The FarmGAP application was a promising AI-built proof of concept that had not yet been put into use. Before the platform could move toward launch, SG Farm Services needed a technical audit to assess the codebase, surface security and...
AI can generate code quickly, but speed alone does not produce reliable software. Generating thousands of lines of code in seconds is counterproductive if it compromises structural integrity, security, and overall quality. Fast technical...
Engineering leaders are being asked to navigate something genuinely new. Not just a technology upgrade, and not just another platform shift. Instead, we face a fundamental change in how software gets built, who builds it, and what it...
For more than 15 years, AgilityFeat has helped companies build software across Latin America. As AI reshapes how products are built, we created something new: Builder Pods. These are small, senior, AI-native nearshore squads designed for...
AgilityFeat CTO Alberto González recently appeared on the Software Defined Talk podcast to discuss the realities of building secure, scalable AI implementations for enterprise use. While the conversation also covers WebRTC foundations,...
Most companies struggle when scaling engineering teams because hiring is often treated as a sourcing activity rather than an alignment process. Speed becomes the primary objective, while ownership expectations, tenure patterns, and...
Building LLM-driven applications is not like building traditional software. The rules are different, the failure modes are different, and the gap between a working AI prototype and a production-ready AI system is wider than most teams...
At annual conferences across any vertical, AI has become the default lens for discussing modernization. Fintech Americas Miami 2026 was no exception. At the event, every conversation about banking modernization, core systems, customer...
When the conversation turns to AI, the lens almost always points westward. To San Francisco, Palo Alto, or to the handful of hyperscalers dominating the headlines. It's an understandable bias. But it's also an increasingly expensive one....
Spec-driven AI tools automate complex workflows by first generating detailed specifications. These are clear, step-by-step plans that humans review before executing them precisely, minimizing errors across industries like software...
In fintech and other regulated industries, technology decisions carry higher stakes than in most software domains. Systems must process financial transactions accurately, remain available under heavy load, and comply with strict...
When AI agents interact with live systems and sensitive data, safety can’t rely on a single model or moderation filter. True protection comes from layered guardrails: a structured stack spanning model-level safety, structured tool...
If it’s true that AI allows us to build anything, and to build it more efficiently than ever before, are we entering an age of software abundance? Or are we about to experience a deluge of useless software that no one actually needs? The...
Both startups and established enterprises use MVPs and POCs to validate ideas before committing to full-scale builds. AgilityFeat’s expert nearshore software development services offers a way to experiment quickly while keeping costs and...
Client: Worksource (AI Startup Concept) | Industry: HR Technology | Project Type: Hybrid AI Proof of Concept | Timeline: 2 weeks "Working with [the AgilityFeat team] was great. It is amazing to tell someone the idea you have in your head...
Integrating AI development tools like Cursor, Cline, and GitHub Copilot into your software development workflow promises speed and productivity. But without best practices, it can also create security vulnerabilities, technical debt, and...
AI code generation transformed how quickly my teams could ship features. We went from week-long implementations to same-day deployments. The velocity was real and initially, it felt like a competitive advantage. Then we started scaling....
One of the hardest questions companies face is when to scale a development team. Scale too soon, and you'll burn runway on hiring, onboarding, and building features the market hasn't validated yet. Scale too late, and competitors—or your...
This post is grounded in two working Voice AI demos our expert AI integrations team built to explore how authority, execution, and human-in-the-loop control actually behave in production. If you are automating customer support in a...
For any enterprise running applications on AWS, achieving and maintaining compliance is a constant, complex battle. In this context, compliance means continuously aligning your AWS accounts and resources with security standards and...
Today's innovation economy is in the midst of a full-scale talent war to hire LLM engineers and AI specialists who can build real-world software products powered by advanced AI capabilities. This isn't just about developers who use AI...
When building a Minimum Viable Product (MVP) for a client, we prioritize two things: speed to market and cost efficiency. But moving fast often comes at the expense of building a scalable, robust foundation. This creates a common dilemma...
Most engineering leaders know the feeling of staring at a long feature roadmap and quietly asking, "Do we know if any of this will matter to customers?" Evidence-driven engineering is about refusing to guess, and insisting on proof. In a...
Businesses in financial services, insurance, and e-commerce all rely on complex decision logic to automate approvals, pricing, and compliance. Traditionally, these rules are hardcoded into applications, making every policy tweak or...
Modern engineering teams are recalibrating how they deliver software by balancing speed, safety, and culture. In The Evolution of DevOps: Automation, Scale, and the AI Frontier (Episode 59 of the Scaling Tech Podcast, proudly sponsored by...