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SKIP THE TOOLS, MAKE THE OUTCOMES

In the age of AI, software design should shift from prioritizing intermediate tools to delivering direct outcomes and immediate answers.

AVOIDING THE AGENTIC DEATH SPIRAL IN B2B SOFTWARE PRICING

Pre-AI B2B software vendors raising prices for agent and API access risk triggering an "agentic death spiral," where users bypass platforms to avoid fees and ultimately weaken product stickiness and moats.

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CARING VS. KNOWING

While AI lowers software development costs, supporting a growing audience demands continuous learning and quality standards. Developers face challenges in managing user diversity and the risks of unchecked customization. Ultimately, maintaining quality requires an ongoing commitment.

THE STAKEHOLDER WHO MATTERS MOST

The industry overlooks the primary stakeholder: the user. Current evaluation metrics measure machine functionality rather than whether an agent actually reduces effort for humans. Consequently, companies fail to instrument the complete customer journey, leading to hidden inference costs and unmeasured user abandonment.

‘NOT ENOUGH USAGE': YOUR BIGGEST CHURN REASON IS A BROKEN HABIT LOOP

"Not enough usage" is the primary driver of subscription app churn, often accounting for 26% to 40% of cancellations. This churn reason is frequently due to a broken habit loop rather than a pricing problem. Using discounts to fix usage churn is ineffective because lowering the price does not restore user value or engagement.

NOT EVERY QUESTION DESERVES A STUDY

Every research question should be assigned a specific price in minutes, days, or an owned risk before any investigation begins. By implementing a five-step routing discipline, product teams can determine whether an answer already exists in organizational memory, warrants a rapid study, or should be bypassed entirely with an accepted risk written down.

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DESIGNING AI PRODUCTS AND FEATURES: STUDY GUIDE

The guide highlights key strategies for defining value propositions, crafting prompt assistance, and optimizing feature design to deliver meaningful user experiences.

HOW ZAPIER'S CEO GRADES PMS ON AI FLUENCY (74 MINUTE VIDEO)

Wade Chambers discusses the company's updated AI fluency rubric, outlining expectations for PMs across capable, adaptive, and transformative levels. Zapier expects PMs to operate primarily in the adaptive tier while running occasional experiments or building transformative systems, such as company-wide AI agent frameworks.

PRODUCT MANAGER, APPLIED AI AT TLDR ($200K BASE + $60K BONUS, FULLY REMOTE)

TLDR is hiring its first PM to help build the agent-first operating layer used across the company. We're looking for a builder who has shipped real products/systems with LLMs. Click here to learn more [13].

THE PROBLEM WITH PUTTING PEOPLE IN BOXES

Personality labels can hide how much behavior depends on context. Understanding what causes people to switch modes may tell you more than knowing their “type.”

AI ON TOP OF A DYSFUNCTIONAL SYSTEM (1): THE PRODUCT BACKLOG

Applying generative AI to a dysfunctional product backlog masks underlying flaws by polishing artifacts without resolving root causes like missing customer evidence or decision authority. AI-generated user stories obscure a lack of real product discovery. To remain effective, product teams must maintain clear direction, authentic authority, and feedback loops tied to real outcomes.

EXTRACTING PRODUCT DESIGN DECISIONS AND DOMAIN MODELS USING AI BROWSER TOOLS

Tools like Codex Browser Use and the Claude Chrome Extension excel at extracting design and product decisions from existing products.

HOW TO WRITE AN OUTCOME-BASED OKR WHEN YOUR USER IS AN AI AGENT

Writing outcome-based OKRs for AI agent products requires measuring human behavior rather than agent activity.

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MOATS & THE BARBELL-IFICATION OF SOFTWARE

AI is weakening traditional software moats and squeezing the middle. Software may split between massive platforms and small niche products.

POPULAR ISN'T A BUSINESS MODEL

Open source can drive adoption, but it does not create a business by itself. Companies need to identify what becomes valuable enough for users to pay for.

