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If you use AI for competitor research, steal this rule. Every claim gets a date. Last week Claude answered a simple question about Linear’s competitors using an old source as if it were recent. It also stated a guess as fact. The skill forced the answer to show the dates,

Founders are doing product marketing earlier than they think. It usually shows up when a buyer says something you weren’t expecting. That gap between how you describe the product and how buyers see it can change the story you tell and what gets built next. If you’re a founder

The first thing I want from AI doing product marketing is the ability to say "I don’t know." If it can’t verify a competitor change, that uncertainty belongs in the answer. If a recommendation needs evidence it doesn’t have, the system should stop there. Friday at 10 AM PT I’m

If a customer conversation has ever changed how you explain the product, you’ve already done product marketing. Friday at 10 AM PT I’m taking one B2B product through 16 jobs like that with AI. I’ll run the same work with and without the matching skill and see which version I’d

AI makes bad product marketing look finished. That’s the part I don’t trust. A competitive brief can sound current while leaning on an old source. Positioning can sound sharp even when the logic underneath is a guess. A battlecard can look complete and still fail the rep who

If you work on a B2B product, product marketing is probably already part of your job whether or not it’s in your title. It shows up when something you learn from the market changes how the product gets explained or sends the team back into the product. Friday at 10 AM PT I’m

Founders are doing product marketing earlier than they think. The market starts teaching you how buyers see the product almost immediately. What they compare it to affects the story you tell. Objections and lost deals often expose something deeper about the product itself. That

Linear CEO @karrisaarinen: "I took a break this summer from paying attention to AI. I thought that when I came back, I'd feel left behind. But when I came back, I realized that nothing has really changed. There's new models, there's new techniques, there's new agents. But in the

ON TOUGH TIMES AT WORK People are different, and different people need different things to get them through tough times at work — times when work is stressful, or you’re dealing with annoying politics, or just when the motivation tank is running low. For some, it’s energizing

We asked Claude what changed with Linear’s competitors. The first answer used an old source as if it were recent. It also stated a guess as fact. Then we gave the same model our competitive skills. It showed its limits up front. It explained how it ranked the changes and kept

Trend I'm following: Teams using AI "simulations" to quickly test product ideas and flow tweaks. Products like @simile_ai, @primitivelabsai, @syntheticusers, and others. If you've tried something like this, how'd it go?

🎙️Recorded Conversations We now record almost everything — every meeting has an AI note-taker, and some people wear glasses that capture every word. So what does that do to our relationships when nothing is forgotten and everything can be fact-checked? Petra Wille and Teresa Torres explore the…

We asked Claude what changed among Linear's competitors. No skills: an old source treated as recent, and a guess stated as fact. Same model, with our competitive skills installed: every claim dated, the ranking marked as its own view, and a line about what it could not see.

.@thsottiaux (Head of ChatGPT & Codex) on the skills trending up and down in the AI era. Trending up: great taste, passion to build something that matters, knowing what good looks like. Trending down: typing fast.

The most important idea that most product people forget somewhere along the way: Everything you do with your product originates in your thinking, so the best (and really the only) path to consistently build successful products is to greatly improve the quality of your thinking.

This happens to smart people because of: 1. Deep-rooted identity of “I am good at product” (vs. “I am good at winning” or something like that) 2. Moral aversion against marketing & distribution 3. A habit of seeking virtue points by proclaiming “I just want to serve my users”

"Having to set up and fiddle with your loops… I don't think this is the way that it's going to work." @thsottiaux (Head of ChatGPT & Codex) says we are heading towards Dots being the primary way you talk to AI. Full conversation:

My biggest takeaways from @thsottiaux: 1. Most actions on the internet will soon be taken by agents, and Tibo doesn’t think most people have priced this in yet. When Notion launched its MCP server, it saw a flood of traffic, which strained its systems and forced it to rethink its economics. Every…

Product management is laced with one stubborn bias: we overvalue our own ideas about what to build next. Steve (Vistaly) says minds rarely change until teams hear customers describe the problem in their own words. That's why Vistaly puts interview evidence directly on the opportunity solution…

My conversation with Head of ChatGPT and Codex, @thsottiaux We discuss: 🔸 Why the model picker is likely going away 🔸 Why loops and graphs are a passing phase 🔸 Why most actions on the internet will soon be taken by agents 🔸 OpenAI’s approach to AI safety Listen now 👇

Inspired by Git diff, Teresa Torres started simple: compare the input tree to the output tree and generate a change set. Then she learned the same pair of trees can produce multiple change sets—and only one tells the real story. A semantic merge means something very different from a delete plus…

Most mid-career product people who are doing reasonably well make 2 implicit assumptions that affect their quality of life: 1. the ceiling of key product skills is just an inch higher than where they are now (i.e. they’re basically already at the ceiling) 2. the point of any upskilling is to get a…

From coaching 100s of people over the years on career decisions, LinkedIn Envy and the Impact Lie are the root cause of many career regrets of otherwise-smart people. How to avoid such regrets? As with many such situations, the knowledge is the cure:

This is also true in tech careers. A lot of people I speak with are successful by every conventional metric, but they find it difficult to decide what to do next, in their career and their life.

Teresa Torres wants to believe every product team does careful synthesis after each customer interview. The reality? It's hard, so teams give up and grab the two or three things they remember most. "We're not competing with making good synthesis faster. We're competing with making shallow synthesis…

What happens when you hand your opportunity solution tree to an AI? Vistaly rebuilt its entire product to find out—and the agents were the easy part. In this episode of Just Now Possible, Teresa Torres talks with Matt O'Connell (Co-Founder and CEO), CP Dehli (Co-Founder), and Steve Klein…