# self-improvement Published articles for self-improvement. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Building a Personal Assistant Orchestrator with Claude Code and Headless Sub-Agents DevFeed: [Building a Personal Assistant Orchestrator with Claude Code and Headless Sub-Agents]() Original publisher: [Read original article]() Author: Eugene Petrenko Published: 2026-07-19T00:00:00Z Content type: article Language: en Sources: [Eugene Petrenko]() Topics: [AI Agent](), [Claude Code](), [Code](), [Processes](), [Git](), [Slack](), [OpenClaw]() Tags: [ai-agent](), [ai-agents](), [ai-coding](), [architecture](), [claude-code](), [code](), [comparison](), [eugene-petrenko](), [git](), [hermes-agent](), [infrastructure](), [jonnyzzz](), [openclaw](), [process](), [prompt](), [self-improvement](), [slack](), [tag-41199d53f463](), [workflow]() ### AI overview The article describes building a personal-assistant orchestrator from a prompt in an interactive Claude Code session. It routes requests from Slack and Telegram, assigns each task to a fresh headless sub-agent process, and uses files, process boundaries, and git to manage work and recovery. The author also compares the approach with OpenClaw and Hermes. ### Source excerpt In one afternoon -- one pasted prompt, included below -- we turned an interactive Claude Code session into a personal-assistant orchestrator: channels in, a fresh headless sub-agent per request, an inbox loop that delivers finished work before taking new work, and a three-lens quorum that reviews and ships its own process fixes. By day two it was also babysitting the machine's other AI Agent consoles through a guarded keystroke path. No daemon, no webhooks, no database -- jsonl files, blocking CLIs, and git as the deployment mechanism -- and a hands-on comparison against OpenClaw and Hermes. ## How to Make Team Retrospectives Effective DevFeed: [How to Make Team Retrospectives Effective]() Original publisher: [Read original article]() Author: Domenico Luciani Published: 2025-11-02T23:00:00Z Content type: opinion Language: en Sources: [Domenico Luciani]() Topics: [retrospectives]() Tags: [continuous](), [effective](), [retrospective](), [self-improvement](), [team](), [team-dynamics]() ### AI overview This opinion article explains how team retrospectives can support learning, self-improvement, idea sharing, celebration, and continuous improvement. It emphasizes psychological safety, focusing on processes rather than blaming people, and adapting the retrospective format to the team's situation. ### Source excerpt A team retrospective is not just another useless meeting, and if you feel so, it means you are doing it wrong, and this article is for you. ## Recursive Improvement: AI Singularity Or Just Benchmark Saturation? DevFeed: [Recursive Improvement: AI Singularity Or Just Benchmark Saturation?]() Original publisher: [Read original article]() Published: 2025-02-12T00:00:00Z Content type: opinion Language: en Sources: [Tim Kellogg]() Topics: [Artificial Intelligence](), [Large Language Model](), [Benchmark]() Tags: [ai](), [benchmark](), [llms](), [paper](), [self-improvement](), [training]() ### AI overview This opinion article examines a paper describing recursive self-improvement for large language models: models generate problems and answers, filter results through majority voting, and train on the resulting corpus. It argues that the approach may extend performance on incremental, objectively verifiable tasks, while facing limitations with ambiguous problems, creative writing, and cost. ### Source excerpt A fascinating new paper shows that LLMs can recursively self-improve. They can be trained on older versions of themselves and continuously get better. This immediately made me think, "this is it, it's the AI singularity", that moment when AI is able to autonomously self-improve forever and become a... (well that sentence can end a lot of ways) ## Better unit tests with Parameterized testing 📈 DevFeed: [Better unit tests with Parameterized testing 📈]() Original publisher: [Read original article]() Author: Sergio Sastre Florez Published: 2021-05-31T06:30:38Z Content type: tutorial Language: en Sources: [Sergio's little tech corner]() Topics: [Testing](), [Kotlin](), [Java](), [passwords]() Tags: [android-app-development](), [best-practices](), [data](), [java](), [kotlin](), [password](), [self-improvement](), [set](), [tdd](), [test](), [testing](), [tests](), [unit-testing](), [unit-tests](), [verify](), [writing]() ### AI overview This tutorial explains how parameterized or data-driven tests can improve unit-test quantity and quality. Using a password validator as an example, it discusses testing multiple inputs and expected outputs in JUnit 5 with Kotlin, with applicability to Java. ### Source excerpt While writing Unit Tests, we often verify that given an input, the output of the method under test is the one expected. When you execute the same test with a different set of inputs and expected outputs several times, you come up with Data Driven Tes... ## How to structure learning for maximum return DevFeed: [How to structure learning for maximum return]() Original publisher: [Read original article]() Published: 2019-04-10T00:00:00Z Content type: opinion Language: en Sources: [Vasya Drobushkov]() Topics: [Learning](), [Development](), [Kanban](), [gist]() Tags: [development](), [kanban](), [learning](), [self-improvement](), [upskill]() ### AI overview The author reflects on several approaches to self-improvement and technical learning, including reading fiction, studying processes, and filling technical gaps. They propose a more structured learning method based on a high-level plan and a tracking tool, comparing Scrum, Kanban, and GIST before selecting GIST. ### Source excerpt Photo by Tim Gouw on Unsplash In IT, it's very difficult to keep up-to-date. A full-time job doesn't give you a chance to upskill or try new things because you're too busy dealing with legacy code, developing features, etc. Yet, self-development is an important thing and I've tried my best over years to make it a habit. For the few past years, I've conducted a few experiments towards self-improvement, and I'd like to share a few of those here.