Proton Launches Proton Meet With A Privacy Feature That Beats Its Rivals

In Today’s edition:

1. Proton Just Took a Shot at Zoom and co. With Proton Meet Launch

2. EXCLUSIVE RESOURCE FROM ATAI 2026

3. PMNA TUTORIAL: How to Create a Smart Sprint Retrospective Generator Using Make.com

4. UPCOMING EVENT: Automating Your Business with AI and Make.com

5. Asana Says AI Should Work Like a Team Not a Tool

6. TOOL REVIEW: ProductBridge Transforms Customer Feedback Into Clear Product Decisions

7. Exciting Career Opportunities for Product and Project Management Professionals

Reading time: 5 minutes

HEADLINE NEWS

Proton Just Took a Shot at Zoom and co. With Proton Meet Launch

Proton has launched a new video conferencing tool called Proton Meet, positioning it as a privacy-first alternative to mainstream platforms like Zoom. The service emphasizes end-to-end encryption, no data logging, and even allows users to join calls without creating an account. This move completes Proton’s broader ecosystem, aiming to rival big tech productivity suites with a privacy-centric approach.

• Proton Meet offers end-to-end encryption by default, meaning even Proton cannot access calls or messages.

• Users can host or join meetings without an account, unlike competitors that require sign-ups.

• Free users can host calls with up to 50 participants (or 4 without an account).

• The platform uses the open-source Messaging Layer Security (MLS) protocol for secure communication.

• Proton Meet integrates with calendars and completes Proton’s full privacy-focused alternative to Google Workspace and Microsoft 365.

Proton Meet reflects a growing push against big tech data practices, especially concerns around AI training on user conversations. By building privacy into the core of its ecosystem, Proton is positioning itself as a serious alternative for users who prioritize security over feature depth. While the platform may still lack some polish compared to established tools, it represents a significant shift toward privacy-first digital collaboration. Read More

We are giving out this exclusive resource from the ATAI Conference 2026

At All Things AI 2026, Jordan Van Maanen delivered a high-impact workshop on eliminating operational bottlenecks using automation. The session went beyond theory, showing how teams can use Make.com to turn repetitive, manual workflows into efficient, scalable systems. More importantly, it challenged attendees to stop observing AI… and start building with it.

At the end of the workshop, attendees were given a set of practical resources... and now, you have access to them too:

👉 Govincorp Value First Framework
→ Shows you how to prioritize automation opportunities based on actual business impact, so you don’t waste time automating the wrong things
👉 Govincorp Process Friction Audit
 → Helps you pinpoint the exact tasks slowing you down, making it easier to identify high-leverage automation wins
👉 Builder’s Lab Worksheet Handout
 → Guides you step-by-step in mapping out and building your own automation, turning ideas into something tangible

These resources are the bridge between understanding automation and actually applying it so you can start reclaiming your time immediately.

PMNA TUTORIAL: How to Create a Smart Sprint Retrospective Generator Using Make.com

Sprint retrospectives are essential for improving team performance, but they’re often based on memory and subjective opinions rather than real data. This makes it difficult to identify true patterns, blockers, and opportunities for improvement. By using Make.com and AI, you can automate the entire retrospective process—pulling sprint data, analyzing it, and generating structured insights before the meeting even begins.

You’ll learn to:

• Define a clear retrospective framework and key metrics

• Create a centralized database for storing retrospectives

• Set up a Make.com scenario triggered at the end of each sprint

• Pull sprint data from tools like Jira, ClickUp, or Asana

• Categorize tasks into completed, spillover, and bugs

• Calculate performance metrics like completion rate and velocity

• Aggregate data for analysis

• Use AI to generate retrospective insights and action items

• Store the generated report in Notion or Google Docs

• Notify the team with a ready-to-review retrospective

Why it matters:

Automating sprint retrospectives transforms them from subjective discussions into data-driven improvement sessions. Teams gain clearer insights, reduce preparation time, and consistently identify meaningful actions to improve performance. For product and project managers, this system ensures every sprint leads to measurable learning and continuous progress.

