Implementing Project Management Software

The best thing I ever did for my AI projects? I invited the biggest critics into the room. Sounds counterintuitive, right? Here's what I've learned across 200+ AI deployments: The skeptics, the curmudgeons, the people who question everything — they're not trying to kill your project. They're showing you exactly how to bulletproof it. But here's the catch: timing is everything. Bring them in too early (during brainstorming or exploration), and they'll suffocate momentum before ideas have room to develop. Bring them in too late (after you've committed resources), and their insights can't save you anymore. The sweet spot? Post-design. When you have a concrete solution that needs stress-testing. When the strategy is formed enough to withstand scrutiny but flexible enough to improve. That's when skeptics deliver maximum value. Here's how to make it work: Set expectations upfront. Tell your team you're deliberately bringing in critics to strengthen the project. Frame it as quality assurance, not a threat. Give them a clear job: Find every weakness. Surface every risk. Reveal organizational realities that need addressing. Document everything they say. Every objection becomes a blind spot you can now account for. The result? → Your plan becomes stronger. → Your strategy accounts for real resistance. → Your risk mitigation addresses actual organizational dynamics. Everything is already accounted for before implementation begins. The critics aren't sabotaging your AI initiative. You're sabotaging it by not leveraging them properly. What's been your experience with managing skeptics in transformation projects?

If I had to pick and roll out a PM tool today, Here's what I'd do: Step 1: Start with the pain, not the platform ↳ Interview PMs, sponsors, and execs on what's broken today ↳ Map current workarounds (Excel chaos, email threads, status guessing) ↳ Define 3-5 must-haves the tool needs to solve immediately Step 2: Evaluate with real work, not demos ↳ Shortlist 1-2 tools that fit your maturity and budget ↳ Run scripted demos for apples-to-apples comparison ↳ Involve multiple relevant stakeholders in the evaluation ↳ Have basic objective scoring mechanisms ↳ Run a 2-week pilot with actual projects and real users ↳ Test adoption friction - if PMs resist in week 1, they'll resist forever Step 3: Configure light, launch fast ↳ Set up core workflows only (intake, status, risks, decisions) ↳ Avoid customizing everything - start with 80% out-of-the-box ↳ Build templates that save time, not add steps Step 4: Run pilots before full rollout ↳ Start with 1-2 teams who are eager to try ↳ Test workflows with real projects for 30-60 days ↳ Gather feedback weekly and adjust configuration ↳ Document what works and what needs fixing Step 5: Drive adoption like a product launch ↳ Train in small groups with real scenarios, not feature tours ↳ Set up a command center with core team and champions ↳ Assign tool champions in each business unit ↳ Provide hand-holding initially for hesitant users ↳ Celebrate early wins publicly and share quick-win stories Step 6: Scale thoughtfully across the organization ↳ Roll out in waves by team or business unit ↳ Use lessons learned from pilots to refine approach ↳ Keep training tight and scenario-based ↳ Monitor adoption closely in each new group Step 7: Measure what matters ↳ Track adoption rate and time saved per PM weekly ↳ Tie tool usage to portfolio visibility and decision speed ↳ Iterate based on feedback - drop what doesn't stick ⚠️ What I'd avoid at all costs: ↳ Buying a tool before fixing your process ↳ Rolling out to everyone at once without champions 💡 What's the biggest mistake you've seen with PPM tool rollouts? ♻️ Repost to help PMOs succeed! 🔔 Follow me (Hussain Bandukwala) for more content like this. 🗝 To get a jumpstart to review PM/PPM tools, use resources like Gartner / Capterra, TechnologyAdvice & Panoramic Solutions.

