Things I’ve Learned in My 10 Years as an Engineering Manager

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TLDR: Jampa Uchoa shares insights from 10 years as an engineering manager, emphasizing that roles vary per team needs, everyone should care about the product, processes must be questioned, and trust in teams is crucial. Successful management requires transparency, communication strategies, and a focus on empowering teams to thrive independently. Managers should navigate between being a player, coach, and cheerleader, while ensuring that none are bottlenecks. Each team must adapt processes to maintain efficiency, with a focus on the outcomes rather than the processes themselves.

https://www.jampa.dev/p/lessons-learned-after-10-years-as

Why AI Assistants Still Face Barriers at Scale

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AI assistants are gaining visibility in workplaces, yet many organizations hesitate to scale their deployment due to security, governance, and trust issues. Despite low usage rates (18% weekly, 8% daily in the US), there's a push for broader adoption, particularly in collaboration software. Companies see a need to leverage AI for efficiency but face challenges like unclear ROI and training needs. Interest in tools like Microsoft 365 Copilot and OpenAI's ChatGPT is high, with many exploring multiple AI solutions. Security risks associated with AI integrations and oversight remain key concerns as enterprises navigate towards larger deployments.

https://www.computerworld.com/article/4119325/why-ai-assistants-still-face-barriers-at-scale.html

As CIOs Focus on AI Integration, New Tools Complicate the Agenda

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CIOs are shifting focus from AI experimentation to integration, prioritizing the execution of existing AI investments. However, the emergence of on-device AI, exemplified by Lenovo’s Qira, adds complexity to this integration process. While offering benefits like improved data privacy and reduced cloud costs, on-device AI also presents challenges such as technical debt and vendor lock-in.

https://www.informationweek.com/ai-innovations/as-cios-focus-on-ai-integration-new-ai-tools-complicate-the-agenda-in-2026

Аgentic AI Security Measures Based on the OWASP ASI Top 10

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The OWASP Foundation released a playbook outlining the top 10 risks of deploying autonomous AI agents, including goal hijacking, tool misuse, and privilege abuse. These risks arise from the agents’ ability to make decisions and process data without human oversight. Mitigation strategies include enforcing least autonomy and privilege, using short-lived credentials, and requiring human confirmation for critical actions.

https://www.kaspersky.com/blog/top-agentic-ai-risks-2026/55184/

Bypassing Windows Administrator Protection

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TLDR: Project Zero's blog discusses Windows 11's new Administrator Protection feature, intended to enhance security over the old UAC system. Despite improvements, vulnerabilities allowing bypass of this protection were identified by security researcher James Forshaw during initial testing. He discovered multiple means to gain administrative privileges, attributing the flaws to the interrelated behaviors of Windows security mechanisms. Ultimately, a fix was issued by Microsoft to mitigate these bypasses, but the analysis suggests a more radical overhaul of Windows security measures may be needed to truly address longstanding issues.

https://projectzero.google/2026/26/windows-administrator-protection.html

Most Workers Spend 3+ Hours Per Week Cleaning up AI Workslop

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TLDR: Workers spend 3+ hours weekly revising low-quality AI outputs, known as “AI workslop.” Despite this, 92% believe AI boosts productivity, indicating it saves more time than it costs. Key issues stem from AI in data analysis and untrained employees, leading to negative consequences like rejections and lost clients. Training can improve outcomes, with 94% of trained workers citing productivity gains. Accountability in AI-generated work remains crucial.

https://zapier.com/blog/ai-workslop/?utm_source=Iterable&utm_medium=email&utm_campaign=itbl-gbl-pgv-ooc-_all__blog_ai_workslop_20260126-ctn

Cybersecurity’s New Business Case: Fraud

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Cybersecurity leaders in government face budget cuts and staffing shortages while fraud increases. Focus should shift from technical jargon to issues like financial fraud, AI-generated scams, and citizen trust. The article emphasizes urgent need for cyber teams to engage in fraud prevention as online financial fraud surges, notably with pandemic-related scams costing billions. Recommendations include collaboration with auditors and implementing robust controls to combat identity fraud, highlighting a collective effort necessary across political lines to address these challenges.

https://www.govtech.com/blogs/lohrmann-on-cybersecurity/cybersecuritys-new-business-case-fraud

Who Approved This Agent? Rethinking Access, Accountability, and Risk in the Age of AI Agents

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AI agents boost productivity by automating tasks, but their rapid deployment complicates accountability, creating security risks. They bypass traditional access models, accumulating broad permissions without clear ownership. Three types of agents exist: personal (user-owned, low risk), third-party (vendor-owned, moderate risk), and organizational (shared, high risk). Organizations must rethink risk management, establish clear ownership, and map user-agent interactions to avoid authorization bypass problems. Unmanaged AI agents represent significant risks due to their autonomous nature and unclear responsibilities.

https://thehackernews.com/2026/01/who-approved-this-agent-rethinking.html

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