Spec27 Blog

Choosing a route into AI support is only the beginning. This article explains how robustness changes across AI-agent-first platforms, service platforms with AI, CRM/contact-centre ecosystems, and in-house builds -- and why every route needs repeatable testing across behaviour, policy, tools, workflows, safety, and change.

Intercom Fin and Zendesk were tested against the same knowledge base, policy rules and realistic customer-input variations. Here’s where their reliability held—and where it began to break.

Model upgrades are not simple component swaps. They can change how AI agents escalate, refuse, call tools, format outputs, and respond to edge cases. This post explains where drift hides and how teams can re-validate agents before switching models.

AI support agents are moving from novelty to infrastructure. This guide maps the third-party vendor market, including what these agents do, why adoption is accelerating, where they perform best, and what risks buyers should consider before deployment.

Sentiment classification looks like a simple task: take a financial statement and return a positive or negative label. It is used in research and production for financial-news monitoring, reporting workflows and downstream analysis. Clean accuracy, however, tells us only how a model behaves on the wording it was given. If the same financial relationship is expressed with different words, a different sentence structure or an added concessive clause, the classification should r

From Test Prompts to Validation Specs: Uplevelling AI Agent Testing

In a hurry? There's a preloaded example you can run in CI today, jump to how you can try this yourself.

On 11 June, we joined the Google DeepMind Startup Sessions at the Ministry of Sound in London – a morning of talks, demos, and live pitches bringing together AI startups and the Google DeepMind community. The lineup included a talk by Dr Raia Hadsell, a recap of Google’s annual developer conference, and a pitch showcase featuring around ten selected startups. We were glad to be one of them, presenting Spec27, our product for validating how AI agents behave before deployment a

At AI Engineer Europe 2026, Spec27 Principal Engineer Michal Cichra explored why engineering decisions need to be captured clearly for both human teams and AI systems. Watch the talk and learn how BDD, ADRs, and PRDs connect to specification-driven validation.

Third-party AI agents can help teams deploy faster, but they also create a validation challenge: the buyer owns the operational risk without full visibility into the internals. This guide explains how to evaluate vendor-built AI agents from the outside using specifications, realistic test cases, pass criteria, re-validation, and evidence.

How many agents do we have? And when do they start hiring their own agents? AI Agents are taking the enterprise by storm (at least on executive roadmaps!) and many leading AI tech companies are rolling out frameworks and platforms for AI Agents. Navigating through what works and what doesn't can be hard to keep track of. There's huge value in a lot of the deployments, but they also each present their own challenges. As the number of agents increases the interactions between t