The scariest thing about AI in PM isn't that it replaces you.
It's that it gives your team false confidence.
A working prototype feels like progress. But if nobody validated the problem, you just built a beautiful solution to nothing.
#ProductManagement #AI
2025 PM: "I need eng to build a prototype"
2026 PM: "I built the prototype last night in Claude Code. Here's the demo."
The PM who can show > tell will always move faster.
Technical literacy isn't optional anymore.
#ProductManagement #AI
How to work smart as a PM:
1. Kill projects that aren't moving the needle
2. Deliver the smallest feature that still creates value
3. Pre-align stakeholders before the big meeting
4. Keep a decision log so you never re-debate
Simple. Hard to do consistently.
#ProductManagement
PM productivity hack nobody talks about:
Use speech-to-text to draft your first version of everything emails, PRDs, strategy docs.
You think faster than you type. Let your voice lead, then edit.
#ProductManagement
Occam's Razor for AI features:
If a dropdown menu solves the problem, don't build a conversational AI interface.
The simplest solution that works is still the best solution.
Not every problem needs a model behind it 👀
#AI #ProductManagement
When observing users, don't ask what they want.
Watch what they do.
Screen shares > surveys
Workarounds > feature requests
Confusion > complaints
What users struggle to articulate is usually more valuable than what they say.
#ProductManagement
The Lindy Effect applied to AI tools:
The PM skills that survived every past hype cycle, user empathy, stakeholder alignment, and problem framing, will outlast this one too.
Learn the new tools. But bet your career on the old skills.
#AI #ProductManagement
I was not comfortable with speech-to-text before , but now I have slowly started using it.
How do you use speech-to-text? Any best practices?
#ProductManagement #AI
The Automation Paradox of AI in PM:
The more AI automates routine decisions, the harder the remaining decisions become.
AI handles the easy 80%. You're left with the ambiguous 20% that actually matters.
That's not less work, PM work gets harder
#AI #ProductManagement
Old PM: writes detailed PRD → hands to eng → waits 3 weeks
New PM: prototypes with real data in Claude → shows eng a working demo → ships in days
Cut TTM from weeks to days with this shift.
#ProductManagement #AI
Atlassian CEO breaks down the 3 types of SaaS in the AI era
1️⃣ Work-Tied Seats: High risk. If AI agents do the work, do you still need the seats?
2️⃣ System of Record: Safer. Pricing is not tied to output
3️⃣ The Middle Ground: Hybrid - balances creative work with tools
www.youtube.com/watch?v=0lzo...
"AI makes building cheap" is the most dangerous sentence in product.
Cheap to build ≠ worth building.
You can now create the wrong thing faster than ever.
Validation didn't get cheaper. It got more important.
#ProductManagement #AI
Decision log template that actually gets used:
1. What we decided
2. What alternatives did we considered
3. Why we chose this
Three lines. That's it.
6 months from now, nobody will remember the "why" unless you wrote it down.
#ProductManagement
Domino's didn't add GPS delivery because customers asked for it.
They noticed delivery notes kept saying "meet me at the beach" and "I'm in the park."
The best feature ideas hide in workarounds your users already invented.
#ProductManagement
Real question: Are you using AI to think better, or to avoid thinking?
If you can't write a clear problem statement without ChatGPT, that's not efficiency.
That's atrophy.
#ProductManagement #AI
The blank AI chat box is bad UX.
We spent decades perfecting form design, search patterns, and guided workflows.
Then AI shipped and said, "Just type anything" 🤣
No wonder people don't know what to do with it.
#AI #ProductManagement
Synthetic data is a PM superpower nobody talks about.
Use AI to generate test scenarios for edge cases, permission rules, and data APIs.
You don't need production data to validate your product logic.
#ProductManagement #AI
Pre-mortem > Post-mortem.
Before you build, ask your Eng and QA team: "If this feature fails, why did it fail?"
You'll catch integration gaps, edge cases, and wrong assumptions before they cost you a sprint.
#ProductManagement
70-75% AI-generated code is the new normal for MVPs.
The question isn't "is that too much?"
The question is, "Do you have someone who can tell good AI code from bad AI code?"
That's where the real risk lives.
#AI #ProductManagement
Stop planning your deliverables. Start planning your outcomes.
#ProductManagement
Built a personal PRM as an OpenClaw skill.
This one maps relationships as a graph, Obsidian-native, with weekly "who are you neglecting?" digests
Full write-up + open source skill.
Give it a try
gobiraj.substack.com...
#AI
In volatile markets, the winner is often the team that learns fastest, not the team that looks most polished.
#AI
Your strategy doc is more valuable for the thinking it forces than the document it produces.
#ProductManagement
I would say it is not binary but somewhere in the middle.AI won’t replace engineers, but it absolutely compresses execution cost. That changes team size, leverage, and expectations. There is a shift coming
Execution clarity is an underrated PM skill.
Especially now, when half your team is quietly anxious about AI replacing them.
You don't need a grand AI strategy.
You need to help each person on your team answer: "What does this mean for my work, this week?"
Before you build your roadmap, answer these first:
1️⃣ Who is your ICP?
2️⃣ What core problem are you solving?
3️⃣ What's your positioning?
Without these, your roadmap is just a wish list with dates.
#ProductManagement
The burning platform now isn't 'adopting AI.'
It's designing organizations that convert AI capability into reliable business outcomes.
That's the actual hard part nobody's solving.
#AI
AI Reality: Best users can also be the most expensive users.
#AI
You are right, not all use cases need an always-on agent. An agent on a recurring schedule should suffice
The hardest shift when building AI-native products isn't technical.
It's mental: going from SaaS-user mindset to infrastructure-operator mindset.
Flat-rate subscriptions weren't built for agents.
#AI
