TLDR Product Management 2026-05-29

Product teams are shipping AI-powered features faster than ever. But how do you experiment, release, and optimize AI experiences without increasing risk?At Flagship: The Feature Management and Experimentation Summit hosted by Harness, leaders from Cursor, Box, United Airlines, JPMC, and more will share how modern product and engineering teams are adapting feature delivery for the AI era, including how to:

✅Release AI-powered features with confidence

✅Experiment safely before changes impact customers

✅Scale rollout strategies without sacrificing control

Featuring sessions on feature flags, experimentation, and AI-driven product delivery.Join live on June 17 (10:00 AM PT / CET)Register now >

PMs are not “dying” but changing in scope depending on the organization. This article shares a framework for PMs' past, present, and future across several areas, with special emphasis on how AI and AGI pressure will reshape responsibilities.

AI tools are changing product development workflows. New approaches move teams from early ideas to building and production, showing what changes across the product lifecycle.

AI products often lose users not because the model is weak, but because adoption design decisions are missing or wrong. There are four common failure modes: activation cliffs, a trust gap, broken correction loops, and an agent autonomy ceiling.

Anthropic and OpenAI have achieved PMF for enterprise coding/general-purpose agent tools. The shift is driven by real enterprise demand for products like Claude Code/Cowork and Codex, despite thin “AI cost failure” anecdotes.

Tired of babysitting agents? With OpenProse, you define your outcome ("Inbox at zero by 5pm") - the runtime executes, watches for drift, and pings you when it's done. Write your goal once in plain English, let the system keeps it true. To start, simply open terminal and type npx skills add openprose/prose

User segmentation gets more design buy-in than relying on personas alone. Personas often get dismissed, and there are four segmentation elements to reinforce personas: total audience size, time period/seasonality, device/tech context, and new vs. returning customer.

To achieve a big long-term goal, teams must “sell Point C”- a concrete, vivid next destination they will reach in the next 12–24 months - rather than settling for “continue existing.” This should be a strategic, fundable milestone aligned with mission, vision, strategy, and anchored in the needs of the community the team serves.

Slack evolved its AI infrastructure from self-managed AWS SageMaker to managed Amazon Bedrock to solve scaling and latency issues. By moving to Bedrock, Slack reduced engineering overhead and improved efficiency through Provisioned Throughput and on-demand capacity.

AI labs will own many horizontal AI tools, but startups can still win in complex vertical workflows. The strongest AI app companies will own the system of work, including customer data, governance, integrations, and measurable business outcomes.

Product leaders shouldn't outsource customer thinking to LLMs.

At senior levels, promotions depend on more than your manager's support.