Productivity Apps

AI agents should never receive unrestricted access just because they can complete a task. The more tools, systems, and data an agent can reach, the more carefully its permissions must be designed. These five access control models provide different ways to keep agent actions scoped, secure, and auditable: → 𝗥𝗼𝗹𝗲-𝗕𝗮𝘀𝗲𝗱 𝗔𝗰𝗰𝗲𝘀𝘀 𝗖𝗼𝗻𝘁𝗿𝗼𝗹 Permissions are assigned through predefined roles. It works well when responsibilities are stable and agents can be mapped to roles such as support agent, finance agent, or administrator. → 𝗔𝘁𝘁𝗿𝗶𝗯𝘂𝘁𝗲-𝗕𝗮𝘀𝗲𝗱 𝗔𝗰𝗰𝗲𝘀𝘀 𝗖𝗼𝗻𝘁𝗿𝗼𝗹 Access decisions use attributes such as agent identity, resource type, requested action, location, time, risk, and business context. This enables more precise and dynamic policies. → 𝗔𝗰𝗰𝗲𝘀𝘀 𝗖𝗼𝗻𝘁𝗿𝗼𝗹 𝗟𝗶𝘀𝘁𝘀 Each resource maintains a list of agents or groups allowed to access it and the actions they may perform. This provides direct resource-level control but can become difficult to manage at scale. → 𝗠𝗮𝗻𝗱𝗮𝘁𝗼𝗿𝘆 𝗔𝗰𝗰𝗲𝘀𝘀 𝗖𝗼𝗻𝘁𝗿𝗼𝗹 Central authorities assign security labels to agents and resources. Strict policies determine access, and individual users or agents cannot override them. → 𝗖𝗮𝗽𝗮𝗯𝗶𝗹𝗶𝘁���-𝗕𝗮𝘀𝗲𝗱 𝗔𝗰𝗰𝗲𝘀𝘀 𝗖𝗼𝗻𝘁𝗿𝗼𝗹 Agents receive scoped tokens that authorize a specific action, resource, limit, or time period. This avoids granting broad standing permissions and works well for temporary, task-specific execution. No single access control model fits every agent workflow. Role-based control provides simplicity. Attribute-based control adds context. ACLs offer direct resource permissions. Mandatory control enforces strict policy. Capability-based control provides narrow, temporary authority. Which access control model best fits the AI agents operating inside your enterprise?

TRUE STORY: A trusted developer embedded a "kill switch" that locked out thousands of corporate users worldwide—triggered the moment his credentials were revoked. The cost? Hundreds of thousands in damages. The lesson? Insider threats from privileged users are real, and they’re escalating. 🧾 Case Summary In August 2025, Davis Lu, a former software developer at large corporation, was sentenced to four years in federal prison for deploying malicious code across his employer’s network. See https://lnkd.in/edJggBKu. After a corporate restructuring reduced his access, Lu planted sabotage scripts including a “kill switch” that activated when his account was disabled. The code crashed servers, deleted coworker profiles, and locked out thousands of users globally. His actions caused extensive disruption and financial loss, and his digital footprint revealed deliberate planning to evade detection. ✅ Help Prevent Cyber Sabotage from a Privileged Insider 1. Implement Role-Based Access Controls (RBAC) Limit access to sensitive systems based on job function. No single employee should hold unchecked privileges. 2. Conduct Regular Privilege Audits Regularly review who has elevated access—and why. Remove dormant or unnecessary accounts promptly. Such reviews should ideally take place at least quarterly. 3. Monitor for Anomalous Behavior Use behavioral analytics to flag unusual activity like privilege escalation, mass deletions, or off-hours access. 4. Enforce Code Review and Change Management Require peer review and approval for all code deployments, especially in production environments. 5. Deploy Insider Threat Detection Tools Invest in platforms that correlate user behavior, access logs, and system changes to identify risks early. 6. Establish a Clear Offboarding Protocol Disable access in a controlled sequence. Monitor systems closely during and after termination events. 7. Encrypt and Log Developer Actions Maintain immutable logs of code changes and admin actions. Encryption helps ensure integrity; logging helps ensure accountability. 8. Foster a Culture of Transparency and Respect Many insider threats stem from resentment or perceived injustice. Proactive communication and fair treatment matter. 9. Engage Legal and Cyber Teams Early Legal counsel should be looped in on high-risk terminations, especially those involving privileged users. 10. Build Relationships with Law Enforcement The FBI encourages proactive engagement to mitigate insider threats. Don’t wait until it’s too late. What other recommendations would you add? Please feel free to include in the comments.