FULL TUTORIAL HERE

UPCOMING EVENT: Automating Your Business with AI and Make.com

The upcoming webinar is a hands-on session aimed at showing businesses how to leverage AI to improve workflows and operational efficiency. Participants will learn practical ways to use Make.com alongside AI to automate repetitive tasks, connect different systems, and accelerate decision-making. The focus is on real-world applications, making it ideal for professionals who want actionable automation strategies.

Event Details:

• Speakers: Ricardo Govindasamy (lead presenter) and Mark Hinkle

• Date & Time: Tuesday, April 14, 2026, at 12:00 PM Eastern Time (5:00 PM WAT)

• Location: Online, hosted via WebinarJam

• Event Topic: Combining AI and Make.com to create automated workflows that reduce manual effort and streamline business processes

• Highlights: Practical AI use cases, workflow design strategies, tool integrations, decision support, and operational efficiency techniques

Why it matters:

This webinar is particularly relevant for anyone looking to transform AI into practical business value. By attending, participants will gain insights on identifying automation opportunities, designing workflows that deliver results, and avoiding common mistakes in AI-driven processes. It’s a valuable session for builders, operators, and automation enthusiasts seeking to improve efficiency and scale operations effectively.

REGISTER HERE

Asana Says AI Should Work Like a Team Not a Tool

Asana is rethinking how AI agents should function in the workplace, arguing they must be built for collaboration rather than isolated productivity. According to its Chief Product Officer, the future of enterprise AI lies in “multiplayer” systems where agents work alongside multiple humans and other agents. This approach challenges the typical “copilot” model by emphasizing coordination, shared context, and teamwork.

• Asana believes AI agents should be “multiplayer by design,” collaborating with teams instead of serving just one user.

• The company launched AI Teammates—agents that can autonomously complete tasks within workflows.

• Users can create custom agents or choose from prebuilt ones tailored to roles like marketing, IT, and operations.

• Unlike traditional copilots, these agents operate with shared context across teams, improving coordination and execution.

• Asana sees its core data layer (“work graph”) as critical infrastructure for enabling multi-agent collaboration.

As AI adoption grows, the challenge is shifting from individual productivity gains to managing complex collaboration between humans and multiple AI agents. Asana’s “multiplayer” vision positions it as a coordination layer in this evolving ecosystem. If successful, this model could redefine how enterprises deploy AI—moving from tools that assist individuals to systems that orchestrate entire teams. Read More

TOOL REVIEW: ProductBridge Transforms Customer Feedback Into Clear Product Decisions

ProductBridge is an AI-powered feedback management platform built to help product teams collect, organize, and act on user feedback at scale. It transforms scattered input from multiple channels into structured insights, enabling teams to prioritize what truly matters. The platform ultimately bridges the gap between user feedback and product decisions by automating the entire feedback-to-roadmap workflow.

Key Features

• Centralized Feedback Collection: Aggregates feedback from widgets, portals, and integrations into a single, organized hub.

• AI-Powered Organization (AutoBridge): Automatically categorizes, deduplicates, and analyzes feedback to surface meaningful patterns.

• Data-Driven Prioritization: Highlights high-impact feature requests based on user demand and frequency.

• Roadmap Integration: Converts feedback directly into trackable product initiatives with customizable workflow stages.

• Automated Feedback Loop Closure: Notifies users when their requested features are planned, in progress, or shipped.

For project managers, ProductBridge eliminates one of the biggest inefficiencies in product development: unclear priorities driven by scattered or subjective feedback. By turning raw user input into structured, AI-analyzed insights, it enables faster, more confident decision-making while aligning teams around real user needs. In a world where building the wrong feature is costly, ProductBridge provides a systemized way to ensure every roadmap decision is backed by actual demand.

TOOL LINK

Exciting Career Opportunities for Product and Project Management Professionals

• Facility Capital Projects Lead @ Siemens

  📍 Raleigh, NC.

• Product Owner @ PENNYMAC

  📍 Cary, NC.

• Project Manager @ Markon Solutions

  📍 Hertford, NC.

• Portal Product Owner - Life and Annuity Business Unit @ Accenture

  📍 Charlotte, NC.

• Project Manager @ Salas O'Brien

  📍 Raleigh, NC.

THAT’S A WRAP