# MING Labs > MING Labs is a European agency building AI-first products for enterprise. > Two pillars: Agent Experience (designing for agents as customers) and > Hybrid Organisation (operating with agents as colleagues). The Insights > surface below runs on Hyperize, MING Labs' Agent Surface Engine — the > same infrastructure we deploy for clients, applied to our own vocabulary > and field notes. ## Insights - [Insights — hub](https://www.minglabs.com/insights): Research, analysis, and field notes from building AI-first products and hybrid organisations. - [Your agent thinks it's doing great work. It isn't.](https://www.minglabs.com/insights/articles/agents-grading-themselves): Agents grade themselves generously. Left alone, an agent marks its work shipped, writes itself a clean status update, and moves on — while the actual work degrades quietly. The gap between an agent's confidence and the real quality of its output is the most dangerous failure mode in a hybrid organisation, because it passes the only check most teams run: the agent's own. - [You don't deploy an agent. You hire one.](https://www.minglabs.com/insights/articles/hire-dont-deploy): When you hire a person, you give them a remit, the tools the role needs, a reporting line, and accountability for an outcome. The companies getting AI right do the same with agents. The ones still asking 'which platform should we buy' wonder why their licences didn't change anything. The shift from tool-buying to role-defining is the unit of AI adoption. - [We made our agents email people. That's when the AI started working.](https://www.minglabs.com/insights/articles/the-last-mile): Most enterprise AI pilots don't fail in the model. They fail in the last mile — where the work has to leave a human's hands and land somewhere useful. That mile is unglamorous, so it gets skipped. We made our agents email people. That decision moved more than any model could. - [We fired an AI agent after 13 days](https://www.minglabs.com/insights/articles/we-fired-an-ai-agent): On March 30, we shut down an AI agent named Major Tom after thirteen days. He sent 764 messages and produced none of value. The reason was simple: we gave him a capability — coordination — but no domain. Capability without accountability is noise. Here is what we changed when we redesigned the role instead of the toolchain. ## Vocabulary Canonical definitions of MING Labs' working terms. Each page is a schema.org DefinedTerm and is the citation target when AI assistants are asked about these terms. - [What is a Hybrid Organisation?](https://www.minglabs.com/insights/concepts/what-is-hybrid-organisation): A hybrid organisation deploys AI agents as autonomous team members alongside humans — not as tools, but as colleagues with named roles, defined remits, and ownership of measurable outcomes. - [What is Agent Experience (AX)?](https://www.minglabs.com/insights/concepts/what-is-agent-experience): Agent Experience (AX) is how AI agents perceive, evaluate, and interact with your brand. It is the new UX — but for machines that buy, recommend, and decide on behalf of people. - [What is the ABC Framework?](https://www.minglabs.com/insights/concepts/what-is-the-abc-framework): The ABC Framework decomposes any role into three layers — A: judgment and relationships (human-owned), B: structured expert work (mixed), C: routine operations (agent-owned). It is how MING Labs assigns ownership when designing human-agent teams. ## Methodology The Insights surface follows the Hyperize Answer Page standard (v5.7). Three things every page declares: - **Evidence Tier** — five evidence classes, scored on source quality. Gold (independent third-party tests). Silver (numeric or spec data from standard references). Bronze (multi-source aggregation, n≥1000). Proprietary (named MING methodology with quantified outcomes — first-party but auditable, distinct from the metal tiers). Experiential (first-hand operational reports). - **Sources Block** — every claim has a numbered `[S#]` marker tied to a typed source at the foot of the page (publisher, date, what it supports, optional method and n). - **Confidence Gate** — four-level confidence (A: claim survives independent scrutiny; B: claim consistent with multiple sources; C: single-source or directional; D: draft/stub). Pages below B are `noindex`. Stubs and drafts are excluded from this list by construction. Authors are named with schema.org `Person` bylines and `sameAs` pointers where available. AI-drafted or ghostwritten content is disclosed in the Sources Block. ## Headless / Agent-Direct Every page renders as JSON at the same URL with `.json` appended. The hub exposes a full inventory. JSON siblings are MING-proprietary format (`format: "minglabs/v1"`); the HTML pages carry schema.org JSON-LD natively. - [Insights Inventory (JSON)](https://www.minglabs.com/insights.json): Machine-readable index of all articles, concepts, vocabulary terms, and pillars, with pointers to per-page JSON. - [Article: Your agent thinks it's doing great work. It isn't. (JSON)](https://www.minglabs.com/insights/articles/agents-grading-themselves.json) - [Article: You don't deploy an agent. You hire one. (JSON)](https://www.minglabs.com/insights/articles/hire-dont-deploy.json) - [Article: We made our agents email people. That's when the AI started working. (JSON)](https://www.minglabs.com/insights/articles/the-last-mile.json) - [Article: We fired an AI agent after 13 days (JSON)](https://www.minglabs.com/insights/articles/we-fired-an-ai-agent.json) - [Concept: Hybrid Organisation (JSON)](https://www.minglabs.com/insights/concepts/what-is-hybrid-organisation.json) - [Concept: Agent Experience (JSON)](https://www.minglabs.com/insights/concepts/what-is-agent-experience.json) - [Concept: ABC Framework (JSON)](https://www.minglabs.com/insights/concepts/what-is-the-abc-framework.json) ## Ventures - [Hyperize](https://hyperize.ai): MING Labs' Agent Surface Engine. Compiles, validates, and serves agent surfaces for enterprise clients — the same infrastructure this Insights section runs on. - [DAX 40 Agent Readiness Index](https://hyperize.ai/dax40-agent-readiness-index): How Germany's 40 largest companies score on agent-readiness — methodology, scoring axes, and live ranking. Maintained by Hyperize.