A lot of what is being described as “next” is what we are already quietly doing with clients at Synaptyx AI. So rather than a hot take, here is how we are already leaning into those themes in practice 👇
✨ Agentic AI as an operating model We do not just build a cute little agent and walk away. We design meshes of planner, worker and judge agents around real workflows... with auditability, rollbacks and human in loop built in.
🧩 Vibe coding, at the right level We lean into conversational, “vibe coded” build only at a module or function level... to speed up design, flows and UI, not to magic up entire enterprise architectures by prompt. Fast where it is safe, disciplined where it needs to last.
🧠 Small AI + graphs over model worship In production, we often pair compact distilled models with ontologies and knowledge graphs that act as organisational memory. Big models help explore... small ones plus graphs help you ship reliably, at a sensible cost.
🛡️ Governance as a product, not a slide Our accelerators come with an Assurance layer from day one... clear agent identities, least privilege access, machine readable policies and replay when things misbehave. That is the only way regulated clients can take AI from PoC to BAU.
⚙️ Agentic accelerators, not monolithic platforms We chose accelerators over fully baked products for a reason. We bring 60 percent ready, agent ready building blocks that plug into your stack and your controls... so the intelligent enterprise that emerges still feels like yours.
If you are reading pieces like Bain’s and wondering what this looks like with your data, your legacy and your regulators... that is exactly the conversation we like having. Whats your take on some of the points mentioned?