, and draws lessons about understanding the interview format, preparing adequately, and recognizing bias and knowledge gaps. ### Source excerpt If you've been through the job hunt as a developer, you probably have at least one horrific interview experience. The kind that makes you reconsider your entire career, your life choices, and whether or not you should just quit and become a goat herder. ## The CTO Told Me to Leave Cursor On. The Interview Got Harder. DevFeed: [The CTO Told Me to Leave Cursor On. The Interview Got Harder.]() Original publisher: [Read original article]() Author: Brian Jenney Published: 2026-01-02T18:00:56Z Content type: opinion Language: en Sources: [Brian Jenney]() Topics: [cursor](), [Artificial Intelligence](), [coding](), [Code]() Tags: [ai](), [ai-tools](), [cursor](), [interview](), [vs-code]() ### AI overview The article argues that AI-assisted coding interviews can be more demanding than traditional live-coding interviews. Using Cursor may require candidates to explain their prompting, code-selection, and problem-solving decisions, while pretending not to use AI or claiming to understand code they cannot explain can undermine their performance. ### Source excerpt "Are you using any AI tools we should know about?" ## The 5 Worst Tech Trends of 2025 DevFeed: [The 5 Worst Tech Trends of 2025]() Original publisher: [Read original article]() Author: Brian Jenney Published: 2025-12-29T20:01:09Z Content type: opinion Language: en Sources: [Brian Jenney]() Topics: [Artificial Intelligence](), [coding](), [engineering-culture](), [Job](), [Bootcamp]() Tags: [2025](), [ai](), [coding](), [developers](), [engineering-culture](), [job](), [junior-developer]() ### AI overview An opinionated review of negative technology-industry trends observed in 2025, focusing on claims about AI productivity, a harder junior developer job market, and coding bootcamp closures. The supplied text is incomplete and ends during the bootcamp section. ### Source excerpt (And How to Win in 2026) ## I Went Viral With a Boring Take on AI DevFeed: [I Went Viral With a Boring Take on AI]() Original publisher: [Read original article]() Author: Brian Jenney Published: 2025-12-20T16:14:57Z Content type: opinion Language: en Sources: [Brian Jenney]() Topics: [Artificial Intelligence](), [Software Engineering](), [coding]() Tags: [ai](), [coding](), [software](), [software-engineering](), [technology]() ### AI overview The author reflects on a YouTube video about six months at a startup that unexpectedly attracted a large audience. They argue that AI tools are useful but do not justify sweeping claims that software engineering is over, and that online narratives about the field distort reality and may discourage people unnecessarily. ### Source excerpt This week, a YouTube video I posted unexpectedly took off. ## Free interview-preparation challenges for software engineering and front-end developer interviews DevFeed: [Free interview-preparation challenges for software engineering and front-end developer interviews]() Original publisher: [Read original article]() Author: Brian Jenney Published: 2025-12-15T20:00:52Z Content type: article Language: en Sources: [Brian Jenney]() Topics: [Learning](), [Programming](), [Data structures](), [Front end](), [Software Engineering]() Tags: [advice](), [coding](), [data-structures](), [front-end](), [learning](), [system-design]() ### AI overview The author describes spending $10,000 on Interview Kickstart after repeated technical interview failures, later reaching final rounds at Google and Meta without receiving offers. They share free interview-preparation challenges covering light data structures and algorithms, front-end development, system design, behavioral interviews, videos, resources and bonus questions. ### Source excerpt About 5 years ago, I dropped $10,000 on Interview Kickstart (not an endorsement and not NOT an endorsement either) after bombing technical interview after technical interview. ## How I Actually Use AI as a Developer (And When I Don't) DevFeed: [How I Actually Use AI as a Developer (And When I Don't)]() Original publisher: [Read original article]() Author: Brian Jenney Published: 2025-12-06T17:14:53Z Content type: opinion Language: en Sources: [Brian Jenney]() Topics: [Artificial Intelligence](), [Code](), [Python](), [Cloud Run](), [cloud-tasks](), [SQL](), [API]() Tags: [ai](), [cloud-run](), [cloud-tasks](), [code](), [developer](), [python](), [sql](), [workflow]() ### AI overview A developer describes a practical workflow for using AI-assisted coding under startup delivery pressure. The article covers making unfamiliar Python code understandable, evaluating architecture and debugging options across local and Cloud Run environments, and running rapid experiments involving batching, SQL queries, API calls, and logging. The author presents this as a personal workflow rather than a universal prescription. ### Source excerpt The workflow that helped me "make the impossible possible" in my first 3 months at a startup.