As product managers, we spend a lot of time trying to understand user friction and solve for it in the products we build. But we often only perceive and solve for the most obvious form of friction when we in fact should be spending more of our time addressing the higher level forms of friction that our users regular experience. Let's break down the three types of friction users experience in our products: 💻 Interaction Friction - Friction a user experiences when interacting with our product's interface. It covers all aspects of the UI that may be hindering our users from accomplish their goal. Most of the popular best practices revolve around solving this type of friction, including things like A/B testing, usability testing, consistent interfaces, etc. 🧠 Cognitive Friction - Cognitive load refers to the total amount of mental effort being used in working memory. Cognitive friction is anything that increases cognitive load for the user. This is a far broader though often overlooked form of friction. Uber is a great example of an app that significantly reduced the cognitive friction compared to calling a taxi. Before you had to find the phone number for a local taxi company, call to schedule a ride, call back multiple times since no one picked up, get an untrustable estimate on when they will arrive, etc. Uber was able to remove nearly all of this cognitive friction from the ride hailing experience. 😩 Emotional Friction - Emotions a user feels that prevent them from accomplishing their goal. This is often the very hardest to perceive but by far the most impactful if you can resolve. Tinder offers the perfect example of emotional friction. The previous generation of dating experiences were incredibly intimidating since they required you to put in a ton of effort creating a profile, searching for potential matches, reaching out to people of interest, and ultimately experiencing a ton of rejection. Tinder's swipe right innovation quickly helped you determine mutual interest between both parties, removing much of the emotional friction of the previous generation of online dating experiences, resulting in online dating ultimately becoming mainstream. 👇 Read today's essay to learn more about each of these types of user friction and best practices for solving for them in your own product experience. https://lnkd.in/gHWW_WJ

Continuously growing utilization of AI applications in day-to-day business 💡   The potential of artificial intelligence to enhance productivity and communication is enormous, provided that the right security standards are in place. Currently, we at TÜV Rheinland Group are already using numerous different AI-tools, e.g. the following applications:   👉 TUV-GPT: Automatically compiles documents, aids in targeted research, and creates service descriptions. Unlike the OpenAI model, TUV-GPT operates in our own European cloud environment.   👉 VOIZE App: Allows vehicle inspectors to capture defects via voice command on their smartphones, with the AI automatically generating the necessary documentation.   👉 Legal Chatbot: Provides information on various legal topics, such as standard contracts, contract reviews, NDAs, damage cases, and IP rights.   👉 AI-based forecasting in Controlling: Utilizes machine learning to provide precise decision-making suggestions to management.   Our experience has shown its effectiveness. Embracing the benefits of new technologies and continuously improving them significantly contributes to our corporate goals. Currently, there are more AI applications in development. 🚀   How is your company dealing with the opportunities and challenges of AI? Looking forward to your insights! #KI #AI #Certification #Cybersecurity #tuvrheinland

How AI Boosted Our Engineering Productivity by 18% in Just 30 Days 🚀 That’s exactly what we discovered during a recent pilot program at Cognism, where we tested AI-powered coding assistants. The results were too exciting not to share! Why We Tried AI Our engineering team is always looking for ways to work smarter. We introduced this AI tool with three goals in mind: ✅ Automate repetitive tasks ✅ Accelerate development cycles ✅ Empower our team to focus on innovation We gamified adoption by rewarding our early adopters who showed the greatest productivity gains—and their feedback was key in shaping the rollout. The Numbers Don’t Lie Here’s what the pilot achieved: 📈 31% more issues resolved—less time on repetitive work, more time on creative problem-solving. 🔗 21% more pull requests (PRs) merged—quicker features, faster deliverability. ⏱️ 3% faster PR cycle time—a small win that we know can grow. Overall, an 18% productivity boost for our engineering team. What We Learned 1️⃣ It’s not perfect yet. AI isn’t replacing human developers, but it’s transforming how we approach mundane tasks. 2️⃣ Focus matters. The real value is freeing up time for innovation—our developers can concentrate on solving complex challenges, not repetitive ones. 3️⃣ It’s just the beginning. As these tools evolve, the potential gains could be exponential. The tool we selected : www.cursor.com Please comment below with your own findings and tools you are testing.

People have asked me what my AI productivity stack looks like. Here's a list of my 3 best AI tools that I use to scale myself, as a startup founder. 1) Zapier Zapier helps me automate workflows across different apps without coding. Put simply, you can eliminate a lot of mind-numbing, mundane tasks like data entry. I've used it to automate tasks like: (i) pinging users on WhatsApp after they've signed up on Peek, and (ii) updating call summaries into our CRM. They've made it possible to create these workflows by simply telling its AI zap creator what you want it to do. 2) Fireflies.ai As a founder, some days I have to be on calls for hours; with existing clients or onboarding new ones. But taking calls is the easy part. Generating summaries to keep track of what was discussed, and following up on actionable items is where it gets harder to keep up. Fireflies uses AI to help me transcribe, summarize, and follow up on calls with the help of Zapier. 3) Cursor (by Anysphere) I've previously written about how I build mini webapps to validate demand for a feature idea - before committing any engineering time and resources to build it into the product. Cursor is an AI code editor that helps me write code using natural language. So even as a non-technical founder, I can quickly build "minimally viable features" without having to distract my tech team. Personal finance is one area of our lives where AI can help you stay on top of otherwise very messy, and frustrating tasks. At Peek, we're trying to use AI to be your personal CFO. I'm always curious to know how you are using AI tools in your own work to supercharge your productivity. Let me know the best hacks you've discovered!

