Avoid Automated Mistakes in Problem Solving

Day 7/7 — The Question ❓ 𝘚𝘰 𝘣𝘦𝘧𝘰𝘳𝘦 𝘸𝘦 𝘤𝘦𝘭𝘦𝘣𝘳𝘢𝘵𝘦 𝘴𝘱𝘦𝘦𝘥 𝘸𝘪𝘵𝘩𝘰𝘶𝘵 𝘵𝘩𝘰𝘶𝘨𝘩𝘵 — 𝘈𝘴𝘬: 𝘸𝘩𝘢𝘵 𝘩𝘢𝘷𝘦 𝘸𝘦 𝘣𝘶𝘪𝘭𝘵, 𝘢𝘯𝘥 𝘸𝘩𝘢𝘵 𝘩𝘢𝘷𝘦 𝘸𝘦 𝘭𝘰𝘴𝘵? Seven days. One question asked seven different ways. Here's where I land: AI is the most powerful tool software teams have ever had. But a tool that replaces thinking, instead of amplifying it, makes us weaker, not stronger. The answer isn't to write everything by hand again. The answer is intentional literacy: Require understanding, not just approval Invest in architectural knowledge, not just output Measure comprehension alongside velocity Treat code review as learning, not ceremony The teams that win the next decade won't be the ones who ship the most code. They'll be the ones who understand what they shipped. What's one practice your team could adopt tomorrow to stay literate in an AI-first world? #WhoOwnsTheCode #AICodeLiteracy #SoftwareEngineering #GenerativeAI #TechLeadership #EngineeringCulture #FutureOfDev #Day7of7

AI agents are transforming how product teams surface, categorize, and prioritize technical debt — turning it from an invisible backlog problem into a ranked, quantified item with a clear business case.

Most SMB AI projects don't fail because the model is bad — they fail because nobody mapped the exception paths, the edge cases pile up, and the team quietly reverts to the spreadsheet. We broke down the failure patterns we've watched kill rollouts (and hit ourselves on our own books) and the sequencing that keeps a project alive past week three. The playbook is boring on purpose: ship the narrow, high-volume workflow first, instrument every handoff, and never automate a process you can't already run cleanly by hand. https://lnkd.in/eDNrt7tk

Myth: CI capability is mostly about tools, templates, and technical know‑how. Misfire: Organizations double down on tool training while the real gaps — judgment, communication, and change navigation — go unaddressed. Reality: In an AI‑enabled operations world, the new CI capability stack is human‑centered. It’s built on critical thinking — the ability to interpret data, make sound decisions, understand context, and guide teams through uncertainty. Tools support improvement. Critical thinking drives it. More on the new CI capability stack coming tomorrow. #ContinuousImprovement #OperationalExcellence #OpusWorks #AIandWork #CICapabilityStack #CriticalThinking #WorkforceDevelopment

The hardest part of building something new is keeping track of what you have learned, and being honest about it. Over the past year we have talked with many founders and innovation teams, and the same pattern kept showing up. After months of customer calls and experiments, nobody could quite say what was proven and what was still a guess. Beliefs from January become "facts" by June, and enthusiasm gets counted as evidence. We rebuilt Assumption Mapper around that problem. Getting things in is now simple: paste a meeting transcript, or let your AI assistant (Claude, Cursor) file what it heard straight from your calls. And the processing is deliberately honest. Evidence is weighed by what customers did, not what they said, so ten enthusiastic quotes count for less than one signed pilot. When the evidence contradicts you, that belief gets louder. And no experiment starts without writing down, in advance, the result that would kill it. 👉 What you get is a live picture of what your business actually knows, and what it is still assuming. Give it a shot at assumption-mapper.com

Your team may not be asking you the same questions because they are incapable. They may be asking because the answers still live in your head. That is where a lot of owner bottlenecks come from. The process is not clear enough. The handoff is not documented enough. The expectations are not specific enough. The team does not have the tools, prompts, or decision-making structure to move forward without checking with you first. That is exactly the gap the Team Efficiency Makeover is designed to address. In this video, I explain how clearer roles, stronger systems, and practical AI support can help your team operate with more independence and fewer repeated questions. Learn more about the Team Efficiency Makeover here: https://lnkd.in/g28uW27K

I am excited to announce that I will be speaking at the Testing Talks Conference in Sydney on Thursday, 6 August 2026.🎤 My session, "Performance Engineering in the Age of AI: Real-World Lessons," will be a discussion-led conversation with fellow practitioners from the testing community. We will explore how organizations are rethinking performance testing for AI-enabled applications and LLM-driven experiences. Key topics we will cover include: - The increasing importance of performance engineering in the AI era - Key considerations for modern testing teams - Real-world lessons from enterprise environments - AI-driven analysis, scripting, and autonomous testing approaches - Balancing speed, quality, and reliability as AI adoption accelerates I look forward to sharing insights and connecting with peers at what promises to be a great event! 🎟️Tickets: https://lnkd.in/gErPpGNQ #TestingTalksConference #OpenText #PerformanceEngineering Cameron Bradley Joanna Alexiou Tim Rand Ray Ffrench David Rossi Meenakshi Shahi Wayne Tomlinson Marina Campbell Judith McDonald Sophia Bahrami Paul Utiu Sharon Levin Riccardo Sanna

🚀 Tired of losing brilliant ideas in scattered notes and forgotten chats? What if you had a personal AI Second Brain that never forgets, connects your knowledge automatically, and actually gets smarter every single day? I just built one using Claude, Obsidian and the results have been transformative. Why it works: Obsidian stores everything as plain Markdown files you fully own local, private, and future-proof. Claude (via Code/Desktop and MCP) acts as your intelligent maintainer: ingesting raw captures, synthesizing insights in your voice, creating atomic notes, and building rich connections. The Daily Compounding Effect: Ruthless capture → AI-powered processing & linking → Automated maintenance. Query across your entire history with contextual depth. Project folders keep Claude focused; skills and autopilot routines handle the rest. No more rebuilding context from scratch. Your ideas compound. Your thinking elevates. This setup is accessible (takes an evening to launch) and incredibly powerful once the graph starts growing. Plain text means you’re never locked into one tool. #SecondBrain #AIProductivity #Obsidian #ClaudeAI #PersonalKnowledgeManagement #Productivity #KnowledgeWork #FutureOfWork

Quick gut check for anyone rolling out AI at work. You handed your team a tool. Told them to use it. How many actually changed how they work? Versus just adding one more tab they glance at? Most rollouts I see stall right there. The tool arrives, the habits don't move, and six months on someone asks why the ROI never showed. The tech was never the hard part. The habits are. What's the first habit you'd change?

There are only two types of people right now: Those scaling. And those stuck. Scaling = systems Stuck = manual work Simple. I chose systems. AI stack. Clear workflow. Execution speed. You can stay where you are. Or you can level up.