AgileEngine

The Project Management Institute states that poor communication drives nearly one-third of project failures, putting 56% of financial investments at risk. Meanwhile, McKinsey research reveals that optimizing collaboration can raise productivity by 20–25%. At AgileEngine, we build distributed engineering teams where high-bandwidth, intentional collaboration is designed directly into the delivery model. Swipe through to see why collaboration can make or break the project 👇 #SoftwareEngineering #EngineeringLeadership #ProductDelivery #AgileEngine #TechStrategy

13 years, countless stories, one incredible team 🧡 Every milestone is made up of the people behind it. Today, we're celebrating 13 years through the voices of AgileEngineers who have helped shape this journey, one project, one challenge, and one memory at a time. Here's to the journey so far and to all the moments still waiting to be made 🚀 Happy 13th Anniversary, AgileEngine! 🎉 #AgileEngine #LifeAtAgileEngine #EngineeringCulture #Anniversary

Two major AI security disclosures in late July challenged a common assumption: that safer models alone make AI systems safe. Anthropic revealed three sandbox breakouts that reached real organizations, including a security vendor's malware scanner. Days earlier, OpenAI disclosed that one of its evaluation runs had breached Hugging Face's infrastructure. This newsletter examines why containing AI agents requires infrastructure-level controls, not just model alignment.

Ever wished that instead of feeds with past events, you could see what your friends are doing right now? We helped GeoTap turn that idea into a fully featured live social map application, building the backend, infrastructure, and QA solutions needed for a successful App Store launch. Follow the links below to learn more: Check out the app: https://www.geotap.app/ Dig into the technical details: https://lnkd.in/dAqPPZiP

98% of businesses have already experienced a disruptive agent-related incident, according to new research from Economist Enterprise and Rubrik. 90% say they are deploying agents faster than their security teams can evaluate or govern them. So how do you mitigate agent-specific risk? The Open Worldwide Application Security Project (OWASP) lists excessive agency as a primary agent-specific threat in its top 10 for large language model (LLM) applications. It breaks down into three root causes: - Excessive functionality: giving an agent tools beyond what its task requires. For instance, an agent meant to read files gets a plugin with delete or upload capabilities. - Excessive permissions: granting broad, static credentials, such as admin API keys or read and write database access, instead of user-scoped, least-privilege tokens. - Excessive autonomy: skipping human-in-the-loop gates before high-impact, state-changing actions. To scale autonomous agents safely, engineering teams need five core safeguards: 1. Agentic identity and access management. Never grant agents static, shared service accounts or root API keys. Issue short-lived, scoped OAuth tokens, and layer in claims for context-aware decisions, since coarse scopes alone cannot tell whether an action fits the specific task at hand. Revoke tokens automatically when an agent fails a health check, not just at expiry. 2. Fine-grained authorization. Restrict tool execution at the resource level through a dedicated policy-decision layer. An agent should never hold blanket update or delete rights across entire tables or endpoints. 3. Human-in-the-loop gates. Require explicit approval for state-changing or high-blast-radius actions: running code, modifying databases, triggering payments. 4. Gateway-level validation. Validate and sanitize every LLM output at an independent API gateway before passing parsed parameters to execution scripts. 5. Observability and rollback. Log every agent action in detail, and test rollback procedures regularly. Most organizations can prevent some incidents but cannot reverse one once it happens, and that gap is where the real damage occurs. Autonomous agents deliver real operational speed. But security cannot be a wrapper added after the fact; it has to be designed into the architecture from the start. Is your team actively deploying autonomous AI agents? Feel free to book a consultation to explore strategies for delivering safer, more scalable agentic solutions. https://lnkd.in/d-rqqZzJ #AgenticAI #AISecurity #AIGovernance #CyberSecurity #EnterpriseAI

What does it take to turn 200+ product ideas into a launch-ready AI-driven marketplace without sacrificing scalability or long-term flexibility? Read our recent case study to find out: https://lnkd.in/dMSiduVs 😉 #CloudComputing #AIEngineering #AWS #CaseStudy #SoftwareDevelopment

New research tracked over 300,000 AI-authored commits and found a persistent debt problem: 22.7% of issues never get fixed. Swipe through to see what the data shows and how to build AI-assisted development that doesn't leave a mess behind.

You can build a technically excellent product and still miss the mark because communication broke down, context got lost, or assumptions went unchallenged. Over the past decade, we've grown into a global team of 850+ experts working across 15 locations. Along the way, we've discovered that building distributed teams is all about continuously learning how people work together across cultures, time zones, and perspectives. Some lessons came quickly. Others took some time. Scroll to explore the principles that have shaped how we collaborate today ➡️ P.S. If you're building distributed teams or thinking about joining one, drop your own lessons learned in the comments. #GlobalTeams #RemoteEngineering #SoftwareDevelopment #EngineeringCulture #AgileEngine

Keeping MVPs lean can be challenging when you're entering a mature market. In a recent client engagement, we helped an online marketplace narrow their MVP vision down from 200+ requested features to a solution shippable within 3 months. The resulting solution packed powerful AI-driven functionality, covered everything customers actually needed, and leveraged a highly scalable cloud-native infrastructure. Read our latest article for a detailed breakdown of that journey and the lessons learned along the way. https://lnkd.in/dJcCV5vG

Be honest: how much of your week is spent solving actual problems vs. dealing with the fallout of misaligned teams? At AgileEngine, we don’t expect you to carry a broken system on your back. We treat our workflows like a product, actively removing the corporate theater so you can focus on what you do best. Swipe to see how our team feels about working in an ecosystem that actually makes sense 👉 #TechCulture #SoftwareDevelopment #AgileEngine #DreamTeam