Methodology: Every two weeks we collect most relevant posts on LinkedIn for selected topics and create an overall summary only based on these posts. If you´re interested in the single posts behind, you can find them here: https://linktr.ee/thomasallgeyer. Have a great read!
If you prefer listening, check out our podcast summarizing the most relevant insights from Digital Products & Services CW 04/ 05:
AI in Product
AI is framed as a force multiplier for learning cycles, not a standalone feature race
New skills cluster around agents, experience architecture, and functional prototyping rather than generic AI buzzwords
Decision rights and guardrails are highlighted as essential to avoid AI driven centralization of power and risk
Automation of lower-level tasks shifts product roles toward judgment, abstraction, and system thinking
Discovery & Experiments
Discovery is treated as an always on discipline that links user insight directly to outcomes
Early decisions are identified as the main risk point, reinforcing lean, experiment led approaches
Strategy, OKRs, and discovery are positioned as one integrated system for evidence-based prioritization
Frameworks such as Lean Product Development and Toggle Method are used to diagnose and correct weak strategies
Product Operating Models
Operating models are expected to be designed from strategy, not copied from reference companies
Product Ops maturity is described as a journey from tooling and reporting toward real team empowerment
Many organizations struggle to leave project mode because decision systems remain approval heavy and slow
Clear product models and ownership mechanisms such as on call drive scalable, sustainable product delivery
Leadership & Mindset
Product failure is often traced back to weak mission clarity, feedback, and expectation management
Leaders are urged to build structured feedback loops that keep teams focused on measurable outcomes
Healthy teams require a shift from individual heroics toward shared responsibility and empowerment
AI is seen as an amplifier of leadership quality, exposing poor prioritization faster than before
Product Communication
Executive storytelling and strong metaphors are positioned as critical for landing complex product choices
Product sense and product taste are separated, guiding what to build and how it should feel
Communication quality is treated as a core part of the product system, not a cosmetic afterthought
Presentations, updates, and feedback mechanisms are framed as levers that influence decisions like roadmaps do
Learning & Ecosystem
Curated ML and AI product resources signal a push toward more structured learning in the craft
Experimentation playbooks position tests and systems thinking as foundational for sustainable growth
Case studies from major players are used to extract principles instead of encouraging blind model copying
Community events and meetups anchor operating model discussions in peer practice, not just theory
Overall Signal
Focus is shifting from isolated features toward the operating system of product work across AI, discovery, and decisions
AI is treated as a pervasive capability that tests the quality of strategy and operating models
Investment in discovery discipline, product ops, and leadership habits is put on par with investment in technology stacks
The field moves toward clearer roles, explicit models, and more experimental ways of working across Digital Products and Services
Want to see the posts voices behind this summary?
This week’s roundup (CW 04/ 05) brings you the Best of Digital Products & Services Insights:
→ 62 handpicked posts that cut through the noise
→ 30 fresh voices worth following
→ 1 deep dive you don’t want to miss