Add blog post on Sustainable Acceleration in ASDLC#430
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lhancock-scottlogic
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Looks good! I have left you a few comments. I would also try to break up the text a bit more as some of the paragraphs are a bit long and there are places where the topic changes slightly, which would be a good place to insert a break.
I would also consider using some subtitles to further break up the text, splitting your post up into different titled parts
…evelopment-life-cycle.markdown Changed summary
…tware-development-life-cycle.markdown Added commas Co-authored-by: lhancock-scottlogic <110816543+lhancock-scottlogic@users.noreply.github.com>
Updated the content and structure of the markdown file to enhance clarity and organization regarding the Agentic Software Development Life Cycle.
Updated the content structure and added sections on governance, policies, leadership, pacing, cognitive entropy, accessibility, and assurance to enhance clarity and organization.
Removed word, added comma
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@lhancock-scottlogic Thanks for reviewing this. I have incorporated a lot of the suggestions (section headers, etc). Let me know if there is anything else you think needs changing. |
| Human engineers move up the value chain focusing less on implementation and more on orchestrating design, evaluating trade-offs and shaping architecture. Their efforts to simplify are becoming increasingly strategically critical including reducing technical debt, minimising maintenance surface area, and preserving architectural clarity. In addition, prompt engineering is now a core competency, with AI agents' effectiveness depending on how effectively humans can define objectives, constraints, and architectural intent. This skill requires continuous refinement as model updates can greatly alter the output of prompts. Great prompts can (model updates permitting) be shared across teams as reusable interaction patterns between human engineers and AI agents. Planning benefits heavily from well-structured prompts reducing unnecessary iteration and minimising wasted AI Compute Unit (ACU) consumption. Plans very rarely survive implementation unchanged, but spending the time to resolve ambiguity before generating code is significantly less costly than correcting flawed assumptions afterwards. | ||
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| #### Pacing | ||
| The surge in AI generated activity is already exponential, placing significant infrastructure and scaling pressure on platforms such as GitHub. However, human attention does not scale exponentially. As AI generated activity such as pull requests continues to increase, a psychological strain can emerge in the form of mounting expectations for human engineers to review, comment and merge in increasingly compressed timelines. Let us take a moment to consider the Japanese concept of ma (間) which refers to intentional space or pause in both physical and temporal contexts. Hayao Miyazaki, co-founder of Studio Ghibli, once described it by clapping repeatedly and explaining “The time in between my clapping is ma. If you just have non-stop action with no breathing space at all, it’s just busyness.”. As human engineers begin collaborating with AI agents, intentional pacing becomes essential to supporting them as effective stewards of their systems. This is not inefficiency, but instead actively preserving long-term coherence in systems adapting to accelerated delivery: |
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I'd probably add a break before you begin talking about ma, as this paragraph is still a little long
Split up big paragraph
lhancock-scottlogic
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Jun 16, 2026
…evelopment-life-cycle to change date
…evelopment-life-cycle to 2026-06-17-sustainable-acceleration-and-the-agentic-software-development-life-cycle.markdown
Updated the publication date
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https://danallsop.github.io/blog/2026/06/19/sustainable-acceleration-and-the-agentic-software-development-life-cycle.html
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npm installfollowed bynpx mdspell "**/{FILE_NAME}.md" --en-gb -a -n -x -tif that's your thing)Posts are reviewed / approved by your Regional Tech Lead.