I had a full founder moment reading this… like are we really here already? 😅 The agent is already inside the building. Not maybe. Not soon. Already. And as a builder, that hits differently. Because we’re not just reading research—we’re literally building these systems right now. High: this is incredible technology. Low: we are absolutely underprepared. Oh la la: we’re deploying agents we can’t fully control. That emotional rollercoaster is real. But here’s the thing… research is great. Stats are great. Scary stories are "great". But as founders, we don’t get paid to be scared. We get paid to build responsibly anyway. So the real question is: How do you actually implement governance without killing velocity? Here’s how I’m thinking about it 👇 1️⃣ Stop treating governance like a policy doc—make it architecture Most teams start with “we need AI policies.” Great. Nobody reads them. And agents definitely don’t. Governance only works if it’s enforced by the system itself. That means access control, permissions, and constraints are built into how data flows—not written in a doc somewhere. If your governance can be bypassed by a prompt… it’s not governance. 2️⃣ Use least privilege + task-scoped access (this is the one you were thinking of) Give agents only the minimum access they need, for a specific task, for a limited time. Not blanket access to a system. Not “read everything in this folder.” This is classic least privilege combined with just-in-time (JIT) access and task-based permissions. If the agent is generating a report, it gets access to only the data required for that report—nothing more, nothing persistent. When the task is done, access is gone. No leftovers. 3️⃣ Give agents guardrails where it matters—at the moment of action We don’t need to block everything (that kills innovation). But we do need to control critical actions. Reading sensitive data. Moving files. Triggering workflows. That’s where enforcement lives. Think of it like parenting a very smart toddler—you don’t stop them from exploring, but you absolutely lock the dangerous cabinets. 4️⃣ Make “what happened” answerable in minutes, not days If something goes wrong—and it will—you need instant clarity. Who did what? What data was touched? Was it allowed? If your answer is “we need to investigate”… you’re already behind. Builders need systems where accountability is automatic, not forensic. And here’s my honest founder take: We are all building faster than governance is maturing. That’s just reality. But the winners won’t be the ones who slow down. They’ll be the ones who build governance into the speed. Because agents are not "tools" anymore. They are actors inside your tools. And once they’re inside… you don’t get to pretend you’re still in control. You need to build for control. #Kiteworks

AI productivity tools are real. These are 3 that deliver tangible leverage. In our world, leverage is everything. I am constantly testing new technology to find what actually works, not what is just a distraction. This is my current productivity stack. 1. Wispr Flow This is the most powerful voice-to-text automation I have used. It took my output from a 30-40 wpm bottleneck to 130 wpm. Its ability to handle accurate punctuation across all communications is a fundamental game-changer. 2. Fyxer AI An AI assistant directly connected to my inbox. It classifies all incoming email and, more importantly, drafts accurate replies for me. The company claims it gets you back an hour a day. I have found this to be accurate. 3. Lindy AI This tool allows non-technical people to build custom AI agents using simple prompts. This is key. You can automate any repetitive digital task. I use it for meeting prep, where it provides summaries of attendees and our past comms, and for post-call breakdowns, delivering clear topics and next steps. This is a stack for high-output execution. What tools are in your productivity stack?

Digital transformation doesn’t break at go-live. It breaks weeks before — when access control is an afterthought. Rule 4 – Set Access Before Rollout Access control is not a technical detail : it’s governance, security, and trust!  Every migration, rollout, or new workflow should define who sees what, who does what, and who decides what before configuration starts. Here’s what strong access governance looks like: ① Define access by design ⇒ Map permissions early ⇒ Identify data owners ⇒ Classify information (public, internal, restricted, confidential) ② Assign owners, not admins ⇒ Admins execute & Owners decide ③ Align permissions with processes ⇒ Roles must match workflows, not org charts ④ Automate reviews Access evolves [Quarterly reviews prevent silent privilege creep] 💥 The biggest mistake? Rolling out tools before defining access — and discovering too late that everyone can see everything… or no one can see anything! Access is not about restriction : It’s about clarity, security, and predictability! 💬 What’s the biggest access challenge you’ve seen in a digital project?

