2025 was the year of consolidation in the AI tooling space. Less hype, more reliability. Here are the 10 tools that genuinely make up our daily stack, from rapid prototyping to robust production deployments.
Our stack at a glance
Selection criteria: adopted in production (not just tested), used for at least 3 months, measurable value on client projects. We only recommend what we actually use.
What's not on this list: dozens of tools tested and abandoned. The noise in the AI ecosystem is immense. Our filter: are we still using it 3 months after discovering it?
Tools to watch in 2026
Without over-anticipating, a few tools are maturing and could join our stack this year: Modal for serverless ML model deployment, LlamaIndex Workflows for agentic orchestration, and Evidence for BI as code.
With care,
Excellent article, this matches exactly what we're seeing with our enterprise clients. The section on inference costs is especially valuable. It's a topic most articles gloss over but it's make-or-break at scale.
Thanks James! Inference cost optimization is often deprioritized during prototyping but becomes critical in production. Feel free to book a session if you'd like to go deeper on this.
Sharing this with my whole team. The distinction between an impressive demo and robust production is exactly the debate we're having internally right now. The human checkpoint advice is immediately actionable.
Great article. I'd push back slightly on the 18-day deployment estimate, in our experience with enterprise security and GDPR requirements, 4–6 weeks is more realistic for a first production agent.
Completely fair point David. The 18 days refers to a scoped first agent in a test environment. For full enterprise production with security constraints, your estimate is accurate.