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171 posts · Last used 2d

Sanjay Mohindroo @smohindroo1@social.vivaldi.net
· 4w ago
“It’s not the will to win that matters—everyone has that. It’s the will to prepare to win that matters.” — Paul Bryant. Where are you preparing? #Preparation #Discipline #SuccessMindset #PersonalGrowth #Leadership #Confidence #LifeLessons #ThoughtOfTheDay
stayingalive.in

The Work Nobody Applauds

Success is built before opportunity appears. Preparation turns ambition into confidence, discipline, and lasting results.

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Sanjay Mohindroo @smohindroo1@social.vivaldi.net
· 1mo ago
Where would you draw the line between AI-assisted analysis and AI-made judgment in your organization? More importantly, who is accountable for that line? #ArtificialIntelligence #AIGovernance #CIO #BoardGovernance #Leadership #DigitalTransformation #EnterpriseAI #GenerativeAI #AIStrategy #FutureOfWork #DecisionMaking #TechnologyLeadership
stayingalive.in

What part of the organization’s thinking are we handing over?

AI adoption is not about automating the most work. Boards must decide which tasks AI should execute and which judgments humans must retain.

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Mark Levison @mlevison@hachyderm.io
· 1mo ago
Put GenAI usage into someone's performance review and you'll get exactly what you asked for. Some organizations now incorporate AI usage into performance reviews. What could go wrong? One team member generates multiple new features with 1000+ line pull requests, then drowns the rest of the team in review overload. Measuring individual productivity has always been a bad idea. Measuring it in an organization using AI is worse. If GenAI is an amplifier, it amplifies both the good and the bad. Measure velocity or individual productivity, and it gets amplified. Measure AI usage, and people will find a way to trigger it: you'll get a large bill from Anthropic or OpenAI to celebrate your "success," while drowning in AI-generated technical debt and security flaws. Two things from my Reading Rabbit Hole this issue: Bryan Finster argues AI is a "High Pass Filter" for software delivery, amplifying strong practices and exposing weak ones (https://bryanfinster.substack.com/p/ai-is-a-high-pass-filter-for-software) I think even the evidence for "amplifies strong practices" is thin, everyone claims it, nobody shows the data. And "Potemkin Understanding in Large Language Models" (https://arxiv.org/html/2506.21521v2) shows these tools don't understand what they're doing. They're very good mimics. Focus on the product and the team, not the individual. Don't measure AI usage or velocity. Not anti-AI. Studying where it breaks isn't anti-AI, it's the precondition for using it well. If your organization is setting GenAI adoption targets, what behaviour is it actually incentivizing? Every issue of my newsletter includes a Reading Rabbit Hole like this one. #AIinSoftwareDevelopment #Leadership https://agilepainrelief.com/newsletter/?utm_source=mastodon&utm_campaign=archive-reshare
AI is a High Pass Filter for Software Delivery
bryanfinster.substack.com

AI is a High Pass Filter for Software Delivery

A high-pass filter (HPF) is a circuit or software algorithm that allows signals with frequencies above a certain cutoff to pass while reducing those below it.

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