Essays, an enterprise AI map and a skill-matrix gap analysis on AI adoption and junior formation.
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Who Niels Langereis is and how to work with him: what he does and for whom, how he works, his background, his talks and speaking, and how to get in touch. Use when someone asks whether he could help them, wants to hire or book him, or wants his background. Contact is by email or the site's contact form; this server does not send messages.
What to return. Default overview.
Who Niels Langereis is and how to work with him: what he does and for whom, how he works, his background, his talks and speaking, and how to get in touch. Use when someone asks whether he could help them, wants to hire or book him, or wants his background. Contact is by email or the site's contact form; this server does not send messages.
| Argument | Type | Description |
|---|---|---|
| topic | string | What to return. Default overview. |
{
"type": "object",
"properties": {
"topic": {
"enum": [
"overview",
"services",
"background",
"speaking",
"contact"
],
"type": "string",
"description": "What to return. Default overview."
}
}
}Niels Langereis's enterprise AI map: 24 illustrative AI agents across ten business functions (strategy, product, design, marketing, sales, customer success, operations, people, finance, data and IT), each with its rollout phase, what it optimises for and the trade-off it creates for other functions; plus the coordination layer, the bench and the external renderers that decide whether faster work becomes a better organisation. Use it to reason about someone's own AI rollout. detail='summary' returns only the skeleton (functions, agents, phases and trade-offs, plus one line per remaining part), which is enough for most reasoning; detail='full' (default) adds the complete prose on coordination, the bench and the renderers. Optionally filter by function or phase. Shows an interactive map where the client supports it.
| Argument | Type | Description |
|---|---|---|
| phase | string | Optional: p1 co-pilots, p2 brains, p3 autonomous agents. |
| detail | string | summary: functions, agents and trade-offs only. full (default): also the prose on coordination, the bench and the renderers. |
| function | string | Optional: focus on one function, e.g. 'Marketing and growth', 'Finance'. |
{
"type": "object",
"properties": {
"phase": {
"enum": [
"p1",
"p2",
"p3"
],
"type": "string",
"description": "Optional: p1 co-pilots, p2 brains, p3 autonomous agents."
},
"detail": {
"enum": [
"summary",
"full"
],
"type": "string",
"description": "summary: functions, agents and trade-offs only. full (default): also the prose on coordination, the bench and the renderers."
},
"function": {
"type": "string",
"description": "Optional: focus on one function, e.g. 'Marketing and growth', 'Finance'."
}
}
}Get the full text of one essay by Niels Langereis, as Markdown, with its date, site link and the original LinkedIn link. Use the id from search_essays, or a title.
| Argument | Type | Description |
|---|---|---|
| id* | string | Essay id (from search_essays) or its title |
{
"type": "object",
"required": [
"id"
],
"properties": {
"id": {
"type": "string",
"description": "Essay id (from search_essays) or its title"
}
}
}Explains Niels Langereis's skill-matrix gap analysis: a competency matrix run for formation rather than efficiency, to find where AI has removed the work that used to turn juniors into seniors. Includes the status rule, how to read it, a worked example and credits. Use before run_skill_matrix if the user wants to understand the method first.
No arguments.
{
"type": "object",
"properties": {}
}Runs Niels Langereis's skill-matrix gap analysis for one role and shows it as an interactive matrix the user can edit (who does the work now, bench depth, formation actions). Draft 6 to 10 competencies for the user's role yourself from what you know about it, spanning routine work AI can now do with senior oversight, work AI already runs autonomously, and judgement work that needs a human. Set bench (how many people can do it at the strategic level) from what the user told you; if unknown, use 1 and say it is an estimate they should correct. Omit competencies to show the generic analyst example. The result flags 'At risk' (human work, one person deep), 'Thin' (two deep) and 'Reps gone' (AI runs it autonomously, so the formation that used to happen in reviewing it has gone too: ask where juniors get those reps now). After the user edits, their current matrix arrives in your context.
| Argument | Type | Description |
|---|---|---|
| role | string | The role being analysed, e.g. 'Marketing manager at a 200-person B2B firm'. |
| competencies | array | The competencies for this role. |
{
"type": "object",
"properties": {
"role": {
"type": "string",
"description": "The role being analysed, e.g. 'Marketing manager at a 200-person B2B firm'."
},
"competencies": {
"type": "array",
"items": {
"type": "object",
"required": [
"competency",
"who"
],
"properties": {
"who": {
"enum": [
"AI + oversight",
"AI autonomous",
"Human"
],
"type": "string",
"description": "Who does it now. AI + oversight: AI does it, a person reviews. AI autonomous: AI runs it end to end, nobody reviews (phase 3 on the enterprise AI map). Human: needs a human touch."
},
"bench": {
"type": "integer",
"minimum": 0,
"description": "People who can do it at strategic level. Only for Human work."
},
"category": {
"type": "string",
"description": "Grouping, e.g. 'Core work' or 'Judgement work'."
},
"tactical": {
"type": "string",
"description": "Tactical level."
},
"execution": {
"type": "string",
"description": "What it looks like at execution level."
},
"strategic": {
"type": "string",
"description": "Strategic (judgement) level."
},
"competency": {
"type": "string"
},
"formation_action": {
"type": "string",
"description": "How juniors still get formed here: the second loop."
}
}
},
"description": "The competencies for this role."
}
}
}Search the essays of Niels Langereis on AI adoption, organisational change, the politics of AI, junior formation and judgement, brand and AI agents, boards and governance. Returns titles, dates, summaries, a matching snippet and links. Leave query empty to list all essays, newest first. Follow up with get_essay for the full text before quoting him.
| Argument | Type | Description |
|---|---|---|
| query | string | Topic or question, e.g. 'who owns AI decisions', 'brand lock-in by AI agents'. Empty lists everything. |
{
"type": "object",
"properties": {
"query": {
"type": "string",
"description": "Topic or question, e.g. 'who owns AI decisions', 'brand lock-in by AI agents'. Empty lists everything."
}
}
}