Short-form insights you can read in under 5 minutes.
At the Monet Venice exhibit at Brooklyn Museum. The paintings only make sense when viewed from far enough back that technique gives way to the feel of mist, light, and water. I got that in gap tooth patches as crowds threaded by at touching distance from the canvases - losing forest for trees.
My first thoughts in any leadership role is who is my team. Who are my partners. Who are my advocates. Who can I really trust to do their job well, to focus on collective success, and be candid with me. That’s everything. Full stop.
I believe there is space for an AI assisted coding practice that aids in the prep, research, planning of a coding task, the completeness review and retrospection of the completed task but does not generate the code and tests itself.
The space would work for master developers working in high value, highly sensitive or safety spaces. For more junior devs and as part of every developers ongoing skills development as needed to keep our craft and minds sharp.
Is someone working up this practice? An ai assisted plan, human do, ai assisted check and act?
Recognize talent, value experience, develop human potential. You know, for the AI’s sake.
AI enables us to…
Replace software engineers with people expert at building, enhancing, and maintaining useful, safe, reliable, and cost efficient software.
Replace designers with people expert at crafting usable, consistent, and delightful experiences.
Replace product managers with people who understand why features exist, what customer problems they solve, and can validate they return on investment.
I.e. software engineers, designers, and product people.
AI is reducing the need for people who hack code, sling components on a page, and ensure the spreadsheets run on time.
And increasing the need for people who are genuinely good at their respective roles.
So, again, maybe we should recognize talent, value experience, develop human potential by investing in mentoring and training. ‘Cause AI.
People are working on disciplined practices to improve the code produced in collaboration with ai agents. People send me links to projects all the time and I thank you for that.
I’d also appreciate links to any research quantifying the impact of these practices on delivery speed and code quality.
I believe that undisciplined code generation leads to significant issues like code duplication and large batch sizes, which ultimately slow down delivery. As coders, we must actively engage in the coding process, focusing on analysis and execution to minimize code cloning and enhance incremental testing. Our unique human insights are essential in navigating complex codebases and ensuring effective project outcomes.
Claude code, Github, and Obsidian editor are my goto document management solution. Having great success producing deep and broad analysis quickly using these tools where we have to work from outlines, capture notes, understand and process a lot of written context.
Success requires a deliberate practice and a personal commitment that every word that appears in a final draft is verifiably true or qualified with attribution and written or reviewed and copy edited to the word by a me or one of my collaborators.
I’m currently working with a transformation client in LA, and I've learned that listening before speaking can open doors. We engage with individuals and teams, ensuring leaders know how to improve. Our team conducted 30 interviews in 3 days, emphasizing anonymity and collaboration. Immersion in this process, fueled by joy and urgency, truly showcases what a high-performing team can achieve.
NY AI Summit. Missing comicon and musing on what the cosplay for this conf would be.
Agile is dead. But…
We want to deliver value in short intervals We want to experiment, validate assumptions, fail fast, and adapt We want to track a small number of relevant measures and respond to what they tell us We want to make sure we have the right people in the right accountable roles We want to collaborate and communicate We want to identify blockers and work together to remove them
But… Agile is dead.
I believe that using AI agents to build code can significantly enhance our speed without compromising delivery. By analyzing our codebase to minimize duplication, breaking work into manageable increments, and meticulously planning our implementations, we can streamline our processes. I emphasize the importance of testing early, frequent commits, and reflecting on our work to identify areas for improvement. Let's harness these strategies to elevate our coding practices!
I see many organizations using AI ineffectively, leading to inflated productivity metrics but ultimately slowing down delivery and degrading quality. We're creating complex, poorly understood changes that increase QA time and failures in production. It's crucial to respect engineering principles and ensure teams are trained before deploying new tools. Let's not blame the tools when the real issue lies in our approach.