Ever seen a project update look like a crime investigation? Slack says “Done.” Email says “Pending.” Excel says “Who even owns this?” And by the time you find the real answer… ...the deadline has quietly retired. Here’s the kicker: Most teams think the problem is “communication.” It’s not. It’s context-switching disorder... ....brought on by tool sprawl and blind optimism. We bounce between five apps... ...like it’s cardio, burn time, lose clarity, and then blame “alignment.” That’s not project management. That’s organized chaos with a JIRA badge. The antidote? → One dashboard → One truth → One place to point fingers (professionally) Here’s what to do inside Teamwork.com: ✅ Map every deliverable in Portfolios- owner, budget, deadline ✅ Use Workload & Time Tracking to catch burnout early ✅ Automate updates via Slack/email- no more “missed memos” ✅ Flip between Board & Gantt views like genres- without losing the plot Proof? Teamwork now holds nearly half of Planview’s PM software market. And 82% of companies already use tools like this. Translation: half the world’s done chasing updates in WhatsApp threads. When everyone sees the same board, confusion fades. Accountability sticks. That’s why high-performing teams don’t just “align”- they sync. Question: If your team tools had a family WhatsApp group… Would anyone reply on time?

Ever feel like your team is stuck in an endless loop of manual data entry? (Automation Tip Tuesday 👇) That’s exactly where one of our clients — an education consulting firm — found themselves. They were juggling a whole tech stack of tools that didn’t “talk”  to each other, creating inefficiencies and double work. We started with a look into their sales workflow. 🔹 Sales data lived in HubSpot, but once a deal closed, someone had to manually update Asana to track project progress. 🔹 Internal teams worked from one Asana board, but clients needed visibility into their own project timelines — cue more manual updates. 🔹 With so much repetitive data entry, valuable time was being wasted on low-impact admin work. Here’s what we did: 🔗 HubSpot → Asana automation: We created an integration that auto-generates project tasks in Asana when a deal reaches a certain stage in HubSpot. No more copy-pasting! 📢 Internal and client boards sync: Internal progress updates in Asana now automatically reflect on client-facing Asana projects, reducing the back-and-forth. Less busywork, more productivity. By eliminating duplicate data entry, the team saved 10+ hours per week — time now spent on strategy and client success. When your tools work together, your team can focus on what really matters. Where is your team losing time? Drop a comment below! ⬇️ -- Hi, I’m Nathan Weill, a business process automation expert. ⚡️ These tips I share every Tuesday are drawn from real-world projects we've worked on with our clients at Flow Digital. We help businesses unlock the power of automation with customized solutions so they can run better, faster and smarter — and we can help you too! #automationtiptuesday  #automation #workflow #efficiency

One matrix to rule your project Imagine this: You are on a cross-functional project team, a group of talented and skilled individuals. You begin working with the team on project activities that align with your skill sets. When some progress is made, others suddenly start questioning or commenting on your role in the project. What value are you adding? Why are you even required on the project? You are not doing what you are expected to do You expect others to do certain things, whereas others expect you to do those things.   Sound familiar? I have been there. We have all been there. It is that moment when you realize that the roles of the team members are not clear. There is so much confusion, and it is not clear who is responsible for what. That is exactly where the RASIC matrix comes in. It's not just another project management tool; it's the engine, the compass, and the clear sailing instructions a project team desperately needs.   Now, picture this instead: You are kicking off a new project. Before the first task even begins, you and your team collaboratively map out every key activity. For each activity, you ask: - Who is Responsible (R) for different activities involved in the project? - Who is Accountable (A) – the single person who signs off, owns the outcome of different actions and takes the ultimate bow (or takes the hit)? - Who needs to be Supportive (S), offering resources or assistance? - Who needs to be Consulted (C) for their invaluable input before a decision is made? - Who needs to be Informed (I) about the progress or decision after it's happened? ....and just like that, the ambiguity goes away. Suddenly, everyone knows their role. There are no more assumptions, no more duplicated efforts, and definitely no more "I thought you were doing that!" or "You are not doing your work properly!" moments. The person Responsible gets to work, knowing they have the backing of the Accountable person. The Consulted feel valued, and the Informed stay in the loop without constantly asking about the progress. The result? The team moves swiftly and directly towards the finish line. Collaboration flourishes because clarity exists. This is the tool that I always emphasize using in the training sessions that I conduct. Takeaway: If your projects ever feel like that spinning boat, give RASIC a try. It’s a simple yet powerful matrix that can transform confusion into clarity, and effort into impact.   What are your experiences with RASIC? Share your success stories or challenges in the comments below. #ProjectManagement #RASIC #RACI #Teamwork #Leadership #Communication Picture credits: https://lnkd.in/dk5kpEtT

