BairesDev

Most conversations about kids and screens are about setting limits. Fewer are about what good screen time actually looks like. That's the framing Justice E., BairesDev's CTO, brought to a recent Business Insider piece on how tech leaders are setting tech rules for their own families. His household has a one-hour screen-time cap. But the harder line sits inside that hour: short-form content is out, because of its effect on attention span. He's more open to gaming. An hour spent in a game can teach teamwork, reaction time, problem-solving, grit, and how to deal with defeat. An hour spent scrolling short-form video doesn't. ➡️ Read the full piece from Business Insider: https://lnkd.in/dWaDRSVq

Most enterprises invest in AI backwards. The work of making AI pay off is roughly 70% people and process change, 20% tooling, and 10% models. Budget and attention tend to flow in the opposite direction. That's the observation our Fellow, Arun Nandi, Chief Data & AI Officer at Carrier, lays out in his latest piece. After two decades running data and AI programs at Fortune 500 companies, his read is direct: most AI failures trace back to process redesign, change management, and incentives. That work stays underfunded while budget chases models. Research from MIT Sloan backs the pattern. 70 to 90% of AI initiatives fail to scale into recurring operations. The breakdown point is rarely technical. If the model works in a POC but doesn't reach the P&L, the fix usually isn't more fine-tuning. It's better data pipelines, redesigned workflows, clear ownership, and the operating discipline to embed AI into how teams operate. Read the full article: https://lnkd.in/deEkx2qu

56% of developers say critically evaluating AI-generated output is the most essential baseline skill for developers in 2026. 67% say their teams don't have the knowledge to do it. That gap is where the next set of engineering challenges is showing up. Not in the tools, but in the validation layer beneath them. Our Q1 Dev Barometer asked how engineers are working with AI. 87% say they're comfortable using AI in their role, and the productivity gains are widely recognized. What's still evolving is how teams take ownership of AI output, and how consistently they validate it. This requires context, judgment, and time allocated for review, and it's a muscle many teams are still building. Justice E., our CTO, wrote about this for DEVOPSdigest. His argument: as AI takes on more of the execution, accountability for the outcome stays with the developer — which means validation, not acceleration, is where the next competitive edge will be built. ➡️ Read the full article: https://lnkd.in/duihNmpU 

Most companies aren’t struggling with AI anymore. They’re struggling with making it work in production. Agentic AI can query data, generate insights, and take action, but that’s exactly where things start to break: → Governance gaps → Unreliable outputs → No clear ownership or auditability On May 19, we’re bringing together leaders who are dealing with this in real environments: •🔥 Brett Berhoff 🔥 Top Voice 🏆 (Moderator) •Charles Boyle •Charles L. We’ll have a candid discussion on what it actually takes to operationalize agentic AI, especially within platforms like Snowflake. 📅 May 19 | 1 PM EDT 👉 Register: baires.dev/agentic-AI-work

AI tools generate code far faster than any human reviewer can meaningfully process it, turning traditional code review into a bottleneck, not a quality gate. And with less human translation in the middle softening a vague spec, a sloppy requirement doesn't produce a bug. It produces an entire feature built in the wrong direction, at machine speed. Our Fellow Ayman Shoukry, CTO at Specright, argues the fix isn't faster reviews or more reviewers, but restructuring where human judgment gets applied. He lays out a two-tier model: humans review intent, and agents review generated code. The pattern has precedent. The industry built trust in compilers and code generators the same way. What's new is the implication for engineering teams: specification quality is now directly measurable. Not in theory. In production, at scale. The question worth asking might not be whether AI-generated code is trustworthy, but whether the requirements feeding it are precise enough to warrant that trust. ➡️ Read the full article: https://lnkd.in/dm8k4gg3

AI has made it cheaper than ever to start a company. That doesn't mean it's easier to survive. In a Computerworld article by Agam Shah, our CEO, Nacho De Marco, stressed that AI is lowering the financial and operational barriers for founders. You can build something massive without outside capital. But only if your unit economics work. Building more with less is an advantage, not a finish line. The companies that last are the ones focused on solving real problems for real clients, not on how much they've raised. As Nacho put it: fundraising gives you dopamine, but real progress comes from customers. Read the full article: https://lnkd.in/g9KrP7-7

BairesDev ranked #10 on the Top 100 Companies to Watch for Fully Remote Jobs in 2026. Based on 424K+ vetted remote jobs analyzed in 2025, this ranking highlights companies operating remote at scale. As a company that’s been remote since day one, this recognition reflects that foundation. See the full list: https://lnkd.in/dwF2Q-9C

Multi-cloud isn’t a default strategy. Used incorrectly, it adds unnecessary complexity. Our Fellow, Chris Haire, CTO at VSCO®, breaks down when it actually makes sense and when it doesn’t. At VSCO, this came down to a series of deliberate decisions on how to structure their architecture. The result: → 40% reduction in infrastructure costs → 6x improvement in global performance Those gains came from making more intentional architectural decisions. The shift is moving away from trying to stay fully cloud-agnostic, and toward making intentional decisions about where flexibility matters and where deeper integration pays off. It also reflects a broader reality: cost, performance, and security are tightly connected. Treating them separately creates tradeoffs that compound over time. Multi-cloud only earns its complexity when it clearly improves outcomes. ➡️ Read the full breakdown: https://lnkd.in/dxyF-E9G

Companies aren’t built by tools. They’re built by people. That’s why hiring brilliant minds isn’t a side priority. It is the job. When everything else changes, that’s the only thing that holds: the people you bring in. People who think clearly. Who works hard. Who stays committed over time. That’s the difference between reacting to change and moving through it. In this clip from the panel “How High Can Unicorns Fly?” at the World Economic Forum’s Annual Meeting, our CEO, Nacho De Marco, explains why building the right team is what sustains a company long term. #WEF26

What does it actually take to move from cloud-native to AI-first engineering? Tomorrow, we’re bringing together leaders who are already doing it: • Chris Haire (CTO, VSCO) • Jason Davenport (Google) • Saurabh Gupta (CTO, Credit One Bank) • Ravi Bellur (Founder, Precession Partners) In this live panel, they’ll break down how organizations are: → Evolving architectures with Google Kubernetes Engine → Embedding AI into real-world applications with Vertex AI → Scaling data platforms across complex environments → Rethinking developer workflows for an AI-first era If you're thinking about what’s next for your platform strategy, this is a conversation worth joining. Last chance to register: https://lnkd.in/dzRC_kB7