CONNECTING PRODUCT OUTCOMES TO BUSINESS STRATEGY

Product outcomes should connect directly to business strategy through a clear hierarchy of goals. The Strategy Stack keeps product teams autonomous while aligned with company priorities.

HOW SHOULD WE APPROACH THE SOFTWARE FACTORY AS A PRODUCT TEAM?

AI software factories should encode human judgment into automated feedback, not just produce more code. Teams should learn through real product work and continuously improve how their agents operate.

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NOBODY NEEDS A HUMAN ROUTER

Engineering managers should stop being information routers and use AI to get back into the technical work. Staying close to code, architecture, and critical projects helps them make faster, better decisions.

4 NEW EVALS AND 16 EXPERIMENT VARIANTS TO FIX 1 CUSTOMER COMPLAINT

Reliable AI products need more than better prompts or models. Teams need evals, guardrails, and orchestration to catch errors and help agents correct them.

MOMENTUM IS NOT A MOAT

Momentum drives growth, but it is not a moat. AI startups need to turn early traction into durable advantages competitors cannot easily copy.

COACHING SOMEONE THROUGH THE BURNOUT THAT REST DOESN'T FIX

Some burnout comes from feeling disconnected from who you want to be at work, not simply from overwork. Managers can help identify that gap and restore a sense of agency.

THE WORKAROUND IS OFTEN THE REQUIREMENT

Workarounds often reveal product needs users no longer think to mention.

WHAT DECIDES WHICH TASKS PRODUCT MANAGERS ARE WILLING TO DELEGATE TO GENAI?

AI adoption works best when teams start there and keep human ownership clear.

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STRONG OPINIONS, LOOSELY HELD

AI makes building cheaper, not product judgment easier. Strategy, customer understanding, and independent thinking matter more than ever.

CRACKS IN THE AI THESIS PART 2

Anthropic extended its lead in business AI adoption, though overall growth slowed and spending by top users dropped nearly 10% in August. Falling token prices and a shift to cheaper models are cutting costs, while open-source and Chinese models account for little corporate usage.

DON'T LET AI AUTOMATE THE MESS OUT OF PRODUCT DEVELOPMENT

Don't automate away productive friction. Use AI for routine work, but keep humans in the conversations where judgment and alignment happen.

PRODUCT MANAGEMENT IS STILL ALL ABOUT TELLING STORIES

AI makes building cheap, but judgment still defines great products. The PM's job is to choose what matters and tell a story users understand.

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THE PRODUCT PROCESS THAT SAVED US WEEKS OF WASTED DEVELOPMENT

Catch bad product architecture before you build it. Validate early, and let the structure of the problem shape the solution.

CONGRATS, YOUR SALES PROBLEMS IN PLG ARE COMPLETELY UNORIGINAL

Don't kill PLG to grow enterprise. Let product adoption create enterprise demand, then use sales when customers actually need it.

CATCHING THE (VENTURE) BUS

Tech's biggest winners are increasingly built in private markets. Traditional venture allocations may be too small, but access to the best funds matters more than broad exposure.

HOW TO FIND MEANING IN LIFE

Meaning comes from commitment, not endless options. Invest deeply in people, purpose, and work that matters beyond yourself.

DISTINGUISHING DECISIONS FROM ASSUMPTIONS

AI can make assumptions look like decisions.

WHY SPOTIFY STILL USES FREQUENTIST A/B TESTING

Bayesian A/B testing is only as useful as its priors.

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THE COMING PRODUCT RETENTION CRISIS

AI excels at routine work but struggles to hold consumer attention, which depends on novelty and authenticity. As apps become cheaper to build, they will resemble disposable content, shifting success from retaining users to producing fresh hits and building lasting brands.

HOW TO GIVE AWAY FREE PRODUCT AND MAKE MONEY DOING IT

Free AI access can attract paying customers more efficiently than traditional ads by allowing users to experience a product's value firsthand. Lovable treats free offerings as customer acquisition costs, targeting a three-month payback period while implementing eligibility rules and fraud controls to mitigate abuse.