For PMs who want to use AI agents to be more productive but feel stuck coming up with ideas, I've been experimenting with a prompt: (this works best in a project that already has context on you/your team/product) ❝❝❝ Based on what you know about me and my organization, please brainstorm five ideas for an AI automation I can build using platforms such as Zapier Agents/Lindy AI/Relay app/Cassidy AI/Gumloop/ etc. These should help me as a product manager save time on draining-yet-essential tasks that take me away from more valuable, strategic, and creative use of my attention and energy. Ask yourself: What ongoing repetitive work requires some judgment and writing abilities, but not my full expertise and intuition? # IMPORTANT: these should be event-driven AI automations, not batch tasks Only suggest event-driven automations that process items one-at-a-time as they arrive. Do NOT suggest batch tasks that process multiple items on a schedule (e.g., "every morning scan all..." or "weekly compile..."). Why: AI automations shine in one-at-a-time, repetitive tasks. They do best when designed for immediate responses to individual triggers. ❌ WRONG (Batch Task): "Every morning, scan all new support tickets and summarize them" ✅ RIGHT (Event-Driven): "When a new support ticket arrives, analyze it and alert me if it's urgent" # Examples Below are examples of use cases where product managers have gotten a lot of value from AI agents. 1. Compile fragmented information that would require a lot of clicks “When a new message is posted in the #feature-requests Slack channel, distill the customer request into 2-5 keywords. Search those keywords in recent Slack threads, HubSpot conversations, and Gong snippets, and reply to the thread with what you find.” “Every morning scan my calendar for customer calls, and instead of searching the web, DM me with recent interactions from this customer in Salesforce, Gong, and Zendesk.” “Every Monday morning, prepare a competitor activity digest by scanning recent blog posts, App Store updates, and X announcements.” “When a customer churns, post a message in the #churn-lessons channel with recent support interactions, NPS rating and date, and churn survey response.” 2. Boring, Sisyphean tasks with high upside “Monitor the pricing pages of 5 competitors for changes.” “DM me a weekly report with bugs that are nearing their SLA deadline for the associated customer, and cc each respective CS representative.” 3. Scanning exhausting amounts of data “DM me with support cases where the resolution was around product confusion rather than tech.” “Monitor NPS responses being posted as messages in a Slack channel. If something is clearly a technical issue, create a support ticket in Zendesk.” 4. Drafting updates “Every Friday at 10 a.m., write a summary of progress made across all teams in our project board, across epics, changes made to scope, and highlight any timeline changes.” ❞❞❞

The most important thing Anthropic shipped this month wasn’t a model. It was a 33-page PDF that could easily go unnoticed. It’s called Skills. Reusable workflows you build once, that Claude runs consistently every time. Available in Claude, Claude Code, and via API. Deployable org-wide. Think of it this way. MCP gives Claude access to your tools — Figma, Notion, Slack. Skills teach Claude how to use them properly. One is the kitchen. The other is the recipe. What caught my attention as a CPO: there’s already a Product Management skill plugin on Claude. It covers writing specs from a problem statement, synthesizing user research, generating stakeholder updates, running competitive analysis. On GitHub, people are building entire PM skills repos with PRD generation, backlog creation from a single brief, and sprint planning workflows. One skill generated 42 user stories with acceptance criteria from a single PRD in 10 minutes. This is the beginning of something real for product people. Not because AI will replace PM thinking. But because the repetitive parts of our work — structuring specs, formatting updates, translating decisions into dev tasks — can now be packaged once and run on demand. The PM who builds the best workflows will ship faster than the PM who writes the best prompts. Product quality and velocity are almost always a direct reflection of how the product team is organized. The best process, the right rituals, the shared standards — that’s what compounds. Skills won’t solve all of this overnight. But they’re the first real infrastructure for packaging PM expertise into something an AI agent can execute consistently. Models improve every few months. Workflows you build on top of them compound over time.

