Craft & Code: Able Perspectives

You've probably seen the numbers by now. With the advent of advanced AI, engineering teams are experiencing unprecedented acceleration. Developers, empowered by tools like Copilot, complete coding tasks 55% faster. The 2025 DORA Report shows 90% global AI adoption among developers, with over 80% reporting enhanced productivity.

Simon Bengen·Oct 20, 2025

As a leader, you’re constantly told that you need an "AI strategy." But what does that actually mean? It’s more than a shopping list of technologies or a vague mandate to "innovate." A robust AI strategy is a clear-eyed assessment of where you are, where you want to go, and how this powerful new toolkit can get you there faster and more effectively than your competition.

Andy McKinney·Sep 15, 2025

When midmarket companies talk about AI implementation, the conversation often begins with efficiency. How much can we automate manual processes? What's the ROI on automation? These are important questions, but there's a more strategic question that deserves equal attention: once you do achieve that efficiency, what happens next?

Andy McKinney·Aug 19, 2025

Growing mid-market companies often hit a wall trying to scale operations. Fortune 500 enterprises don’t thrive just because they’re big – they are big because they’ve built sophisticated internal coordination and systems to control everything seamlessly. The good news is you can reverse-engineer these enterprise playbooks using agentic AI systems to get Fortune 500-level coordination without the Fortune 500 headcount or overhead.

Arnon Bruno V. Santos·Aug 5, 2025

As a CTO, the AI boom brings new terminology that's both exciting and overwhelming. When it's your job to explain these complex ideas to your leadership team or board, who aren't in the tech trenches daily, the challenge grows.

Arnon Bruno V. Santos·Jun 18, 2025

In an era where AI systems increasingly shape our interactions with the world, the need for trustworthy AI has never been more critical. In this article, we will delve into the complexities of designing AI systems that are not only functional but also ethically sound, transparent, and secure. We explore six core elements of trustworthy AI—truthfulness, safety, fairness, robustness, privacy, and machine ethics—providing a pragmatic framework of assessment to counter some of the top known ethical issues with generative AI specifically.

Michelle Yi·Apr 8, 2025

Leading the engineering discipline at Able, I've had the privilege of working with a team that is both exceptional and naturally curious. Experimentation is in our DNA—we’ve always been early adopters, thoughtfully evaluating new tools and technologies before integrating them into our stack.

Pradeepa Dhanasekar·Mar 26, 2025

This "AI is revolutionizing..." thing has become a familiar refrain across industries, the journey from artificial intelligence research to practical implementation in private equity (PE) presents unique challenges. Integrating AI into high-stakes PE workflows, from sourcing deals to conducting due diligence and managing portfolios, requires more than just cutting-edge technology. In an industry built on expertise and trust, many investment professionals remain wary of cutting-edge black-box models guiding million-dollar decisions. This article explores the complex barriers between AI's theoretical potential and its practical application in PE, examining integration hurdles, trust issues, and real-world lessons from early adopters. We'll also investigate how bridging this gap requires a two-sided evolution: AI researchers developing more practical, interpretable solutions while PE firms build stronger technological foundations through investments in data infrastructure, talent, and cultural change.

Arnon Bruno V. Santos·Feb 7, 2025

Discover how vertical AI and efficient domain models are revolutionizing mid-market companies by streamlining development, reducing costs, and delivering accurate, industry-specific insights.

Michelle Yi·Jan 24, 2025