Authorization is a where we control the access, deciding what a person can or cannot do. Below are the various kinds of authorization : 𝟭. 𝗥𝗼𝗹𝗲-𝗕𝗮𝘀𝗲𝗱 𝗔𝗰𝗰𝗲𝘀𝘀 𝗖𝗼𝗻𝘁𝗿𝗼𝗹 (𝗥𝗕𝗔𝗖) Definition: Assigns permissions to roles, and users are assigned to these roles. Use Cases: Enterprise systems, where job functions determine access. Example: A “Manager” role has access to financial reports, and employees in that role inherit those permissions. 𝟮. 𝗔𝘁𝘁𝗿𝗶𝗯𝘂𝘁𝗲-𝗕𝗮𝘀𝗲𝗱 𝗔𝗰𝗰𝗲𝘀𝘀 𝗖𝗼𝗻𝘁𝗿𝗼𝗹 (𝗔𝗕𝗔𝗖) Definition: Access is granted based on attributes of the user, resource, environment, or action. Attributes: User’s department, resource sensitivity, time of access, etc. Example: A user can only access documents tagged with “Confidential” if their “clearance level” is “High.” 𝟯. 𝗗𝗶𝘀𝗰𝗿𝗲𝘁𝗶𝗼𝗻𝗮𝗿𝘆 𝗔𝗰𝗰𝗲𝘀𝘀 𝗖𝗼𝗻𝘁𝗿𝗼𝗹 (𝗗𝗔𝗖) Definition: The resource owner decides who can access their resources. Example: A file owner can grant read/write access to specific users. 𝟰. 𝗠𝗮𝗻𝗱𝗮𝘁𝗼𝗿𝘆 𝗔𝗰𝗰𝗲𝘀𝘀 𝗖𝗼𝗻𝘁𝗿𝗼𝗹 (𝗠𝗔𝗖) Definition: Access is determined by a central authority based on classification levels. Example: A “Top Secret” document can only be accessed by individuals with “Top Secret” clearance. 𝟱. 𝗣𝗼𝗹𝗶𝗰𝘆-𝗕𝗮𝘀𝗲𝗱 𝗔𝗰𝗰𝗲𝘀𝘀 𝗖𝗼𝗻𝘁𝗿𝗼𝗹 (𝗣𝗕𝗔𝗖) Definition: Decisions are made based on policies defined by administrators. Example: Access is allowed if the user’s location is “USA” and their subscription level is “Premium.” 𝟲. 𝗜𝗱𝗲𝗻𝘁𝗶𝘁𝘆-𝗕𝗮𝘀𝗲𝗱 𝗔𝗰𝗰𝗲𝘀𝘀 𝗖𝗼𝗻𝘁𝗿𝗼𝗹 (𝗜𝗕𝗔𝗖) Definition: Access is granted directly to an individual identity rather than roles or attributes. Example: Granting a specific user access to a single resource. 𝟳. 𝗙𝗶𝗻𝗲-𝗚𝗿𝗮𝗶𝗻𝗲𝗱 𝗔𝗰𝗰𝗲𝘀𝘀 𝗖𝗼𝗻𝘁𝗿𝗼𝗹 Definition: Granular access decisions based on detailed criteria, often a combination of ABAC and PBAC. Example: A user can only edit specific sections of a document during work hours. 𝟴. 𝗖𝗼𝗻𝘁𝗲𝘅𝘁-𝗔𝘄𝗮𝗿𝗲 𝗔𝗰𝗰𝗲𝘀𝘀 𝗖𝗼𝗻𝘁𝗿𝗼𝗹 Definition: Considers context, such as device, location, or behavior patterns, to decide access. Example: Allow access only if the user is on a trusted device within a specific location. 𝟵. 𝗭𝗲𝗿𝗼 𝗧𝗿𝘂𝘀𝘁 𝗔𝗰𝗰𝗲𝘀𝘀 𝗖𝗼𝗻𝘁𝗿𝗼𝗹 Definition: “Never trust, always verify.” Access is continuously evaluated, even after initial authentication. Example: A user is required to re-authenticate when accessing a sensitive resource, even within a trusted session. 𝟭𝟬. 𝗨𝘀𝗮𝗴𝗲-𝗕𝗮𝘀𝗲𝗱 𝗔𝗰𝗰𝗲𝘀𝘀 𝗖𝗼𝗻𝘁𝗿𝗼𝗹 (𝗨𝗕𝗔𝗖) Definition: Access is based on resource usage patterns and quotas. Example: A user can upload files up to a 10GB limit per month. 𝟭𝟭. 𝗧𝗮𝘀𝗸-𝗕𝗮𝘀𝗲𝗱 𝗔𝗰𝗰𝗲𝘀𝘀 𝗖𝗼𝗻𝘁𝗿𝗼𝗹 (𝗧𝗕𝗔𝗖) Definition: Access is granted based on tasks the user needs to perform. Example: A user can approve a document only if they are part of the approval task chain.