Two years back, I spent 3 hours fixing a report I’ve built 20 times before and i do it even on weekends It hit me: Why am I still doing this manually? That’s when I decided to automate it — and now, what took 3 hours takes less than 3 minutes. Here’s the truth about automation: It’s not always about reaching zero manual effort. It’s about reducing the time, stress, and repetition that eat up your day. And there’s more than one way to automate your work. Let me show you 5 powerful approaches: 1. Excel + Power Query / Macros Example: Pull monthly sales data from multiple CSVs, clean it, and update your dashboard — all with one click. 2. Python Scripting Example: Scrape competitor pricing data daily, clean it, and email a summary to your team automatically. 3. Zapier / Make.com (No-Code Tools) Example: New lead in Google Forms? Instantly add it to your CRM, alert your team on Slack, and send a thank-you email. 4. SQL Scheduled Jobs Example: Run a daily revenue summary at 6 AM and send it to finance before they ask for it. 5. Task Scheduling (Cron Jobs / Task Scheduler) Example: Automatically back up files or trigger Python scripts every night. Start small. Automate one pain point. Even if you save 15 minutes a day — that’s 90 hours a year. I’ll be sharing weekly posts on automation tips using Excel, Python, and no-code tools. Follow if you want to work smarter — not harder.

In almost every data and AI strategy I’ve led, the hardest problem was never the technology. It was the people who didn’t want it. Every organisation has them and I often label them as "detractors". They aren't villains and certainly aren't incompetent. In fact, they are often experienced operators who understand how the place really works. Treat them as obstacles and they will become one. Treat them as stakeholders and they frequently become your strongest allies. Well, that's the idea! Over time I’ve noticed recognisable patterns: The Historian: “We tried this before. It failed.” They are not blocking you; they are protecting the organisation from repeating a mistake. #Strategy: ask them to explain the failure in detail and incorporate one of their lessons into the plan. Respect converts memory into advocacy. The Territorialist: Quietly concerned about loss of authority, budget, or influence.#Strategy: give them ownership of a visible component. People rarely undermine a system that carries their name. The Perfectionist: Endless questions, dismantles every slide. #Strategy: make them part of the design review. Channel criticism into quality assurance and you gain a risk manager for free. The Detached Expert: Supportive in principle, never available in practice. #Strategy: don’t schedule meetings. Ask for a single judgement call. Experts respond to being needed, not invited. The Sceptic: Believes the programme is another management fad. #Strategy: don’t sell vision, deliver a small operational win. Evidence persuades faster than enthusiasm. The mistake people tend to make is to try and remove this friction. But friction is information, because detractors often understand operational reality better than the project team. The strategy that survives them is the one that survives the business. Practical tactics: 👉Share early drafts, not polished decks 👉Ask for criticism before approval 👉Credit them publicly when they improve the plan 👉Involve them in value efforts, not just governance 👉Never surprise them in steering committees Most resistance comes from exclusion, not disagreement. What if they still won’t come to the table? Change the table. Implement a small improvement in their area. Remove a daily pain point. Let results introduce the strategy for you. Nothing converts a critic faster than discovering the new process improved their Monday morning. Of course they may still refuse to come to the table. At that point it is no longer a strategy issue, it is leadership alignment. An operating model cannot be optional. - Supporters help you launch. - Detractors help you succeed. Bring them closer. Many future champions are simply cautious professionals wearing protective armour. Are detractors actually a problem or a signal your strategy hasn’t met reality yet?

𝗜𝗳 𝘆𝗼𝘂’𝗿𝗲 𝗱𝗼𝗶𝗻𝗴 𝘀𝗼𝗺𝗲𝘁𝗵𝗶𝗻𝗴 𝗺𝗼𝗿𝗲 𝘁𝗵𝗮𝗻 𝘁𝗵𝗿𝗲𝗲 𝘁𝗶𝗺𝗲𝘀, 𝗼𝗿 𝗶𝘁 𝘁𝗮𝗸𝗲𝘀 𝗺𝗼𝗿𝗲 𝘁𝗵𝗮𝗻 𝘁𝘄𝗼 𝗵𝗼𝘂𝗿𝘀 — 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗲 𝗶𝘁. That’s the mantra we’ve adopted for product managers at Databricks. ⚙️ 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗲 𝗬𝗼𝘂𝗿𝘀𝗲𝗹𝗳: 𝗛𝗼𝘄 𝗣𝗠𝘀 𝟭𝟬× 𝗧𝗵𝗲𝗶𝗿 𝗣𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝘃𝗶𝘁𝘆 Product managers have always been system thinkers. We design not only products, but also the processes that bring them to life — how we discover, synthesize, and act on truth. At Databricks, we’ve built strong systems for 𝗵𝘆𝗽𝗼𝘁𝗵𝗲𝘀𝗶𝘀-𝗱𝗿𝗶𝘃𝗲𝗻 𝗱𝗶𝘀𝗰𝗼𝘃𝗲𝗿𝘆 and 𝗳𝗶𝗿𝘀𝘁-𝗽𝗿𝗶𝗻𝗰𝗶𝗽𝗹𝗲𝘀 𝘁𝗵𝗶𝗻𝗸𝗶𝗻𝗴. But there’s another layer of the job that can be surprisingly time-consuming: • Coordinating customer outreach for discovery • Polishing and sharing customer notes • Synthesizing insights into reports • Filing bugs from interviews • Tracking growth and churn • Sending weekly business updates • The day-to-day operations of running the business behind the product. Since our Vibe Coding Bootcamp, PMs across Databricks have started using Claude Code and Cursor to automate these tasks — to literally 10× themselves. Here are two of my favorite examples 👇 1️⃣ 𝗖𝘂𝘀𝘁𝗼𝗺𝗲𝗿 𝗖𝗮𝗹𝗹 “𝗢𝗦” PMs used to spend 7–10 hours a week tracking growth and churn, emailing account teams, collecting notes, and writing reports. Now, with vibe-coded automations, PMs have built systems that: • Runs SQL queries to surface top growth/churn accounts • Emails account teams automatically with personalized summaries and charts • Rewrites customer notes in a consistent format • Consolidates bi-weekly reports (all with human review before send-off) • ⏱ Result: 1.5 hours of effort per week instead of 10+. 2️⃣ 𝗨𝘀𝗲𝗿 𝗝𝗼𝘂𝗿𝗻𝗲𝘆 𝗔𝘂𝗱𝗶𝘁𝘀 & 𝗕𝘂𝗴 𝗕𝗮𝘀𝗵𝗲𝘀 PMs built vibe-coded Playwright scripts to simulate users completing tasks with our docs. • These automations flag broken steps, missing links, and confusing flows — even propose doc fixes automatically. • ⏱ Result: We can now measure how easy (or painful) our UX/docs really are, continuously. The results go beyond efficiency. By automating the repetitive work, PMs spend more time thinking strategically — and, interestingly, they’re generating better insights too. At Databricks, PMs don’t just manage products...they design the systems (and now, the automations!) that make building them possible. Would love to hear how others are using AI to automate the operational side of product management!